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Saloner R, Lobo JD, Paolillo EW, Campbell LM, Letendre SL, Cherner M, Grant I, Heaton RK, Ellis RJ, Roesch SC, Moore DJ, Grant I, Letendre SL, Ellis RJ, Marcotte TD, Franklin D, McCutchan JA, Smith DM, Heaton RK, Atkinson JH, Dawson M, Fennema-Notestine C, Taylor MJ, Theilmann R, Gamst AC, Cushman C, Abramson I, Vaida F, Sacktor N, Rogalski V, Morgello S, Simpson D, Mintz L, McCutchan JA, Collier A, Marra C, Storey S, Gelman B, Head E, Clifford D, Al-Lozi M, Teshome M. Identification of Youthful Neurocognitive Trajectories in Adults Aging with HIV: A Latent Growth Mixture Model. AIDS Behav 2022; 26:1966-1979. [PMID: 34878634 PMCID: PMC9046348 DOI: 10.1007/s10461-021-03546-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/22/2021] [Indexed: 11/12/2022]
Abstract
Despite the neurocognitive risks of aging with HIV, initial cross-sectional data suggest a subpopulation of older people with HIV (PWH) possess youthful neurocognition (NC) characteristic of SuperAgers (SA). Here we characterize longitudinal NC trajectories of older PWH and their convergent validity with baseline SA status, per established SuperAging criteria in PWH, and baseline biopsychosocial factors. Growth mixture modeling (GMM) identified longitudinal NC classes in 184 older (age ≥ 50-years) PWH with 1–5 years of follow-up. Classes were defined using ‘peak-age’ global T-scores, which compare performance to a normative sample of 25-year-olds. 3-classes were identified: Class 1Stable Elite (n = 31 [16.8%], high baseline peak-age T-scores with flat trajectory); Class 2Quadratic Average (n = 100 [54.3%], intermediate baseline peak-age T-scores with u-shaped trajectory); Class 3Quadratic Low (n = 53 [28.8%], low baseline peak-age T-scores with u-shaped trajectory). Baseline predictors of Class 1Stable Elite included SA status, younger age, higher cognitive and physiologic reserve, and fewer subjective cognitive difficulties. This GMM analysis supports the construct validity of SuperAging in older PWH through identification of a subgroup with longitudinally-stable, youthful neurocognition and robust biopsychosocial health.
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Qu Y, Middleton MS, Loomba R, Glaser KJ, Chen J, Hooker JC, Wolfson T, Covarrubias Y, Valasek MA, Fowler KJ, Zhang YN, Sy E, Gamst AC, Wang K, Mamidipalli A, Schwimmer JB, Song B, Reeder SB, Yin M, Ehman RL, Sirlin CB. Magnetic resonance elastography biomarkers for detection of histologic alterations in nonalcoholic fatty liver disease in the absence of fibrosis. Eur Radiol 2021; 31:8408-8419. [PMID: 33899143 PMCID: PMC8530863 DOI: 10.1007/s00330-021-07988-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 03/25/2021] [Accepted: 04/02/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVES To investigate associations between histology and hepatic mechanical properties measured using multiparametric magnetic resonance elastography (MRE) in adults with known or suspected nonalcoholic fatty liver disease (NAFLD) without histologic fibrosis. METHODS This was a retrospective analysis of 88 adults who underwent 3T MR exams including hepatic MRE and MR imaging to estimate proton density fat fraction (MRI-PDFF) within 180 days of liver biopsy. Associations between MRE mechanical properties (mean shear stiffness (|G*|) by 2D and 3D MRE, and storage modulus (G'), loss modulus (G″), wave attenuation (α), and damping ratio (ζ) by 3D MRE) and histologic, demographic and anthropometric data were assessed. RESULTS In univariate analyses, patients with lobular inflammation grade ≥ 2 had higher 2D |G*| and 3D G″ than those with grade ≤ 1 (p = 0.04). |G*| (both 2D and 3D), G', and G″ increased with age (rho = 0.25 to 0.31; p ≤ 0.03). In multivariable regression analyses, the association between inflammation grade ≥ 2 remained significant for 2D |G*| (p = 0.01) but not for 3D G″ (p = 0.06); age, sex, or BMI did not affect the MRE-inflammation relationship (p > 0.20). CONCLUSIONS 2D |G*| and 3D G″ were weakly associated with moderate or severe lobular inflammation in patients with known or suspected NAFLD without fibrosis. With further validation and refinement, these properties might become useful biomarkers of inflammation. Age adjustment may help MRE interpretation, at least in patients with early-stage disease. KEY POINTS • Moderate to severe lobular inflammation was associated with hepatic elevated shear stiffness and elevated loss modulus (p =0.04) in patients with known or suspected NAFLD without liver fibrosis; this suggests that with further technical refinement these MRE-assessed mechanical properties may permit detection of inflammation before the onset of fibrosis in NAFLD. • Increasing age is associated with higher hepatic shear stiffness, and storage and loss moduli (rho = 0.25 to 0.31; p ≤ 0.03); this suggests that age adjustment may help interpret MRE results, at least in patients with early-stage NAFLD.
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Affiliation(s)
- Yali Qu
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology, Department of Medicine, University of California at San Diego, La Jolla, CA, USA
- Department of Family Medicine and Public Health, University of California at San Diego, La Jolla, CA, USA
| | - Kevin J Glaser
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Jun Chen
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory, the San Diego Supercomputer Center, University of California at San Diego, La Jolla, CA, USA
| | - Yesenia Covarrubias
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Mark A Valasek
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Kathryn J Fowler
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Yingzhen N Zhang
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Ethan Sy
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Laboratory, the San Diego Supercomputer Center, University of California at San Diego, La Jolla, CA, USA
| | - Kang Wang
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Adrija Mamidipalli
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA
| | - Jeffrey B Schwimmer
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California at San Diego, La Jolla, CA, USA
- Department of Gastroenterology, Rady Children's Hospital San Diego, San Diego, CA, USA
| | - Bin Song
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Scott B Reeder
- Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin, Madison, WI, USA
| | - Meng Yin
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California at San Diego, La Jolla, CA, 92093-0888, USA.
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Hong CW, Cui JY, Batakis D, Xu Y, Wolfson T, Gamst AC, Schlein AN, Negrete LM, Middleton MS, Hamilton G, Loomba R, Schwimmer JB, Fowler KJ, Sirlin CB. Repeatability and accuracy of various region-of-interest sampling strategies for hepatic MRI proton density fat fraction quantification. Abdom Radiol (NY) 2021; 46:3105-3116. [PMID: 33609166 DOI: 10.1007/s00261-021-02965-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 01/13/2021] [Accepted: 01/16/2021] [Indexed: 12/19/2022]
Abstract
PURPOSE To evaluate repeatability of ROI-sampling strategies for quantifying hepatic proton density fat fraction (PDFF) and to assess error relative to the 9-ROI PDFF. METHODS This was a secondary analysis in subjects with known or suspected nonalcoholic fatty liver disease who underwent MRI for magnitude-based hepatic PDFF quantification. Each subject underwent three exams, each including three acquisitions (nine acquisitions total). An ROI was placed in each hepatic segment on the first acquisition of the first exam and propagated to other acquisitions. PDFF was calculated for each of 511 sampling strategies using every combination of 1, 2, …, all 9 ROIs. Intra- and inter-exam intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs) were estimated for each sampling strategy. Mean absolute error (MAE) was estimated relative to the 9-ROI PDFF. Strategies that sampled both lobes evenly ("balanced") were compared with those that did not ("unbalanced") using two-sample t tests. RESULTS The 29 enrolled subjects (23 male, mean age 24 years) had mean 9-ROI PDFF 11.8% (1.1-36.3%). With more ROIs, ICCs increased, RCs decreased, and MAE decreased. Of the 60 balanced strategies with 4 ROIs, all (100%) achieved inter- and intra-exam ICCs > 0.998, 55 (92%) achieved intra-exam RC < 1%, 50 (83%) achieved inter-exam RC < 1%, and all (100%) achieved MAE < 1%. Balanced sampling strategies had higher ICCs and lower RCs, and lower MAEs than unbalanced strategies in aggregate (p < 0.001 for comparisons between balanced vs. unbalanced strategies). CONCLUSION Repeatability improves and error diminishes with more ROIs. Balanced 4-ROI strategies provide high repeatability and low error.
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Roeder HA, Moore TR, Wolfson MT, Gamst AC, Ramos GA. Treating hyperglycemia in early pregnancy: a randomized controlled trial. Am J Obstet Gynecol MFM 2019; 1:33-41. [PMID: 33319755 DOI: 10.1016/j.ajogmf.2019.03.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 02/28/2019] [Accepted: 03/04/2019] [Indexed: 12/01/2022]
Abstract
BACKGROUND Treating women with gestational diabetes mellitus in the third trimester improves perinatal outcomes. It is unknown whether treating women with mild glucose intolerance earlier in pregnancy would be beneficial in the reduction of maternal and neonatal morbidities. OBJECTIVE In women with hyperglycemia (hemoglobin A1c ≥5.7% and/or fasting glucose ≥92 mg/dL) in early pregnancy, we sought to determine whether immediate treatment improved maternal and neonatal outcomes. STUDY DESIGN This unblinded randomized controlled trial enrolled women with hyperglycemia at ≤15+0 weeks gestation between 2013 and 2015. Participants were assigned randomly to early pregnancy or third-trimester treatment of hyperglycemia that included nutrition counseling, glucose monitoring, and medications as needed. Participants underwent a blinded 2-hour glucose tolerance test at 24-28 weeks gestation. Exclusion criteria were pregestational diabetes mellitus and multiple gestations. The primary outcome was the proportion of infants with neonatal umbilical cord C-peptide >1.77 nmoL (90th percentile). Secondary outcomes were neonatal fat mass, infant World Health Organization weight-for-length percentile at birth, maternal gestational weight gain, and diagnosis of gestational diabetes mellitus on glucose tolerance test. Mann-Whitney-Wilcoxon test and Fisher's exact test were used, as appropriate. RESULTS A total of 202 women were assigned randomly; 45 women dropped out before delivery, which left cases 157 for analysis (82 with early pregnancy and 75 with third-trimester treatment). The trial was terminated early because of low enrollment. Baseline characteristics were similar between groups. There was no difference in C-peptide >90th percentile between groups (1 [1.5%] vs 4 [6.7%]; P=.19) in the early pregnancy and third-trimester groups, respectively). There was also no difference in fat mass (0.37±0.16 vs 0.36±0.17 kg; P=.91), weight-for-length percentile at birth (25% vs 25%; P=.46), or macrosomia (1.5 vs 5.0%; P=.84). Maternal gestational weight gain was 22.6±12.9 lb and 23.9±11.2 lb in the early pregnancy and third-trimester groups, respectively (P=.88). Gestational diabetes mellitus was diagnosed in 19.0% of the cohort and did not differ between groups (14.2% vs 25.8%; P=.17). CONCLUSION In this population of women with hyperglycemia, treatment in early pregnancy did not appear to improve maternal or neonatal outcomes significantly. Given comparable results in both groups, caution should be used in the initiation of an intensive diabetes mellitus treatment protocol for women with the diagnosis of hyperglycemia in early gestation.
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Affiliation(s)
- Hilary A Roeder
- Department of Reproductive Medicine, Division of Perinatology, UC San Diego Health, La Jolla, CA.
| | - Thomas R Moore
- Department of Reproductive Medicine, Division of Perinatology, UC San Diego Health, La Jolla, CA
| | - Ms Tanya Wolfson
- University of California, San Diego, Computational and Applied Statistics Laboratory, San Diego Supercomputing Center, La Jolla, CA
| | - Anthony C Gamst
- University of California, San Diego, Computational and Applied Statistics Laboratory, San Diego Supercomputing Center, La Jolla, CA
| | - Gladys A Ramos
- Department of Reproductive Medicine, Division of Perinatology, UC San Diego Health, La Jolla, CA
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Pooler BD, Wiens CN, McMillan A, Artz NS, Schlein A, Covarrubias Y, Hooker J, Schwimmer JB, Funk LM, Campos GM, Greenberg JA, Jacobsen G, Horgan S, Wolfson T, Gamst AC, Sirlin CB, Reeder SB. Monitoring Fatty Liver Disease with MRI Following Bariatric Surgery: A Prospective, Dual-Center Study. Radiology 2018; 290:682-690. [PMID: 30561273 DOI: 10.1148/radiol.2018181134] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Purpose To longitudinally monitor liver fat before and after bariatric surgery by using quantitative chemical shift-encoded (CSE) MRI and to compare with changes in body mass index (BMI), weight, and waist circumference (WC). Materials and Methods For this prospective study, which was approved by the internal review board, a total of 126 participants with obesity who were undergoing evaluation for bariatric surgery with preoperative very low calorie diet (VLCD) were recruited from June 27, 2010, through May 5, 2015. Written informed consent was obtained from all participants. Participants underwent CSE MRI measuring liver proton density fat fraction (PDFF) before VLCD (2-3 weeks before surgery), after VLCD (1-3 days before surgery), and 1, 3, and 6-10 months following surgery. Linear regression was used to estimate rates of change of PDFF (ΔPDFF) and body anthropometrics. Initial PDFF (PDFF0), initial anthropometrics, and anthropometric rates of change were evaluated as predictors of ΔPDFF. Mixed-effects regression was used to estimate time to normalization of PDFF. Results Fifty participants (mean age, 51.0 years; age range, 27-70 years), including 43 women (mean age, 50.8 years; age range, 27-70 years) and seven men (mean age, 51.7 years; age range, 36-62 years), with mean PDFF0 ± standard deviation of 18.1% ± 8.6 and mean BMI0 of 44.9 kg/m2 ± 6.5 completed the study. By 6-10 months following surgery, mean PDFF decreased to 4.9% ± 3.4 and mean BMI decreased to 34.5 kg/m2 ± 5.4. Mean estimated time to PDFF normalization was 22.5 weeks ± 11.5. PDFF0 was the only strong predictor for both ΔPDFF and time to PDFF normalization. No body anthropometric correlated with either outcome. Conclusion Average liver proton density fat fraction (PDFF) decreased to normal (< 5%) by 6-10 months following surgery, with mean time to normalization of approximately 5 months. Initial PDFF was a strong predictor of both rate of change of PDFF and time to normalization. Body anthropometrics did not predict either outcome. Online supplemental material is available for this article. © RSNA, 2018.
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Affiliation(s)
- B Dustin Pooler
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Curtis N Wiens
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Alan McMillan
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Nathan S Artz
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Alexandra Schlein
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Yesenia Covarrubias
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Jonathan Hooker
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Jeffrey B Schwimmer
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Luke M Funk
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Guilherme M Campos
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Jacob A Greenberg
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Garth Jacobsen
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Santiago Horgan
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Tanya Wolfson
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Anthony C Gamst
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Claude B Sirlin
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
| | - Scott B Reeder
- From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.)
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6
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Fazeli Dehkordy S, Fowler KJ, Mamidipalli A, Wolfson T, Hong CW, Covarrubias Y, Hooker JC, Sy EZ, Schlein AN, Cui JY, Gamst AC, Hamilton G, Reeder SB, Sirlin CB. Hepatic steatosis and reduction in steatosis following bariatric weight loss surgery differs between segments and lobes. Eur Radiol 2018; 29:2474-2480. [PMID: 30547206 DOI: 10.1007/s00330-018-5894-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 10/22/2018] [Accepted: 11/14/2018] [Indexed: 12/13/2022]
Abstract
OBJECTIVES The purpose of this study was to (1) evaluate proton density fat fraction (PDFF) distribution across liver segments at baseline and (2) compare longitudinal segmental PDFF changes across time points in adult patients undergoing a very low-calorie diet (VLCD) and subsequent bariatric weight loss surgery (WLS). METHODS We performed a secondary analysis of data from 118 morbidly obese adult patients enrolled in a VLCD-WLS program. PDFF was estimated using magnitude-based confounder-corrected chemical-shift-encoded (CSE) MRI in each hepatic segment and lobe at baseline (visit 1), after completion of VLCD (visit 2), and at 1, 3, and 6 months (visits 3-5) following WLS. Linear regressions were used to estimate the rate of PDFF change across visits. Lobar and segmental rates of change were compared pairwise. RESULTS Baseline PDFF was significantly higher in the right lobe compared to the left lobe (p < 0.0001). Lobar and segmental PDFF declined by 3.9-4.5% per month between visits 1 and 2 (preoperative period) and by 4.3-4.8% per month between visits 1 and 3 (perioperative period), but no significant pairwise differences were found in slope between segments and lobes. For visits 3-5 (postoperative period), lobar and segmental PDFF reduction was much less overall (0.4-0.8% PDFF per month) and several pairwise differences were significant; in each case, a right-lobe segment had greater decline than a left-lobe segment. CONCLUSIONS Baseline and longitudinal changes in fractional fat content in the 5-month postoperative period following WLS vary across segments, with right-lobe segments having higher PDFF at baseline and more rapid reduction in liver fat content. KEY POINTS • Baseline and longitudinal changes in liver fat following bariatric weight loss surgery vary across liver segments. • Methods that do not provide whole liver fat assessment, such as liver biopsy, may be unreliable in monitoring longitudinal changes in liver fat following weight loss interventions.
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Affiliation(s)
- Soudabeh Fazeli Dehkordy
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA.
| | - Kathryn J Fowler
- Department of Radiology, Washington University, Saint Louis, MO, USA
| | - Adrija Mamidipalli
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory, University of California San Diego, San Diego, CA, USA
| | - Cheng William Hong
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Yesenia Covarrubias
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Ethan Z Sy
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Alexandra N Schlein
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Jennifer Y Cui
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Laboratory, University of California San Diego, San Diego, CA, USA
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Scott B Reeder
- Department of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin Madison, Madison, WI, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
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7
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Planquette B, Sanchez O, Marsh JJ, Chiles PG, Emmerich J, Le Gal G, Meyer G, Wolfson T, Gamst AC, Moore RE, Gugiu GB, Morris TA. Fibrinogen and the prediction of residual obstruction manifested after pulmonary embolism treatment. Eur Respir J 2018; 52:13993003.01467-2018. [PMID: 30337447 DOI: 10.1183/13993003.01467-2018] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2018] [Accepted: 09/24/2018] [Indexed: 11/05/2022]
Abstract
Residual pulmonary vascular obstruction (RPVO) and chronic thromboembolic pulmonary hypertension (CTEPH) are both long-term complications of acute pulmonary embolism, but it is unknown whether RPVO can be predicted by variants of fibrinogen associated with CTEPH.We used the Akaike information criterion to select the best predictive models for RPVO in two prospectively followed cohorts of acute pulmonary embolism patients, using as candidate variables the extent of the initial obstruction, clinical characteristics and fibrinogen-related data. We measured the selected models' goodness of fit by analysis of deviance and compared models using the Chi-squared test.RPVO occurred in 29 (28.4%) out of 102 subjects in the first cohort and 46 (25.3%) out of 182 subjects in the second. The best-fit predictive model derived in the first cohort (p=0.0002) and validated in the second cohort (p=0.0005) implicated fibrinogen Bβ-chain monosialylation in the development of RPVO. When the derivation procedure excluded clinical characteristics, fibrinogen Bβ-chain monosialylation remained a predictor of RPVO in the best-fit predictive model (p=0.00003). Excluding fibrinogen characteristics worsened the predictive model (p=0.03).Fibrinogen Bβ-chain monosialylation, a common structural attribute of fibrin, helped predict RPVO after acute pulmonary embolism. Fibrin structure may contribute to the risk of developing RPVO.
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Affiliation(s)
- Benjamin Planquette
- Université Paris Descartes, Sorbonne Paris Cité, France.,Service de Pneumologie et Soins Intensifs, Hôpital Européen Georges Pompidou, AP-HP, Paris, France.,INSERM UMR-S 1140, Paris, France
| | - Olivier Sanchez
- Université Paris Descartes, Sorbonne Paris Cité, France.,Service de Pneumologie et Soins Intensifs, Hôpital Européen Georges Pompidou, AP-HP, Paris, France.,INSERM UMR-S 1140, Paris, France
| | - James J Marsh
- Dept of Medicine, Division of Pulmonary and Critical Care Medicine, University of California, San Diego, CA, USA
| | - Peter G Chiles
- Dept of Medicine, Division of Pulmonary and Critical Care Medicine, University of California, San Diego, CA, USA
| | - Joseph Emmerich
- Université Paris Descartes, Sorbonne Paris Cité, France.,Médecine Vasculaire - Cardiologie, Centre de Diagnostic et de Thérapeutique, Hôpital Hôtel Dieu, AP-HP, Paris, France
| | - Grégoire Le Gal
- Dept of Medicine, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Guy Meyer
- Université Paris Descartes, Sorbonne Paris Cité, France.,Service de Pneumologie et Soins Intensifs, Hôpital Européen Georges Pompidou, AP-HP, Paris, France.,INSERM CIC-1418, Paris, France.,INSERM UMR-S 970, Paris, France
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA
| | - Roger E Moore
- Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Gabriel B Gugiu
- Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Timothy A Morris
- Dept of Medicine, Division of Pulmonary and Critical Care Medicine, University of California, San Diego, CA, USA
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8
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McMenamin SB, Cummins SE, Zhuang YL, Gamst AC, Ruiz CG, Mayoral A, Zhu SH. Evaluation of the Tobacco-Use Prevention Education (TUPE) program in California. PLoS One 2018; 13:e0206921. [PMID: 30388176 PMCID: PMC6214574 DOI: 10.1371/journal.pone.0206921] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Accepted: 10/21/2018] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND AND AIMS The California Tobacco-Use Prevention Education (TUPE) program promotes the use of evidence-based tobacco-specific prevention and cessation programs for adolescents within the school setting. Through a competitive grant process, schools are funded to provide programs for grades 6-12. This research evaluates the association between TUPE funding and tobacco prevention activities and tobacco use prevalence. METHODS This study utilized two data sources: (1) 2016 California Educator Tobacco Survey (CETS), and (2) 2015-2016 California Student Tobacco Survey (CSTS). The CETS collected data from educators about school prevention efforts, priority of tobacco prevention, and confidence in addressing tobacco issues with students. A total of 3,564 educators from 590 schools participated in CETS. The CSTS collected data from 8th, 10th, and 12th graders in California on their exposure to, attitudes about, and utilization of tobacco products. A total of 47,981 students from 117 schools participated in CSTS. RESULTS This study found that TUPE-funded schools were more likely to provide tobacco-specific health education programs, to place a priority on tobacco-prevention efforts, and to prepare educators to address tobacco use than non-TUPE schools. Educators at both types of schools felt better prepared to talk with students about traditional tobacco products than about emerging products such as e-cigarettes. Overall, students at TUPE-funded schools were more likely to report receiving anti-tobacco messages from school-based programs than those at non-TUPE schools. The former were also less likely to use tobacco products, even when the analysis controlled for demographics and school-level characteristics (OR = 0.82 [95% CI = 0.70-0.96]). CONCLUSIONS TUPE funding was associated with an increase in schools' tobacco-specific prevention activities and these enhanced activities were associated with lower tobacco use among students. This study also found that education and prevention efforts regarding emerging tobacco products need to be strengthened across all schools.
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Affiliation(s)
- Sara B. McMenamin
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, California, United States of America
| | - Sharon E. Cummins
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, California, United States of America
- Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America
| | - Yue-Lin Zhuang
- Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America
| | - Anthony C. Gamst
- Department of Mathematics, University of California San Diego, La Jolla, California, United States of America
| | - Carlos G. Ruiz
- Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America
| | - Antonio Mayoral
- Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America
| | - Shu-Hong Zhu
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, California, United States of America
- Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America
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9
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Bashir MR, Wolfson T, Gamst AC, Fowler KJ, Ohliger M, Shah SN, Alazraki A, Trout AT, Behling C, Allende DS, Loomba R, Sanyal A, Schwimmer J, Lavine JE, Shen W, Tonascia J, Van Natta ML, Mamidipalli A, Hooker J, Kowdley KV, Middleton MS, Sirlin CB. Hepatic R2* is more strongly associated with proton density fat fraction than histologic liver iron scores in patients with nonalcoholic fatty liver disease. J Magn Reson Imaging 2018; 49:1456-1466. [PMID: 30318834 DOI: 10.1002/jmri.26312] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 08/09/2018] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The liver R2* value is widely used as a measure of liver iron but may be confounded by the presence of hepatic steatosis and other covariates. PURPOSE To identify the most influential covariates for liver R2* values in patients with nonalcoholic fatty liver disease (NAFLD). STUDY TYPE Retrospective analysis of prospectively acquired data. POPULATION Baseline data from 204 subjects enrolled in NAFLD/NASH (nonalcoholic steatohepatitis) treatment trials. FIELD STRENGTH 1.5T and 3T; chemical-shift encoded multiecho gradient echo. ASSESSMENT Correlation between liver proton density fat fraction and R2*; assessment for demographic, metabolic, laboratory, MRI-derived, and histological covariates of liver R2*. STATISTICAL TESTS Pearson's and Spearman's correlations; univariate analysis; gradient boosting machines (GBM) multivariable machine-learning method. RESULTS Hepatic proton density fat fraction (PDFF) was the most strongly correlated covariate for R2* at both 1.5T (r = 0.652, P < 0.0001) and at 3T (r = 0.586, P < 0.0001). In the GBM analysis, hepatic PDFF was the most influential covariate for hepatic R2*, with relative influences (RIs) of 61.3% at 1.5T and 47.5% at 3T; less influential covariates had RIs of up to 11.5% at 1.5T and 16.7% at 3T. Nonhepatocellular iron was weakly associated with R2* at 3T only (RI 6.7%), and hepatocellular iron was not associated with R2* at either field strength. DATA CONCLUSION Hepatic PDFF is the most influential covariate for R2* at both 1.5T and 3T; nonhepatocellular iron deposition is weakly associated with liver R2* at 3T only. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1456-1466.
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Affiliation(s)
- Mustafa R Bashir
- Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA.,Center for Advanced Magnetic Resonance Development (CAMRD), Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA.,Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, North Carolina
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputing Center (SDSC), University of California-San Diego, San Diego, California, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputing Center (SDSC), University of California-San Diego, San Diego, California, USA
| | - Kathryn J Fowler
- Department of Radiology, Washington University, St. Louis, Missouri, USA
| | - Michael Ohliger
- Departments of Radiology and Biomedical Engineering, University of California-San Francisco, San Francisco, California, USA
| | - Shetal N Shah
- Section of Abdominal Imaging and Nuclear Medicine Department, Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Adina Alazraki
- Departments of Radiology and Pediatrics, Emory University School of Medicine/Children's Healthcare of Atlanta, Atlanta, Georgia, USA
| | - Andrew T Trout
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Cynthia Behling
- Department of Pathology, University of California-San Diego, La Jolla, California, USA
| | | | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology, Department of Medicine, University of California-San Diego, La Jolla, California, USA
| | - Arun Sanyal
- Division of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Jeffrey Schwimmer
- Department of Pediatrics, University of California-San Diego, San Diego, California, USA
| | - Joel E Lavine
- Department of Pediatrics, Columbia College of Physicians and Surgeons, New York, New York, USA
| | - Wei Shen
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics and the Institute of Human Nutrition, Columbia University Medical Center, New York, New York, USA
| | - James Tonascia
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Mark L Van Natta
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Adrija Mamidipalli
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Jonathan Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Kris V Kowdley
- Liver Care Network and Organ Care Research, Swedish Medical Center, Seattle, Washington, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
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- Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
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10
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Fazeli Dehkordy S, Fowler KJ, Wolfson T, Igarashi S, Lamas Constantino CP, Hooker JC, Hong CW, Mamidipalli A, Gamst AC, Hemming A, Sirlin CB. Technical report: gadoxetate-disodium-enhanced 2D R2* mapping: a novel approach for assessing bile ducts in living donors. Abdom Radiol (NY) 2018; 43:1656-1660. [PMID: 29086007 DOI: 10.1007/s00261-017-1365-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
PURPOSE Gadoxetate-disodium (Gd-EOB-DTPA)-enhanced 3D T1- weighted (T1w) MR cholangiography (MRC) is an efficient method to evaluate biliary anatomy due to T1 shortening of excreted contrast in the bile. A method that exploits both T1 shortening and T2* effects may produce even greater bile duct conspicuity. The aim of our study is to determine feasibility and compare the diagnostic performance of two-dimensional (2D) T1w multi-echo (ME) spoiled gradient-recalled-echo (SPGR) derived R2* maps against T1w MRC for bile duct visualization in living liver donor candidates. MATERIALS AND METHODS Ten potential living liver donor candidates underwent pretransplant 3T MRI and were included in our study. Following injection of Gd-EOBDTPA and a 20-min delay, 3D T1w MRC and 2D T1w ME SPGR images were acquired. 2D R2* maps were generated inline by the scanner assuming exponential decay. The 3D T1w MRC and 2D R2* maps were retrospectively and independently reviewed in two separate sessions by three radiologists. Visualization of eight bile duct segments was scored using a 4-point ordinal scale. The scores were compared using mixed effects regression model. RESULTS Imaging was tolerated by all donors and R2* maps were successfully generated in all cases. Visualization scores of 2D R2* maps were significantly higher than 3D T1w MRC for right anterior (p = 0.003) and posterior (p = 0.0001), segment 2 (p < 0.0001), segment 3 (p = 0.0001), and segment 4 (p < 0.0001) ducts. CONCLUSIONS Gd-EOB-DTPA-enhanced 2D R2* mapping is a feasible method for evaluating the bile ducts in living donors and may be a valuable addition to the living liver donor MR protocol for delineating intrahepatic biliary anatomy.
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Affiliation(s)
- Soudabeh Fazeli Dehkordy
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA.
| | - Kathryn J Fowler
- Department of Radiology, Washington University, Saint Louis, MO, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA
| | - Saya Igarashi
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Carolina P Lamas Constantino
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
- Dimagem Diagnóstico por Imagem, Rio de Janeiro, Brazil
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Cheng W Hong
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Adrija Mamidipalli
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Laboratory, San Diego Supercomputer Center, University of California San Diego, San Diego, CA, USA
| | - Alan Hemming
- Department of Surgery, University of California San Diego, San Diego, CA, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA
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11
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Schwimmer JB, Behling C, Angeles JE, Paiz M, Durelle J, Africa J, Newton KP, Brunt EM, Lavine JE, Abrams SH, Masand P, Krishnamurthy R, Wong K, Ehman RL, Yin M, Glaser KJ, Dzyubak B, Wolfson T, Gamst AC, Hooker J, Haufe W, Schlein A, Hamilton G, Middleton MS, Sirlin CB. Magnetic resonance elastography measured shear stiffness as a biomarker of fibrosis in pediatric nonalcoholic fatty liver disease. Hepatology 2017; 66:1474-1485. [PMID: 28493388 PMCID: PMC5650504 DOI: 10.1002/hep.29241] [Citation(s) in RCA: 89] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Revised: 03/23/2017] [Accepted: 04/24/2017] [Indexed: 12/14/2022]
Abstract
UNLABELLED Magnetic resonance elastography (MRE) is a promising technique for noninvasive assessment of fibrosis, a major determinant of outcome in nonalcoholic fatty liver disease (NAFLD). However, data in children are limited. The purpose of this study was to determine the accuracy of MRE for the detection of fibrosis and advanced fibrosis in children with NAFLD and to assess agreement between manual and novel automated reading methods. We performed a prospective, multicenter study of two-dimensional (2D) MRE in children with NAFLD. MR elastograms were analyzed manually at two reading centers, and using a new automated technique. Analysis using each approach was done independently. Correlations were determined between MRE analysis methods and fibrosis stage. Thresholds for classifying the presence of fibrosis and of advanced fibrosis were computed and cross-validated. In 90 children with a mean age of 13.1 ± 2.4 years, median hepatic stiffness was 2.35 kPa. Stiffness values derived by each reading center were strongly correlated with each other (r = 0.83). All three analyses were significantly correlated with fibrosis stage (center 1, ρ = 0.53; center 2, ρ = 0.55; and automated analysis, ρ = 0.52; P < 0.001). Overall cross-validated accuracy for detecting any fibrosis was 72.2% for all methods (95% confidence interval [CI], 61.8%-81.1%). Overall cross-validated accuracy for assessing advanced fibrosis was 88.9% (95% CI, 80.5%-94.5%) for center 1, 90.0% (95% CI, 81.9%-95.3%) for center 2, and 86.7% (95% CI, 77.9%-92.9%) for automated analysis. CONCLUSION 2D MRE can estimate hepatic stiffness in children with NAFLD. Further refinement and validation of automated analysis techniques will be an important step in standardizing MRE. How to best integrate MRE into clinical protocols for the assessment of NAFLD in children will require prospective evaluation. (Hepatology 2017;66:1474-1485).
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Affiliation(s)
- Jeffrey B. Schwimmer
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California,Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California,Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Cynthia Behling
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Jorge Eduardo Angeles
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Melissa Paiz
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Janis Durelle
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Jonathan Africa
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California
| | - Kimberly P. Newton
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, California,Department of Gastroenterology, Rady Children’s Hospital San Diego, San Diego, California
| | - Elizabeth M. Brunt
- Department of Pathology and Immunology, Washington University, St. Louis, Missouri
| | | | - Stephanie H. Abrams
- Columbia University, New York, NY,Baylor College of Medicine, Houston, Texas,Houston Methodist Hospital, Houston, Texas
| | | | | | - Kelvin Wong
- Miller Children’s & Women’s Hospital Long Beach, California
| | | | - Meng Yin
- Mayo Clinic, Rochester, Minnesota
| | | | | | - Tanya Wolfson
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center, University of California, San Diego, California
| | - Anthony C. Gamst
- Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputer Center, University of California, San Diego, California
| | - Jonathan Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - William Haufe
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Alexandra Schlein
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Michael S. Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego School of Medicine, San Diego, California
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Fowler KJ, Tang A, Santillan C, Bhargavan-Chatfield M, Heiken J, Jha RC, Weinreb J, Hussain H, Mitchell DG, Bashir MR, Costa EAC, Cunha GM, Coombs L, Wolfson T, Gamst AC, Brancatelli G, Yeh B, Sirlin CB. Interreader Reliability of LI-RADS Version 2014 Algorithm and Imaging Features for Diagnosis of Hepatocellular Carcinoma: A Large International Multireader Study. Radiology 2017; 286:173-185. [PMID: 29091751 DOI: 10.1148/radiol.2017170376] [Citation(s) in RCA: 74] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Purpose To determine in a large multicenter multireader setting the interreader reliability of Liver Imaging Reporting and Data System (LI-RADS) version 2014 categories, the major imaging features seen with computed tomography (CT) and magnetic resonance (MR) imaging, and the potential effect of reader demographics on agreement with a preselected nonconsecutive image set. Materials and Methods Institutional review board approval was obtained, and patient consent was waived for this retrospective study. Ten image sets, comprising 38-40 unique studies (equal number of CT and MR imaging studies, uniformly distributed LI-RADS categories), were randomly allocated to readers. Images were acquired in unenhanced and standard contrast material-enhanced phases, with observation diameter and growth data provided. Readers completed a demographic survey, assigned LI-RADS version 2014 categories, and assessed major features. Intraclass correlation coefficient (ICC) assessed with mixed-model regression analyses was the metric for interreader reliability of assigning categories and major features. Results A total of 113 readers evaluated 380 image sets. ICC of final LI-RADS category assignment was 0.67 (95% confidence interval [CI]: 0.61, 0.71) for CT and 0.73 (95% CI: 0.68, 0.77) for MR imaging. ICC was 0.87 (95% CI: 0.84, 0.90) for arterial phase hyperenhancement, 0.85 (95% CI: 0.81, 0.88) for washout appearance, and 0.84 (95% CI: 0.80, 0.87) for capsule appearance. ICC was not significantly affected by liver expertise, LI-RADS familiarity, or years of postresidency practice (ICC range, 0.69-0.70; ICC difference, 0.003-0.01 [95% CI: -0.003 to -0.01, 0.004-0.02]. ICC was borderline higher for private practice readers than for academic readers (ICC difference, 0.009; 95% CI: 0.000, 0.021). Conclusion ICC is good for final LI-RADS categorization and high for major feature characterization, with minimal reader demographic effect. Of note, our results using selected image sets from nonconsecutive examinations are not necessarily comparable with those of prior studies that used consecutive examination series. © RSNA, 2017.
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Affiliation(s)
- Kathryn J Fowler
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - An Tang
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Cynthia Santillan
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Mythreyi Bhargavan-Chatfield
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Jay Heiken
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Reena C Jha
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Jeffrey Weinreb
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Hero Hussain
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Donald G Mitchell
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Mustafa R Bashir
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Eduardo A C Costa
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Guilherme M Cunha
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Laura Coombs
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Tanya Wolfson
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Anthony C Gamst
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Giuseppe Brancatelli
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Benjamin Yeh
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
| | - Claude B Sirlin
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.J.F., J.H.); Department of Radiology, Centre Hospitalier de l'Universite de Montreal, Montreal, Canada (A.T.); Department of Radiology, Liver Imaging Group (C.S., C.B.S.), and Computational and Applied Statistics Laboratory, San Diego Supercomputer Center (T.W., A.C.G.), University of California San Diego, San Diego, Calif; American College of Radiology, Reston, Va (M.B., L.C.); Department of Radiology, MedStar Georgetown University Hospital, Washington, DC (R.C.J.); Department of Radiology, Yale Medical School, New Haven, Conn (J.W.); Department of Radiology, University of Michigan, Ann Arbor, Mich (H.H.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (D.G.M.); Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC (M.R.B.); Cedrul, CT and MRI, Joao Pessoa, Brazil (E.A.C.C.); Clinica de Diagnostico por Imagem-CDPI-DASA, Rio de Janeiro, Brazil (G.M.C.); Division of Radiological Science, Di.Bi.Med., University of Palermo, Palermo, Italy (G.B.); and Department of Radiology, University of California San Francisco, San Francisco, Calif (B.Y.)
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Zhu SH, Anderson CM, Zhuang YL, Gamst AC, Kohatsu ND. Smoking prevalence in Medicaid has been declining at a negligible rate. PLoS One 2017; 12:e0178279. [PMID: 28542637 PMCID: PMC5479677 DOI: 10.1371/journal.pone.0178279] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2016] [Accepted: 05/10/2017] [Indexed: 12/03/2022] Open
Abstract
Background In recent decades the overall smoking prevalence in the US has fallen steadily. This study examines whether the same trend is seen in the Medicaid population. Methods and findings National Health Interview Survey (NHIS) data from 17 consecutive annual surveys from 1997 to 2013 (combined N = 514,043) were used to compare smoking trends for 4 insurance groups: Medicaid, the Uninsured, Private Insurance, and Other Coverage. Rates of chronic disease and psychological distress were also compared. Results Adjusted smoking prevalence showed no detectable decline in the Medicaid population (from 33.8% in 1997 to 31.8% in 2013, trend test P = 0.13), while prevalence in the other insurance groups showed significant declines (38.6%-34.7% for the Uninsured, 21.3%-15.8% for Private Insurance, and 22.6%-16.8% for Other Coverage; all P’s<0.005). Among individuals who have ever smoked, Medicaid recipients were less likely to have quit (38.8%) than those in Private Insurance (62.3%) or Other Coverage (69.8%; both P’s<0.001). Smokers in Medicaid were more likely than those in Private Insurance and the Uninsured to have chronic disease (55.0% vs 37.3% and 32.4%, respectively; both P’s<0.01). Smokers in Medicaid were also more likely to experience severe psychological distress (16.2% for Medicaid vs 3.2% for Private Insurance and 7.6% for the Uninsured; both P’s<0.001). Conclusions The high and relatively unchanging smoking prevalence in the Medicaid population, low quit ratio, and high rates of chronic disease and severe psychological distress highlight the need to focus on this population. A targeted and sustained campaign to help Medicaid recipients quit smoking is urgently needed.
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Affiliation(s)
- Shu-Hong Zhu
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, California, United States of America
- Moores Cancer Center, University of California, San Diego, La Jolla, California, United States of America
- * E-mail:
| | - Christopher M. Anderson
- Moores Cancer Center, University of California, San Diego, La Jolla, California, United States of America
| | - Yue-Lin Zhuang
- Moores Cancer Center, University of California, San Diego, La Jolla, California, United States of America
| | - Anthony C. Gamst
- Moores Cancer Center, University of California, San Diego, La Jolla, California, United States of America
- Department of Mathematics, University of California, San Diego, La Jolla, California, United States of America
| | - Neal D. Kohatsu
- Department of Health Care Services, Sacramento, California, United States of America
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Sun W, Dacek ST, Ong SP, Hautier G, Jain A, Richards WD, Gamst AC, Persson KA, Ceder G. The thermodynamic scale of inorganic crystalline metastability. Sci Adv 2016; 2:e1600225. [PMID: 28138514 PMCID: PMC5262468 DOI: 10.1126/sciadv.1600225] [Citation(s) in RCA: 229] [Impact Index Per Article: 28.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2015] [Accepted: 10/20/2016] [Indexed: 05/03/2023]
Abstract
The space of metastable materials offers promising new design opportunities for next-generation technological materials, such as complex oxides, semiconductors, pharmaceuticals, steels, and beyond. Although metastable phases are ubiquitous in both nature and technology, only a heuristic understanding of their underlying thermodynamics exists. We report a large-scale data-mining study of the Materials Project, a high-throughput database of density functional theory-calculated energetics of Inorganic Crystal Structure Database structures, to explicitly quantify the thermodynamic scale of metastability for 29,902 observed inorganic crystalline phases. We reveal the influence of chemistry and composition on the accessible thermodynamic range of crystalline metastability for polymorphic and phase-separating compounds, yielding new physical insights that can guide the design of novel metastable materials. We further assert that not all low-energy metastable compounds can necessarily be synthesized, and propose a principle of 'remnant metastability'-that observable metastable crystalline phases are generally remnants of thermodynamic conditions where they were once the lowest free-energy phase.
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Affiliation(s)
- Wenhao Sun
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Stephen T. Dacek
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Shyue Ping Ong
- Department of NanoEngineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Geoffroy Hautier
- Institute of Condensed Matter and Nanosciences, Université catholique de Louvain, Louvain-la-Neuve 1348, Belgium
| | - Anubhav Jain
- Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - William D. Richards
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Anthony C. Gamst
- Computational and Applied Statistics Laboratory, Department of Mathematics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Kristin A. Persson
- Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- Department of Materials Science and Engineering, University of California, Berkeley, CA 94720, USA
| | - Gerbrand Ceder
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- Department of Materials Science and Engineering, University of California, Berkeley, CA 94720, USA
- Corresponding author.
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Cummins SE, Gamst AC, Brandstein K, Seymann GB, Klonoff-Cohen H, Kirby CA, Tong EK, Chaplin E, Tedeschi GJ, Zhu SH. Helping Hospitalized Smokers: A Factorial RCT of Nicotine Patches and Counseling. Am J Prev Med 2016; 51:578-86. [PMID: 27647058 PMCID: PMC5031241 DOI: 10.1016/j.amepre.2016.06.021] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2016] [Revised: 06/17/2016] [Accepted: 06/29/2016] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Most smokers abstain from smoking during hospitalization but relapse upon discharge. This study tests the effectiveness of two proven treatments (i.e., nicotine patches and telephone counseling) in helping these patients stay quit after discharge from the hospital, and assesses a model of hospital-quitline partnership. STUDY DESIGN This study had a 2×2 factorial design in which participants were stratified by recruitment site and smoking rate and randomly assigned to usual care, nicotine patches only, counseling only, or patches plus counseling. They were evaluated at 2 and 6 months post-randomization. SETTING/PARTICIPANTS A total of 1,270 hospitalized adult smokers were recruited from August 2011 to November 2013 from five hospitals within three healthcare systems. INTERVENTION Participants in the patch condition were provided 8 weeks of nicotine patches at discharge (or were mailed them post-discharge). Quitline staff started proactively calling participants in the counseling condition 3 days post-discharge to provide standard quitline counseling. MAIN OUTCOME MEASURES The primary outcome measure was self-reported 30-day abstinence at 6 months using an intention-to-treat analysis. Data were analyzed from September 2015 to May 2016. RESULTS The 30-day abstinence rate at 6 months was 22.8% for the nicotine patch condition and 18.3% for the no-patch condition (p=0.051). Nearly all participants (99%) in the patch condition were provided nicotine patches, although 36% were sent post-discharge. The abstinence rates were 20.0% and 21.1% for counseling and no counseling conditions, respectively (p=0.651). Fewer than half of the participants in the counseling condition (47%) received counseling (mean follow-up sessions, 3.6). CONCLUSIONS Provision of nicotine patches proved feasible, although their effectiveness in helping discharged patients stay quit was not significant. Telephone counseling was not effective, in large part because of low rates of engagement. Future interventions will need to be more immediate to be effective. TRIAL REGISTRATION This study is registered at www.clinicaltrials.gov NCT01289275.
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Affiliation(s)
- Sharon E Cummins
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, California; Moores Cancer Center at University of California, San Diego, La Jolla, California
| | - Anthony C Gamst
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, California; Moores Cancer Center at University of California, San Diego, La Jolla, California
| | | | - Gregory B Seymann
- Department of Medicine, University of California, San Diego Health Sciences, La Jolla, California
| | - Hillary Klonoff-Cohen
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Champaign, Illinois
| | - Carrie A Kirby
- Moores Cancer Center at University of California, San Diego, La Jolla, California
| | - Elisa K Tong
- Department of Internal Medicine, University of California, Davis, Sacramento, California
| | - Edward Chaplin
- Department of Quality Services and Improvement, Scripps Mercy Hospital, San Diego, California
| | - Gary J Tedeschi
- Moores Cancer Center at University of California, San Diego, La Jolla, California
| | - Shu-Hong Zhu
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, California; Moores Cancer Center at University of California, San Diego, La Jolla, California.
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Hamilton G, Schlein AN, Middleton MS, Hooker CA, Wolfson T, Gamst AC, Loomba R, Sirlin CB. In vivo triglyceride composition of abdominal adipose tissue measured by 1 H MRS at 3T. J Magn Reson Imaging 2016; 45:1455-1463. [PMID: 27571403 DOI: 10.1002/jmri.25453] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 08/16/2016] [Indexed: 11/08/2022] Open
Abstract
PURPOSE To investigate the regional variability of adipose tissue triglyceride composition in vivo using 1 H MRS, examining potential confounders and corrections for artifacts, to allow for adipose tissue spectrum estimation. MATERIALS AND METHODS 1 H magnetic resonance (MR) stimulated echo acquisition mode (STEAM) spectra were acquired in vivo at 3T from 340 adult patients (mean age 48.9 years, range 21-79 years; 172 males, 168 females; mean body mass index [BMI] 34.0, range 22-49 kg/m2 ) with known or suspected nonalcoholic fatty liver disease (NAFLD) in deep (dSCAT), surface (sSCAT) subcutaneous adipose tissue, and visceral adipose tissue (VAT). Triglyceride composition was characterized by the number of double bonds (ndb) and number of methylene-interrupted double bonds (nmidb). A subset of patients (dSCAT n = 80, sSCAT n = 55, VAT n = 194) had the acquisition repeated three times to examine the repeatability of ndb and nmidb estimation. RESULTS Mean ndb and nmidb showed significant (P < 0.0001) differences between depots except for dSCAT and sSCAT nmidb (dSCAT ndb 2.797, nmidb 0.745; sSCAT ndb 2.826, nmidb 0.737; VAT ndb 2.723, nmidb 0.687). All ndb and nmidb estimates were highly repeatable (VAT ndb ICC = 0.888, nmidb ICC = 0.853; sSCAT: ndb ICC = 0.974, nmidb ICC = 0.964; dSCAT: ndb ICC = 0.959, nmidb ICC = 0.948). CONCLUSION Adipose tissue composition can be estimated repeatably using 1 H MRS and different fat depots have different triglyceride compositions. LEVEL OF EVIDENCE 2 J. MAGN. RESON. IMAGING 2017;45:1455-1463.
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Affiliation(s)
- Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Alexandra N Schlein
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Catherine A Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Lab, San Diego Supercomputing Center, San Diego, California, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Lab, San Diego Supercomputing Center, San Diego, California, USA
| | - Rohit Loomba
- Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California, USA.,NAFLD Translational Research Unit, Division of Gastroenterology, Department of Medicine, University of California, San Diego, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA
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17
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Tanabe M, Kanki A, Wolfson T, Costa EAC, Mamidipalli A, Ferreira MPFD, Santillan C, Middleton MS, Gamst AC, Kono Y, Kuo A, Sirlin CB. Imaging Outcomes of Liver Imaging Reporting and Data System Version 2014 Category 2, 3, and 4 Observations Detected at CT and MR Imaging. Radiology 2016; 281:129-39. [PMID: 27115054 DOI: 10.1148/radiol.2016152173] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Purpose To determine the proportion of untreated Liver Imaging Reporting and Data System (LI-RADS) version 2014 category 2, 3, and 4 observations that progress, remain stable, or decrease in category and to compare the cumulative incidence of progression in category. Materials and Methods In this retrospective, longitudinal, single-center, HIPAA-compliant, institutional review board-approved study, 157 patients (86 men and 71 women; mean age ± standard deviation, 59.0 years ± 9.7) underwent two or more multiphasic computed tomographic (CT) or magnetic resonance (MR) imaging examinations for hepatocellular carcinoma surveillance, with the first examination in 2011 or 2012. One radiologist reviewed baseline and follow-up CT and MR images (mean follow-up, 614 days). LI-RADS categories issued in the clinical reports by using version 1.0 or version 2013 were converted to version 2014 retrospectively; category modifications were verified with another radiologist. For index category LR-2, LR-3, and LR-4 observations, the proportions that progressed, remained stable, or decreased in category were calculated. Cumulative incidence curves for progression were compared according to baseline LI-RADS category (by using log-rank tests). Results All 63 index LR-2 observations remained stable or decreased in category. Among 166 index LR-3 observations, seven (4%) progressed to LR-5, and eight (5%) progressed to LR-4. Among 52 index LR-4 observations, 20 (38%) progressed to a malignant category. The cumulative incidence of progression to a malignant category was higher for index LR-4 observations than for index LR-3 or LR-2 observations (each P < .001) but was not different between LR-3 and LR-2 observations (P = .155). The cumulative incidence of progression to at least category LR-4 was trend-level higher for index LR-3 observations than for LR-2 observations (P = .0502). Conclusion Observations classified according to LI-RADS version 2014 categories are associated with different imaging outcomes. (©) RSNA, 2016 Online supplemental material is available for this article.
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Affiliation(s)
- Masahiro Tanabe
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Akihiko Kanki
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Tanya Wolfson
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Eduardo A C Costa
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Adrija Mamidipalli
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Marilia P F D Ferreira
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Cynthia Santillan
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Michael S Middleton
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Anthony C Gamst
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Yuko Kono
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Alexander Kuo
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
| | - Claude B Sirlin
- From the Liver Imaging Group, Department of Radiology (M.T., A.K., E.A.C.C., A.M., M.P.F.D.F., C.S., M.S.M., C.B.S.) and Division of Hepatology, Department of Medicine (Y.K., A.K.), University of California, San Diego, 408 Dickinson St, San Diego, CA 92103; and Computational and Applied Statistics Laboratory (CASL), SDSC-University of California, San Diego, La Jolla, Calif (T.W., A.C.G.)
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Zhu SH, Cummins SE, Gamst AC, Wong S, Ikeda T. Quitting smoking before and after varenicline: a population study based on two representative samples of US smokers. Tob Control 2015; 25:464-9. [PMID: 26283713 DOI: 10.1136/tobaccocontrol-2015-052332] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2015] [Accepted: 07/07/2015] [Indexed: 11/04/2022]
Abstract
BACKGROUND Varenicline is known to have greater efficacy than other pharmacotherapy for treating nicotine dependence and has gained popularity since its introduction in 2006. This study examines if adding varenicline to existing pharmacotherapies increased the population cessation rate. METHODS Data are from two cross-sectional US Current Population Surveys-Tobacco Use Supplements (2003 and 2010-2011). Smokers and recent quitters 18 or older (N=34 869 in 2003, N=27 751 in 2010-2011) were asked if they had used varenicline, bupropion or nicotine replacement therapies (NRT) in their most recent quit attempt. The annual cessation rate, as well as the per cent of smokers who had quit for ≥3 months, was compared between surveys. RESULTS Varenicline use increased from 0% in 2003 to 10.9% in 2010-2011, while use of bupropion decreased from 9.1% to 3.5%, and NRT from 24.5% to 22.4%. Use of any pharmacotherapy increased by 2.4 percentage points. Varenicline users stayed on cessation aids longer and were less likely to relapse than users of other pharmacotherapies in the first 3 months of a quit attempt, after which the difference was no longer significant. The change in annual cessation rate was negligible, from 4.5% in 2003 to 4.7% in 2010-2011 (p=0.36). CONCLUSIONS Addition of varenicline to the list of approved cessation aids has mainly led to displacement of other therapies. As a result, there was no meaningful change in population cessation rate despite a remarkable increase in varenicline use. The population impact of a new therapy is a function of more than efficacy or reach of the therapy.
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Affiliation(s)
- Shu-Hong Zhu
- Moores Cancer Center, University of California, San Diego, California, USA
| | - Sharon E Cummins
- Moores Cancer Center, University of California, San Diego, California, USA
| | - Anthony C Gamst
- Moores Cancer Center, University of California, San Diego, California, USA
| | - Shiushing Wong
- Moores Cancer Center, University of California, San Diego, California, USA
| | - Tyson Ikeda
- Moores Cancer Center, University of California, San Diego, California, USA
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Zhuang YL, Gamst AC, Cummins SE, Wolfson T, Zhu SH. Comparison of smoking cessation between education groups: findings from 2 US National Surveys over 2 decades. Am J Public Health 2015; 105:373-9. [PMID: 25521868 DOI: 10.2105/ajph.2014.302222] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
OBJECTIVES We examined smoking cessation rate by education and determined how much of the difference can be attributed to the rate of quit attempts and how much to the success of these attempts. METHODS We analyzed data from the National Health Interview Survey (NHIS, 1991-2010) and the Tobacco Use Supplement to the Current Population Survey (TUS-CPS, 1992-2011). Smokers (≥ 25 years) were divided into lower- and higher-education groups (≤ 12 years and >12 years). RESULTS A significant difference in cessation rate between the lower- and the higher-education groups persisted over the last 2 decades. On average, the annual cessation rate for the former was about two thirds that of the latter (3.5% vs 5.2%; P<.001, for both NHIS and TUS-CPS). About half the difference in cessation rate can be attributed to the difference in quit attempt rate and half to the difference in success rate. CONCLUSIONS Smokers in the lower-education group have consistently lagged behind their higher-education counterparts in quitting. In addition to the usual concern about improving their success in quitting, tobacco control programs need to find ways to increase quit attempts in this group.
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Affiliation(s)
- Yue-Lin Zhuang
- Yue-Lin Zhuang and Tanya Wolfson are with the Cancer Center, University of California, San Diego, La Jolla. Shu-Hong Zhu, Anthony C. Gamst, and Sharon E. Cummins are with the Department of Family and Preventive Medicine, University of California, San Diego
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20
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Zand KA, Shah A, Heba E, Wolfson T, Hamilton G, Lam J, Chen J, Hooker JC, Gamst AC, Middleton MS, Schwimmer JB, Sirlin CB. Accuracy of multiecho magnitude-based MRI (M-MRI) for estimation of hepatic proton density fat fraction (PDFF) in children. J Magn Reson Imaging 2015; 42:1223-32. [PMID: 25847512 DOI: 10.1002/jmri.24888] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Accepted: 03/02/2015] [Indexed: 01/28/2023] Open
Abstract
PURPOSE To assess accuracy of magnitude-based magnetic resonance imaging (M-MRI) in children to estimate hepatic proton density fat fraction (PDFF) using two to six echoes, with magnetic resonance spectroscopy (MRS) -measured PDFF as a reference standard. METHODS This was an IRB-approved, HIPAA-compliant, single-center, cross-sectional, retrospective analysis of data collected prospectively between 2008 and 2013 in children with known or suspected nonalcoholic fatty liver disease (NAFLD). Two hundred eighty-six children (8-20 [mean 14.2 ± 2.5] years; 182 boys) underwent same-day MRS and M-MRI. Unenhanced two-dimensional axial spoiled gradient-recalled-echo images at six echo times were obtained at 3T after a single low-flip-angle (10°) excitation with ≥ 120-ms recovery time. Hepatic PDFF was estimated using the first two, three, four, five, and all six echoes. For each number of echoes, accuracy of M-MRI to estimate PDFF was assessed by linear regression with MRS-PDFF as reference standard. Accuracy metrics were regression intercept, slope, average bias, and R(2) . RESULTS MRS-PDFF ranged from 0.2-40.4% (mean 13.1 ± 9.8%). Using three to six echoes, regression intercept, slope, and average bias were 0.46-0.96%, 0.99-1.01, and 0.57-0.89%, respectively. Using two echoes, these values were 2.98%, 0.97, and 2.72%, respectively. R(2) ranged 0.98-0.99 for all methods. CONCLUSION Using three to six echoes, M-MRI has high accuracy for hepatic PDFF estimation in children.
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Affiliation(s)
- Kevin A Zand
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Amol Shah
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Elhamy Heba
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory, Division of Biostatistics and Informatics, University of California, San Diego, California, USA
| | - Gavin Hamilton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Jessica Lam
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Joshua Chen
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Jonathan C Hooker
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Laboratory, Division of Biostatistics and Informatics, University of California, San Diego, California, USA
| | - Michael S Middleton
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
| | - Jeffrey B Schwimmer
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA.,Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California, San Diego, California, USA.,Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA
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Heaton RK, Franklin DR, Deutsch R, Letendre S, Ellis RJ, Casaletto K, Marquine MJ, Woods SP, Vaida F, Atkinson JH, Marcotte TD, McCutchan JA, Collier AC, Marra CM, Clifford DB, Gelman BB, Sacktor N, Morgello S, Simpson DM, Abramson I, Gamst AC, Fennema-Notestine C, Smith DM, Grant I. Neurocognitive change in the era of HIV combination antiretroviral therapy: the longitudinal CHARTER study. Clin Infect Dis 2015; 60:473-80. [PMID: 25362201 PMCID: PMC4303775 DOI: 10.1093/cid/ciu862] [Citation(s) in RCA: 275] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2014] [Accepted: 08/19/2014] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND Human immunodeficiency virus (HIV)-associated neurocognitive disorders (HAND) can show variable clinical trajectories. Previous longitudinal studies of HAND typically have been brief, did not use adequate normative standards, or were conducted in the context of a clinical trial, thereby limiting our understanding of incident neurocognitive (NC) decline and recovery. METHODS We investigated the incidence and predictors of NC change over 16-72 (mean, 35) months in 436 HIV-infected participants in the CNS HIV Anti-Retroviral Therapy Effects Research cohort. Comprehensive laboratory, neuromedical, and NC assessments were obtained every 6 months. Published, regression-based norms for NC change were used to generate overall change status (decline vs stable vs improved) at each study visit. Survival analysis was used to examine the predictors of time to NC change. RESULTS Ninety-nine participants (22.7%) declined, 265 (60.8%) remained stable, and 72 (16.5%) improved. In multivariable analyses, predictors of NC improvements or declines included time-dependent treatment status and indicators of disease severity (current hematocrit, albumin, total protein, aspartate aminotransferase), and baseline demographics and estimated premorbid intelligence quotient, non-HIV-related comorbidities, current depressive symptoms, and lifetime psychiatric diagnoses (overall model P < .0001). CONCLUSIONS NC change is common in HIV infection and appears to be driven by a complex set of risk factors involving HIV disease, its treatment, and comorbid conditions.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - J. Hampton Atkinson
- University of California, San Diego
- Veterans Affairs San Diego Healthcare System, California
| | | | | | | | | | | | | | - Ned Sacktor
- Johns Hopkins University, Baltimore, Maryland
| | - Susan Morgello
- Icahn School of Medicine at Mount Sinai, New York, New York
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22
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Artz NS, Haufe WM, Hooker CA, Hamilton G, Wolfson T, Campos GM, Gamst AC, Schwimmer JB, Sirlin CB, Reeder SB. Reproducibility of MR-based liver fat quantification across field strength: Same-day comparison between 1.5T and 3T in obese subjects. J Magn Reson Imaging 2015; 42:811-7. [PMID: 25620624 DOI: 10.1002/jmri.24842] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2014] [Accepted: 11/21/2014] [Indexed: 12/14/2022] Open
Abstract
PURPOSE To examine the reproducibility of quantitative magnetic resonance (MR) methods to estimate hepatic proton density fat-fraction (PDFF) at different magnetic field strengths. MATERIALS AND METHODS This Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by the Institutional Review Board. Following informed consent, 25 severely obese subjects (mean body mass index [BMI]: 45 ± 4, range: 38-53 kg/m(2) ) were scanned at 1.5T and 3T on the same day. Two confounder-corrected multiecho chemical shift-encoded gradient-echo-based imaging methods were acquired to estimate PDFF over the entire liver: 3D complex-based (MRI-C) and 2D magnitude-based (MRI-M) MRI. Single-voxel MR spectroscopy (MRS) was performed in the right liver lobe. Using linear regression, pairwise comparisons of estimated PDFF were made between methods (MRI-C, MRI-M, MRS) at each field strength and for each method across field strengths. RESULTS 1.5T vs. 3T regression analyses for MRI-C, MRI-M, and MRS PDFF measurements yielded R(2) values of 0.99, 0.97, and 0.90, respectively. The best-fit line was near unity (slope(m) = 1, intercept(b) = 0), indicating excellent agreement for each case: MRI-C (m = 0.92 [0.87, 0.99], b = 1.4 [0.7, 1.8]); MRI-M (m = 1.0 [0.90, 1.08], b = -1.4 [-2.4, -0.5]); MRS (m = 0.98 [0.82, 1.15], b = 1.2 [-0.2, 3.0]). Comparing MRI-C and MRI-M yielded an R(2) = 0.98 (m = 1.1 [1.02, 1.16], b = -1.8 [-2.8, -1.1]) at 1.5T, and R(2) = 0.99 (m = 0.98 [0.93, 1.03], b = 1.2 [0.7, 1.7]) at 3T. CONCLUSION This study demonstrates that PDFF estimation is reproducible across field strengths and across two confounder-corrected MR-based methods.
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Affiliation(s)
- Nathan S Artz
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
| | - William M Haufe
- Department of Radiology, University of California, San Diego, California, USA
| | - Catherine A Hooker
- Department of Radiology, University of California, San Diego, California, USA
| | - Gavin Hamilton
- Department of Radiology, University of California, San Diego, California, USA
| | - Tanya Wolfson
- Department of Computational and Applied Statistics Laboratory, University of California, San Diego, California, USA
| | | | - Anthony C Gamst
- Department of Computational and Applied Statistics Laboratory, University of California, San Diego, California, USA
| | - Jeffrey B Schwimmer
- Department of Radiology, University of California, San Diego, California, USA.,Department of Pediatrics, University of California, San Diego, California, USA.,Department of Gastroenterology, Rady Children's Hospital, San Diego, California, USA
| | - Claude B Sirlin
- Department of Radiology, University of California, San Diego, California, USA
| | - Scott B Reeder
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, USA.,Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA.,Department of Emergency Medicine, University of Wisconsin, Madison, Wisconsin, USA
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23
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Donohue MC, Jacqmin-Gadda H, Le Goff M, Thomas RG, Raman R, Gamst AC, Beckett LA, Jack CR, Weiner MW, Dartigues JF, Aisen PS. Estimating long-term multivariate progression from short-term data. Alzheimers Dement 2014; 10:S400-10. [PMID: 24656849 PMCID: PMC4169767 DOI: 10.1016/j.jalz.2013.10.003] [Citation(s) in RCA: 101] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2012] [Revised: 05/01/2013] [Accepted: 05/23/2013] [Indexed: 11/19/2022]
Abstract
MOTIVATION Diseases that progress slowly are often studied by observing cohorts at different stages of disease for short periods of time. The Alzheimer's Disease Neuroimaging Initiative (ADNI) follows elders with various degrees of cognitive impairment, from normal to impaired. The study includes a rich panel of novel cognitive tests, biomarkers, and brain images collected every 6 months for as long as 6 years. The relative timing of the observations with respect to disease pathology is unknown. We propose a general semiparametric model and iterative estimation procedure to estimate simultaneously the pathological timing and long-term growth curves. The resulting estimates of long-term progression are fine-tuned using cognitive trajectories derived from the long-term "Personnes Agées Quid" study. RESULTS We demonstrate with simulations that the method can recover long-term disease trends from short-term observations. The method also estimates temporal ordering of individuals with respect to disease pathology, providing subject-specific prognostic estimates of the time until onset of symptoms. When the method is applied to ADNI data, the estimated growth curves are in general agreement with prevailing theories of the Alzheimer's disease cascade. Other data sets with common outcome measures can be combined using the proposed algorithm. AVAILABILITY Software to fit the model and reproduce results with the statistical software R is available as the grace package. ADNI data can be downloaded from the Laboratory of NeuroImaging.
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Affiliation(s)
- Michael C Donohue
- Department of Family and Preventive Medicine, Division of Biostatistics and Bioinformatics, University of California San Diego, La Jolla, CA, USA.
| | | | | | - Ronald G Thomas
- Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Rema Raman
- Department of Family and Preventive Medicine, Division of Biostatistics and Bioinformatics, University of California San Diego, La Jolla, CA, USA; Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Anthony C Gamst
- Department of Family and Preventive Medicine, Division of Biostatistics and Bioinformatics, University of California San Diego, La Jolla, CA, USA; Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Laurel A Beckett
- Department of Public Health Sciences, Biostatistics Unit, University of California Davis, Davis, CA, USA
| | | | - Michael W Weiner
- Center for Imaging of Neurodegenerative Diseases, University of California, San Francisco, CA, USA
| | | | - Paul S Aisen
- Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
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24
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Shirazian H, Chang EY, Wolfson T, Gamst AC, Chung CB, Resnick DL. Prevalence of sternoclavicular joint calcium pyrophosphate dihydrate crystal deposition on computed tomography. Clin Imaging 2014; 38:380-383. [DOI: 10.1016/j.clinimag.2014.02.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2013] [Revised: 02/03/2014] [Accepted: 02/21/2014] [Indexed: 12/17/2022]
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Abstract
Background Individuals with mental health conditions (MHC) have disproportionately high tobacco-related morbidity and mortality due to high smoking prevalence rates. As high consumers of cigarettes, smokers with MHC may consider using e-cigarettes as an alternative form of nicotine delivery. Objective Examination of the susceptibility to use e-cigarettes by individuals with MHC. Methods A US population survey with a national probability sample (n=10 041) was used to assess ever use and current use of regular cigarettes, e-cigarettes, and US Food and Drug Administration-approved pharmacotherapy for smoking cessation. Survey respondents provided information about whether they had been diagnosed with an anxiety disorder, depression, or other MHC. Results Individuals with MHC were more likely to have tried e-cigarettes (14.8%) and to be current users of e-cigarettes (3.1%) than those without MHC (6.6% and 1.1%, respectively; p<0.01). Ever smokers with MHC were also more likely to have tried approved pharmacotherapy (52.2% vs 31.1%, p<0.01) and to be currently using these products (9.9% vs 3.5%, p<0.01) than those without MHC. Additionally, current smokers with MHC were more susceptible to future use of e-cigarettes than smokers without MHC (60.5% vs 45.3%, respectively, p<0.01). Conclusions Smokers with MHC are differentially affected by the rise in popularity of e-cigarettes. Clinical interventions and policies for tobacco control on e-cigarettes should take into account the possible outcomes and their implications for this priority population.
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Affiliation(s)
- Sharon E Cummins
- Department of Family and Preventive Medicine, University of California, San Diego, La Jolla, California, USA
| | - Shu-Hong Zhu
- Department of Family and Preventive Medicine, University of California, San Diego, La Jolla, California, USA
| | - Gary J Tedeschi
- Cancer Center, University of California, San Diego, La Jolla, California, USA
| | - Anthony C Gamst
- Department of Family and Preventive Medicine, University of California, San Diego, La Jolla, California, USA
| | - Mark G Myers
- Psychology Service, Veteran Affairs San Diego Healthcare System, Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
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26
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Chang EY, Pallante-Kichura AL, Bae WC, Du J, Statum S, Wolfson T, Gamst AC, Cory E, Amiel D, Bugbee WD, Sah RL, Chung CB. Development of a Comprehensive Osteochondral Allograft MRI Scoring System (OCAMRISS) with Histopathologic, Micro-Computed Tomography, and Biomechanical Validation. Cartilage 2014; 5:16-27. [PMID: 24489999 PMCID: PMC3904392 DOI: 10.1177/1947603513514436] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
OBJECTIVE To describe and apply a semi-quantitative MRI scoring system for multi-feature analysis of cartilage defect repair in the knee by osteochondral allografts, and to correlate this scoring system with histopathologic, micro-computed tomography (μCT), and biomechanical reference standards using a goat repair model. DESIGN Fourteen adult goats had two osteochondral allografts implanted into each knee: one in the medial femoral condyle (MFC) and one in the lateral trochlea (LT). At 12 months, goats were euthanized and MRI was performed. Two blinded radiologists independently rated nine primary features for each graft, including cartilage signal, fill, edge integration, surface congruity, calcified cartilage integrity, subchondral bone plate congruity, subchondral bone marrow signal, osseous integration, and presence of cystic changes. Four ancillary features of the joint were also evaluated, including opposing cartilage, meniscal tears, synovitis, and fat-pad scarring. Comparison was made with histological and μCT reference standards as well as biomechanical measures. Interobserver agreement and agreement with reference standards was assessed. Cohen's kappa, Spearman's correlation, and Kruskal-Wallis tests were used as appropriate. RESULTS There was substantial agreement (κ>0.6, p<0.001) for each MRI feature and with comparison against reference standards, except for cartilage edge integration (κ=0.6). There was a strong positive correlation between MRI and reference standard scores (ρ=0.86, p<0.01). OCAMRISS was sensitive to differences in outcomes between the types of allografts. CONCLUSIONS We have described a comprehensive MRI scoring system for osteochondral allografts and have validated this scoring system with histopathologic and μCT reference standards as well as biomechanical indentation testing.
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Affiliation(s)
- Eric Y. Chang
- Department of Radiology, VA San Diego Healthcare System, San Diego, CA, USA,Department of Radiology, University of California, San Diego Medical Center, La Jolla, CA, USA
| | | | - Won C. Bae
- Department of Radiology, University of California, San Diego Medical Center, La Jolla, CA, USA
| | - Jiang Du
- Department of Radiology, University of California, San Diego Medical Center, La Jolla, CA, USA
| | - Sheronda Statum
- Department of Radiology, University of California, San Diego Medical Center, La Jolla, CA, USA
| | - Tanya Wolfson
- Department of Radiology, University of California, San Diego Medical Center, La Jolla, CA, USA
| | - Anthony C. Gamst
- Department of Radiology, University of California, San Diego Medical Center, La Jolla, CA, USA
| | - Esther Cory
- Department of Bioengineering, University of California, San Diego, CA, USA
| | - David Amiel
- Department of Orthopaedic Surgery, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - William D. Bugbee
- Department of Orthopaedic Surgery, University of California, San Diego School of Medicine, La Jolla, CA, USA,Department of Orthopaedic Surgery, Scripps Clinic, La Jolla, CA, USA
| | - Robert L. Sah
- Department of Bioengineering, University of California, San Diego, CA, USA,Department of Orthopaedic Surgery, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Christine B. Chung
- Department of Radiology, VA San Diego Healthcare System, San Diego, CA, USA,Department of Radiology, University of California, San Diego Medical Center, La Jolla, CA, USA
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27
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Negrete LM, Middleton MS, Clark L, Wolfson T, Gamst AC, Lam J, Changchien C, Deyoung-Dominguez IM, Hamilton G, Loomba R, Schwimmer J, Sirlin CB. Inter-examination precision of magnitude-based MRI for estimation of segmental hepatic proton density fat fraction in obese subjects. J Magn Reson Imaging 2013; 39:1265-71. [PMID: 24136736 DOI: 10.1002/jmri.24284] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2013] [Accepted: 05/28/2013] [Indexed: 01/30/2023] Open
Abstract
PURPOSE To prospectively describe magnitude-based multi-echo gradient-echo hepatic proton density fat fraction (PDFF) inter-examination precision at 3 Tesla (T). MATERIALS AND METHODS In this prospective, Institutional Review Board-approved, Health Insurance Portability and Accountability Act (HIPAA) compliant study, written informed consent was obtained from 29 subjects (body mass indexes > 30 kg/m2). Three 3T MRI examinations were obtained over 75-90 min. Segmental, lobar, and whole liver PDFF were estimated (using three, four, five, or six echoes) by magnitude-based multi-echo MRI in colocalized regions of interest. For estimate (using three, four, five, or six echoes), at each anatomic level (segmental, lobar, whole liver), three inter-examination precision metrics were computed: intra-class correlation coefficient (ICC), standard deviation (SD), and range. RESULTS Magnitude-based PDFF estimates using each reconstruction method showed excellent inter-examination precision for each segment (ICC ≥ 0.992; SD ≤ 0.66%; range ≤ 1.24%), lobe (ICC ≥ 0.998; SD ≤ 0.34%; range ≤ 0.64%), and the whole liver (ICC = 0.999; SD ≤ 0.24%; range ≤ 0.45%). Inter-examination precision was unaffected by whether PDFF was estimated using three, four, five, or six echoes. CONCLUSION Magnitude-based PDFF estimation shows high inter-examination precision at segmental, lobar, and whole liver anatomic levels, supporting its use in clinical care or clinical trials. The results of this study suggest that longitudinal hepatic PDFF change greater than 1.6% is likely to represent signal rather than noise.
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Affiliation(s)
- Lindsey M Negrete
- Liver Imaging Group, Department of Radiology, University of California at San Diego, San Diego, California, USA; Alpert Medical School of Brown University, Providence, Rhode Island, USA
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28
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Fennema-Notestine C, Ellis RJ, Archibald SL, Jernigan TL, Letendre SL, Notestine RJ, Taylor MJ, Theilmann RJ, Julaton MD, Croteau DJ, Wolfson T, Heaton RK, Gamst AC, Franklin DR, Clifford DB, Collier AC, Gelman BB, Marra C, McArthur JC, McCutchan JA, Morgello S, Simpson DM, Grant I. Increases in brain white matter abnormalities and subcortical gray matter are linked to CD4 recovery in HIV infection. J Neurovirol 2013; 19:393-401. [PMID: 23838849 DOI: 10.1007/s13365-013-0185-7] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2013] [Revised: 05/21/2013] [Accepted: 06/21/2013] [Indexed: 10/26/2022]
Abstract
MRI alterations in the cerebral white (WM) and gray matter (GM) are common in HIV infection, even during successful combination antiretroviral therapy (CART), and their pathophysiology and clinical significance are unclear. We evaluated the association of these alterations with recovery of CD4+ T cells. Seventy-five HIV-infected (HIV+) volunteers in the CNS HIV Anti-Retroviral Therapy Effects Research study underwent brain MRI at two visits. Multi-channel morphometry yielded volumes of total cerebral WM, abnormal WM, cortical and subcortical GM, and ventricular and sulcal CSF. Multivariable linear regressions were used to predict volumetric changes with change in current CD4 and detectable HIV RNA. On average, the cohort (79 % initially on CART) demonstrated loss of total cerebral WM alongside increases in abnormal WM and ventricular volumes. A greater extent of CD4 recovery was associated with increases in abnormal WM and subcortical GM volumes. Virologic suppression was associated with increased subcortical GM volume, independent of CD4 recovery. These findings suggest a possible link between brain alterations and immune recovery, distinct from the influence of virologic suppression. The association of increasing abnormal WM and subcortical GM volumes with CD4+ T cell recovery suggests that neuroinflammation may be one mechanism in CNS pathogenesis.
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Chang EY, Lim WY, Wolfson T, Gamst AC, Chung CB, Bae WC, Resnick DL. Frequency of atlantoaxial calcium pyrophosphate dihydrate deposition at CT. Radiology 2013; 269:519-24. [PMID: 23737539 DOI: 10.1148/radiol.13130125] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
PURPOSE To determine (a) the prevalence of atlantoaxial calcium pyrophosphate dihydrate (CPPD) crystal deposition in a population of patients undergoing computed tomography (CT) for acute trauma and (b) the association between atlantoaxial CPPD crystal deposition and retro-odontoid soft-tissue thickness. MATERIALS AND METHODS This HIPAA-compliant study was approved by the institutional review board, and the requirement to obtain informed consent was waived. In 513 consecutive patients, CT scans of the cervical spine obtained for acute trauma were retrospectively reviewed for the presence of atlantoaxial CPPD crystal deposition, and the maximal thickness of the retro-odontoid soft tissues was measured. The relationships among imaging findings, age, and sex were assessed with the t test, the χ(2) test, Spearman correlation, and logistic and linear regression models as appropriate. RESULTS The overall prevalence of atlantoaxial CPPD crystal deposition was 12.5% (64 of 513 patients), and prevalence increased with age (P < .0001, logistic regression coefficient). In patients aged 60 years and older, the prevalence of CPPD crystal deposition was 34% (58 of 170 patients). In patients aged 80 years and older, the prevalence of CPPD crystal deposition was 49% (37 of 75 patients). There was a positive correlation between age and retro-odontoid soft-tissue thickness (Spearman ρ = 0.48, P < .0001). The mean retro-odontoid soft-tissue thickness in patients with CPPD crystal deposition was greater than that in patients without CPPD crystal deposition (3.4 mm vs 2.2 mm, respectively; P < .0001, t test). CONCLUSION CPPD crystal deposition in the cervical spine is seen with a higher prevalence than previously reported. CPPD crystal deposition shows a positive correlation with age and retro-odontoid soft-tissue thickening.
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Affiliation(s)
- Eric Y Chang
- Department of Radiology, VA San Diego Healthcare System, 3350 La Jolla Village Dr, MC 114, San Diego, CA 92161
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30
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Levin YS, Yokoo T, Wolfson T, Gamst AC, Collins J, Achmad EA, Hamilton G, Middleton MS, Loomba R, Sirlin CB. Effect of echo-sampling strategy on the accuracy of out-of-phase and in-phase multiecho gradient-echo MRI hepatic fat fraction estimation. J Magn Reson Imaging 2013; 39:567-75. [PMID: 23720420 DOI: 10.1002/jmri.24193] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2012] [Accepted: 04/05/2013] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To assess the effect of echo-sampling strategy on the accuracy of out-of-phase (OP) and in-phase (IP) multiecho gradient-echo magnetic resonance imaging (MRI) hepatic fat fraction (FF) estimation, using MR spectroscopy (MRS) proton density FF (PDFF) as a reference standard. MATERIALS AND METHODS In this Institutional Review Board (IRB)-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant prospective study, 84 subjects underwent proton MRS and non-T1 -weighted gradient-echo imaging of the liver at 3T. Imaging data were collected at 16 nominally OP and IP echo times (TEs). MRI-FF was estimated while varying two echo-sampling parameters (number of consecutive echoes, starting echo number). For each combination of these parameters, MRI-FF estimation accuracy was assessed with slope, intercept, average bias, and R2 from a linear regression of MRS-PDFF on MRI-FF. The relationship between accuracy metrics and echo-sampling parameters was assessed by Spearman rank correlation. RESULTS For FF calculations using 3-16 echoes and a starting echo number of 1, the intercept ranged from 0.0046 to 0.0124, slope from 0.941 to 0.96, average bias from 0.0034 to 0.0078, and R2 from 0.968 to 0.976. All four accuracy metrics were the best with the 3- and 4-echo calculations and worsened progressively with an increasing number of echoes. For a given number of echoes, there was an overall trend toward decreasing accuracy as starting echo number increased. Spearman correlation coefficients between starting echo number and intercept, slope, average bias, and R2 were 0.911, -0.64, -0.889, and -0.954, respectively, indicating progressive loss of accuracy in each case. CONCLUSION Multiecho OP and IP imaging provided high FF estimation accuracy. Accuracy was highest using the earliest 3 or 4 echoes. Incorporation of additional echoes or delaying the starting echo number progressively reduced accuracy.
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Affiliation(s)
- Yakir S Levin
- University of California, San Diego, Department of Radiology, San Diego, California, USA
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Johnson BL, Schroeder ME, Wolfson T, Gamst AC, Hamilton G, Shiehmorteza M, Loomba R, Schwimmer JB, Reeder S, Middleton MS, Sirlin CB. Effect of flip angle on the accuracy and repeatability of hepatic proton density fat fraction estimation by complex data-based, T1-independent, T2*-corrected, spectrum-modeled MRI. J Magn Reson Imaging 2013; 39:440-7. [PMID: 23596052 DOI: 10.1002/jmri.24153] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2012] [Accepted: 03/04/2013] [Indexed: 11/07/2022] Open
Abstract
PURPOSE To evaluate the effect of flip angle (FA) on accuracy and within-examination repeatability of hepatic proton-density fat fraction (PDFF) estimation with complex data-based magnetic resonance imaging (MRI). MATERIALS AND METHODS PDFF was estimated at 3T in 30 subjects using two sets of five MRI sequences with FA from 1° to 5° in each set. One set used 7 msec repetition time and acquired 6 echoes (TR7/E6); the other used 14 msec and acquired 12 echoes (TR14/E12). For each FA in both sets the accuracy of MRI-PDFF was assessed relative to MR spectroscopy (MRS)-PDFF using four regression parameters (slope, intercept, average bias, R(2) ). Each subject had four random sequences repeated; within-examination repeatability of MRI-PDFF for each FA was assessed with intraclass correlation coefficient (ICC). Pairwise comparisons were made using bootstrap-based tests. RESULTS Most FAs provided high MRI-PDFF estimation accuracy (intercept range -1.25 to 0.84, slope 0.89-1.06, average bias 0.24-1.65, R(2) 0.85-0.97). Most comparisons of regression parameters between FAs were not significant. Informally, in the TR7/E6 set, FAs of 2° and 3° provided the highest accuracy, while FAs of 1° and 5° provided the lowest. In the TR14/E12 set, accuracy parameters did not differ consistently between FAs. FAs in both sets provided high within-examination repeatability (ICC range 0.981-0.998). CONCLUSION MRI-PDFF was repeatable and, for most FAs, accurate in both sequence sets. In the TR7/E6 sequence set, FAs of 2° and 3° informally provided the highest accuracy. In the TR14/E12 sequence set, all FAs provided similar accuracy.
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Affiliation(s)
- Benjamin L Johnson
- Liver Imaging Group (LIG), Department of Radiology, University of California at San Diego, San Diego, California, USA
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Tang A, Tan J, Sun M, Hamilton G, Bydder M, Wolfson T, Gamst AC, Middleton M, Brunt EM, Loomba R, Lavine JE, Schwimmer JB, Sirlin CB. Nonalcoholic fatty liver disease: MR imaging of liver proton density fat fraction to assess hepatic steatosis. Radiology 2013; 267:422-31. [PMID: 23382291 DOI: 10.1148/radiol.12120896] [Citation(s) in RCA: 366] [Impact Index Per Article: 33.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE To evaluate the diagnostic performance of magnetic resonance (MR) imaging-estimated proton density fat fraction (PDFF) for assessing hepatic steatosis in nonalcoholic fatty liver disease (NAFLD) by using centrally scored histopathologic validation as the reference standard. MATERIALS AND METHODS This prospectively designed, cross-sectional, internal review board-approved, HIPAA-compliant study was conducted in 77 patients who had NAFLD and liver biopsy. MR imaging-PDFF was estimated from magnitude-based low flip angle multiecho gradient-recalled echo images after T2* correction and multifrequency fat modeling. Histopathologic scoring was obtained by consensus of the Nonalcoholic Steatohepatitis (NASH) Clinical Research Network Pathology Committee. Spearman correlation, additivity and variance stabilization for regression for exploring the effect of a number of potential confounders, and receiver operating characteristic analyses were performed. RESULTS Liver MR imaging-PDFF was systematically higher, with higher histologic steatosis grade (P < .001), and was significantly correlated with histologic steatosis grade (ρ = 0.69, P < .001). The correlation was not confounded by age, sex, lobular inflammation, hepatocellular ballooning, NASH diagnosis, fibrosis, or magnetic field strength (P = .65). Area under the receiver operating characteristic curves was 0.989 (95% confidence interval: 0.968, 1.000) for distinguishing patients with steatosis grade 0 (n = 5) from those with grade 1 or higher (n = 72), 0.825 (95% confidence interval: 0.734, 0.915) to distinguish those with grade 1 or lower (n = 31) from those with grade 2 or higher (n = 46), and 0.893 (95% confidence interval: 0.809, 0.977) to distinguish those with grade 2 or lower (n = 58) from those with grade 3 (n = 19). CONCLUSION MR imaging-PDFF showed promise for assessment of hepatic steatosis grade in patients with NAFLD. For validation, further studies with larger sample sizes are needed.
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Affiliation(s)
- An Tang
- Liver Imaging Group, Department of Radiology, University of California San Diego, 408 Dickinson St, San Diego, CA 92103-8226, USA
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von Känel R, Natarajan L, Ancoli-Israel S, Mills PJ, Wolfson T, Gamst AC, Loredo JS, Dimsdale JE. Effect of continuous positive airway pressure on day/night rhythm of prothrombotic markers in obstructive sleep apnea. Sleep Med 2013; 14:58-65. [PMID: 23036264 PMCID: PMC3540139 DOI: 10.1016/j.sleep.2012.07.009] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2012] [Revised: 06/02/2012] [Accepted: 07/26/2012] [Indexed: 11/22/2022]
Abstract
OBJECTIVE Obstructive sleep apnea (OSA) has been associated with an increased risk of atherothrombotic events. A prothrombotic state might partially explain this link. This study investigated OSA patients' day/night rhythm of several prothrombotic markers and their potential changes with therapeutic continuous positive airway pressure (CPAP). METHODS The study included 51 OSA patients [apnea hypopnea index (AHI) ⩾10] and 24 non-OSA controls (AHI<10). Of the 51 OSA patients, 25 were randomized to CPAP and 26 to placebo-CPAP. Twelve blood samples were collected over a 24h period to measure prothrombotic markers. For the apneic patients these samples were collected before treatment and after 3weeks of treatment with either CPAP or placebo-CPAP. Day/night variation in prothrombotic markers was examined using a cosinor analysis. RESULTS Compared with controls, OSA patients showed lower mesor (mean) and amplitude (difference between maximum and minimum activity) of D-dimer. In unadjusted (but not in adjusted) analysis, patients showed higher mesor of plasminogen activator inhibitor-1 (p<0.05 in all cases). No significant group differences were seen in mesor and amplitude for either soluble tissue factor or von Willebrand factor, or the acrophase (time of the peak) and periodic pattern for any prothrombotic markers. There were no significant differences in changes of periodic pattern and in day/night rhythm parameters of prothrombotic markers pre- to post-treatment between the CPAP and placebo condition. CONCLUSIONS There may be altered day/night rhythm of some prothrombotic markers in OSA patients compared with controls. CPAP treatment for 3weeks did not affect day/night rhythm of prothrombotic markers in OSA patients differently from placebo-CPAP.
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Affiliation(s)
- Roland von Känel
- Department of General Internal Medicine, Inselspital, Bern University Hospital, and University of Bern, Switzerland
- Department of Psychiatry, University of California, San Diego, USA
| | - Loki Natarajan
- Department of Family and Preventive Medicine, University of California, San Diego, USA
| | - Sonia Ancoli-Israel
- Department of Psychiatry, University of California, San Diego, USA
- Department of Medicine, University of California, San Diego, USA
| | - Paul J. Mills
- Department of Psychiatry, University of California, San Diego, USA
| | - Tanya Wolfson
- Computational and Applied Statistics Laboratory, San Diego, Supercomputer Center University of California, San Diego, USA
| | - Anthony C. Gamst
- Computational and Applied Statistics Laboratory, San Diego, Supercomputer Center University of California, San Diego, USA
| | - José S. Loredo
- Department of Medicine, University of California, San Diego, USA
| | - Joel E. Dimsdale
- Department of Psychiatry, University of California, San Diego, USA
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Bae WC, Statum S, Zhang Z, Yamaguchi T, Wolfson T, Gamst AC, Du J, Bydder GM, Masuda K, Chung CB. Morphology of the cartilaginous endplates in human intervertebral disks with ultrashort echo time MR imaging. Radiology 2012. [PMID: 23192776 DOI: 10.1148/radiol.12121181] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
PURPOSE To image human disk-bone specimens by using conventional spin-echo (SE) and ultrashort echo time (TE) techniques, to describe the morphology at magnetic resonance (MR) imaging, and to identify tissue components contributing to high signal intensity near the cartilaginous endplates (CEPs). MATERIALS AND METHODS This study was exempt from institutional review board approval, and informed consent was not required. Five cadaveric lumbar spines (mean age, 61 years ± 11) were prepared into six sample types containing different combinations of disk, uncalcified CEP, calcified CEP, and subchondral bone components and were imaged with proton density-weighted SE (repetition time msec/TE msec, 2000/15) and ultrashort TE (300/0.008, 6.6, echo-subtraction) sequences. Images were evaluated to determine the presence of intermediate-to-high signal intensity in regions excluding the bone marrow. Logistic regression was used to determine which tissue components were significant predictors of the presence of signal intensity for each MR technique. RESULTS On ultrashort TE MR images, intact disk/uncalcified CEP/calcified CEP/bone samples exhibited bilaminar intermediate-to-high signal intensity in the region near the CEP, consistent with the histologic appearance of uncalcified and calcified CEPs. Conversely, proton density-weighted SE images exhibited low signal intensity in this region. Results of logistic regression suggested that the presence of uncalcified CEP (P = .023) and calcified CEP (P = .007) in the sample were strong predictors of the presence of signal intensity on ultrashort TE images, whereas the disk was the only predictor (P < .001) of signal intensity on proton density-weighted SE images. CONCLUSION Ultrashort TE imaging, unlike proton density-weighted SE imaging, enabled direct visualization of the uncalcified and calcified CEP. Evaluation of the morphology and identification of sources of signal intensity at ultrashort TE MR imaging provides opportunities to potentially aid in the understanding of degenerative disk disease.
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Affiliation(s)
- Won C Bae
- Department of Radiology, University of California-San Diego, 408 Dickinson St, San Diego, CA 92103-8226, USA.
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Bahl G, Cruite I, Wolfson T, Gamst AC, Collins JM, Chavez AD, Barakat F, Hassanein T, Sirlin CB. Noninvasive classification of hepatic fibrosis based on texture parameters from double contrast-enhanced magnetic resonance images. J Magn Reson Imaging 2012; 36:1154-61. [PMID: 22851409 DOI: 10.1002/jmri.23759] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2010] [Accepted: 06/19/2012] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To demonstrate a proof of concept that quantitative texture feature analysis of double contrast-enhanced magnetic resonance imaging (MRI) can classify fibrosis noninvasively, using histology as a reference standard. MATERIALS AND METHODS A Health Insurance Portability and Accountability Act (HIPAA)-compliant Institutional Review Board (IRB)-approved retrospective study of 68 patients with diffuse liver disease was performed at a tertiary liver center. All patients underwent double contrast-enhanced MRI, with histopathology-based staging of fibrosis obtained within 12 months of imaging. The MaZda software program was used to compute 279 texture parameters for each image. A statistical regularization technique, generalized linear model (GLM)-path, was used to develop a model based on texture features for dichotomous classification of fibrosis category (F ≤2 vs. F ≥3) of the 68 patients, with histology as the reference standard. The model's performance was assessed and cross-validated. There was no additional validation performed on an independent cohort. RESULTS Cross-validated sensitivity, specificity, and total accuracy of the texture feature model in classifying fibrosis were 91.9%, 83.9%, and 88.2%, respectively. CONCLUSION This study shows proof of concept that accurate, noninvasive classification of liver fibrosis is possible by applying quantitative texture analysis to double contrast-enhanced MRI. Further studies are needed in independent cohorts of subjects.
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Affiliation(s)
- Gautam Bahl
- University of California, San Diego, Department of Radiology, San Diego, California 92103, USA
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36
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Zhu SH, Cummins SE, Wong S, Gamst AC, Tedeschi GJ, Reyes-Nocon J. The effects of a multilingual telephone quitline for Asian smokers: a randomized controlled trial. J Natl Cancer Inst 2012; 104:299-310. [PMID: 22282542 DOI: 10.1093/jnci/djr530] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Although telephone counseling services (quitlines) have become a popular behavioral intervention for smoking cessation in the United States, such services are scarce for Asian immigrants with limited English proficiency. In this study, we tested the effects of telephone counseling for smoking cessation in Chinese-, Korean-, and Vietnamese-speaking smokers. METHODS A culturally tailored counseling protocol was developed in English and translated into Chinese, Korean, and Vietnamese. We conducted a single randomized trial embedded in the California quitline service. Smokers who called the quitline's Chinese, Korean, and Vietnamese telephone lines between August 2, 2004, and April 4, 2008, were recruited to the trial. Subjects (N = 2277) were stratified by language and randomly assigned to telephone counseling (self-help materials and up to six counseling sessions; n = 1124 subjects) or self-help (self-help materials only; n = 1153 subjects) groups: 729 Chinese subjects (counseling = 359, self-help = 370), 848 Korean subjects (counseling = 422, self-help = 426), and 700 Vietnamese subjects (counseling = 343, self-help = 357). The primary outcome was 6-month prolonged abstinence. Intention-to-treat analysis was used to estimate prolonged abstinence rates for all subjects and for each language group. All statistical tests were two-sided. RESULTS In the intention-to-treat analysis, counseling increased the 6-month prolonged abstinence rate among all smokers compared with self-help (counseling vs self-help, 16.4% vs 8.0%, difference = 8.4%, 95% confidence interval [CI] = 5.7% to 11.1%, P < .001). Counseling also increased the 6-month prolonged abstinence rate for each language group compared with self-help (counseling vs self-help, Chinese, 14.8% vs 6.0%, difference = 8.8%, 95% CI = 4.4% to 13.2%, P < .001; Korean, 14.9% vs 5.2%, difference = 9.7%, 95% CI = 5.8% to 13.8%, P < .001; Vietnamese, 19.8% vs 13.5%, difference = 6.3%, 95% CI = 0.9% to 11.9%, P = .023). CONCLUSIONS Telephone counseling was effective for Chinese-, Korean-, and Vietnamese-speaking smokers. This protocol should be incorporated into existing quitlines, with possible extension to other Asian languages.
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Affiliation(s)
- Shu-Hong Zhu
- Department of Family and Preventive Medicine, University of California, San Diego, La Jolla, CA 92093-0905, USA.
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Donohue MC, Gamst AC, Thomas RG, Xu R, Beckett L, Petersen RC, Weiner MW, Aisen P. The relative efficiency of time-to-threshold and rate of change in longitudinal data. Contemp Clin Trials 2011; 32:685-93. [PMID: 21554992 PMCID: PMC3148349 DOI: 10.1016/j.cct.2011.04.007] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2010] [Revised: 04/14/2011] [Accepted: 04/21/2011] [Indexed: 11/30/2022]
Abstract
Randomized, placebo-controlled trials often use time-to-event as the primary endpoint, even when a continuous measure of disease severity is available. We compare the power to detect a treatment effect using either rate of change, as estimated by linear models of longitudinal continuous data, or time-to-event estimated by Cox proportional hazards models. We propose an analytic inflation factor for comparing the two types of analyses assuming that the time-to-event can be expressed as a time-to-threshold of the continuous measure. We conduct simulations based on a publicly available Alzheimer's disease data set in which the time-to-event is algorithmically defined based on a battery of assessments. A Cox proportional hazards model of the time-to-event endpoint is compared to a linear model of a single assessment from the battery. The simulations also explore the impact of baseline covariates in either analysis.
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Affiliation(s)
- M C Donohue
- Division of Biostatistics and Bioinformatics, Department of Family and Preventive Medicine, University of California, San Diego, CA, United States.
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Kang GH, Cruite I, Shiehmorteza M, Wolfson T, Gamst AC, Hamilton G, Bydder M, Middleton MS, Sirlin CB. Reproducibility of MRI-determined proton density fat fraction across two different MR scanner platforms. J Magn Reson Imaging 2011; 34:928-34. [PMID: 21769986 DOI: 10.1002/jmri.22701] [Citation(s) in RCA: 113] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2010] [Accepted: 05/31/2011] [Indexed: 01/08/2023] Open
Abstract
PURPOSE To evaluate magnetic resonance imaging (MRI)-determined proton density fat fraction (PDFF) reproducibility across two MR scanner platforms and, using MR spectroscopy (MRS)-determined PDFF as reference standard, to confirm MRI-determined PDFF estimation accuracy. MATERIALS AND METHODS This prospective, cross-sectional, crossover, observational pilot study was approved by an Institutional Review Board. Twenty-one subjects gave written informed consent and underwent liver MRI and MRS at both 1.5T (Siemens Symphony scanner) and 3T (GE Signa Excite HD scanner). MRI-determined PDFF was estimated using an axial 2D spoiled gradient-recalled echo sequence with low flip-angle to minimize T1 bias and six echo-times to permit correction of T2* and fat-water signal interference effects. MRS-determined PDFF was estimated using a stimulated-echo acquisition mode sequence with long repetition time to minimize T1 bias and five echo times to permit T2 correction. Interscanner reproducibility of MRI determined PDFF was assessed by correlation analysis; accuracy was assessed separately at each field strength by linear regression analysis using MRS-determined PDFF as reference standard. RESULTS 1.5T and 3T MRI-determined PDFF estimates were highly correlated (r = 0.992). MRI-determined PDFF estimates were accurate at both 1.5T (regression slope/intercept = 0.958/-0.48) and 3T (slope/intercept = 1.020/0.925) against the MRS-determined PDFF reference. CONCLUSION MRI-determined PDFF estimation is reproducible and, using MRS-determined PDFF as reference standard, accurate across two MR scanner platforms at 1.5T and 3T.
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Affiliation(s)
- Geraldine H Kang
- Liver Imaging Group, Department of Radiology, University of California, San Diego Medical Center, University of California at San Diego, MR3T Laboratory, San Diego, California 92103-8226, USA
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Donohue MC, Gamst AC, Aisen PS. Requiring an amyloid-β1-42 biomarker for prodromal Alzheimer's disease or mild cognitive impairment does not lead to more efficient clinical trials. Alzheimers Dement 2011; 7:245-6; author reply 247-9. [PMID: 21414558 DOI: 10.1016/j.jalz.2010.12.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2010] [Accepted: 12/06/2010] [Indexed: 10/18/2022]
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40
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Yokoo T, Shiehmorteza M, Hamilton G, Wolfson T, Schroeder ME, Middleton MS, Bydder M, Gamst AC, Kono Y, Kuo A, Patton HM, Horgan S, Lavine JE, Schwimmer JB, Sirlin CB. Estimation of hepatic proton-density fat fraction by using MR imaging at 3.0 T. Radiology 2011; 258:749-59. [PMID: 21212366 DOI: 10.1148/radiol.10100659] [Citation(s) in RCA: 222] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE To compare the accuracy of several magnetic resonance (MR) imaging-based methods for hepatic proton-density fat fraction (FF) estimation at 3.0 T, with spectroscopy as the reference technique. MATERIALS AND METHODS This prospective study was institutional review board approved and HIPAA compliant. Informed consent was obtained. One hundred sixty-three subjects (39 with known hepatic steatosis, 110 with steatosis risk factors, 14 without risk factors) underwent proton MR spectroscopy and non-T1-weighted gradient-echo MR imaging of the liver. At spectroscopy, the reference FF was determined from frequency-selective measurements of fat and water proton densities. At imaging, FF was calculated by using two-, three-, or six-echo methods, with single-frequency and multifrequency fat signal modeling. The three- and six-echo methods corrected for T2*; the two-echo methods did not. For each imaging method, the fat estimation accuracy was assessed by using linear regression between the imaging FF and spectroscopic FF. Binary classification accuracy of imaging was assessed at four reference spectroscopic thresholds (0.04, 0.06, 0.08, and 0.10 FF). RESULTS Regression intercept of two-, three-, and six-echo methods were -0.0211, 0.0087, and -0.0062 (P <.001 for all three) without multifrequency modeling and -0.0237 (P <.001), 0.0022, and -0.0007 with multifrequency modeling, respectively. Regression slope of two-, three-, and six-echo methods were 0.8522, 0.8528, and 0.7544 (P <.001 for all three) without multifrequency modeling and 0.9994, 0.9775, and 0.9821 with multifrequency modeling, respectively. Significant deviation of intercept and slope from 0 and 1, respectively, indicated systematic error. Classification accuracy was 82.2%-90.1%, 93.9%-96.3%, and 83.4%-89.6% for two-, three-, and six-echo methods without multifrequency modeling and 88.3%-92.0%, 95.1%-96.3%, and 94.5%-96.3% with multifrequency modeling, respectively, depending on the FF threshold. T2*-corrected (three- and six-echo) multifrequency imaging methods had the overall highest FF estimation and classification accuracy. Among methods without multifrequency modeling, the T2-corrected three-echo method had the highest accuracy. CONCLUSION Non-T1-weighted MR imaging with T2 correction and multifrequency modeling helps accurately estimate hepatic proton-density FF at 3.0 T.
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Affiliation(s)
- Takeshi Yokoo
- Department of Radiology, University of California at San Diego, 408 Dickinson St, San Diego, CA 92103-8592, USA
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Peavy GM, Jacobson MW, Goldstein JL, Hamilton JM, Kane A, Gamst AC, Lessig SL, Lee JC, Corey-Bloom J. Cognitive and functional decline in Huntington's disease: dementia criteria revisited. Mov Disord 2010; 25:1163-9. [PMID: 20629124 DOI: 10.1002/mds.22953] [Citation(s) in RCA: 77] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
The importance of designating criteria for diagnosing dementia lies in its implications for clinical treatment, research, caregiving, and decision-making. Dementia diagnosis in Huntington's disease (HD) is often based on criteria developed for Alzheimer's disease requiring memory loss. However, it is likely that other cognitive deficits contribute to functional impairment in HD before memory declines. The goal is to identify cognitive deficits that contribute to functional impairment to support dementia criteria that reflect HD neuropathology. Eighty-four HD mutation-positive subjects completed neuropsychological tests and the Unified Huntington's Disease Rating Scale Functional Independence Scale (FIS). Functional impairment was defined as 80 or below on the FIS. Speed of processing, initiation, and attention measures accounted for 70.0% of the variance in FIS ratings (linear regression) and correctly classified 91.7% of subjects as functionally impaired or intact (logistic regression). Measures of memory, motor impairment except dysarthria, neuroleptic use, and depressed mood did not improve prediction. A definition of HD dementia that includes cognitive impairment in at least two areas of cognition but does not require a memory deficit, in the context of impaired functional abilities and a deteriorating course, more accurately reflects HD neuropathology and could lead to improved research methods and patient care.
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Affiliation(s)
- Guerry M Peavy
- Department of Neurosciences, University of California, San Diego, California, USA
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Petersen RC, Aisen PS, Beckett LA, Donohue MC, Gamst AC, Harvey DJ, Jack CR, Jagust WJ, Shaw LM, Toga AW, Trojanowski JQ, Weiner MW. Alzheimer's Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology 2009; 74:201-9. [PMID: 20042704 DOI: 10.1212/wnl.0b013e3181cb3e25] [Citation(s) in RCA: 1210] [Impact Index Per Article: 80.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Neuroimaging measures and chemical biomarkers may be important indices of clinical progression in normal aging and mild cognitive impairment (MCI) and need to be evaluated longitudinally. OBJECTIVE To characterize cross-sectionally and longitudinally clinical measures in normal controls, subjects with MCI, and subjects with mild Alzheimer disease (AD) to enable the assessment of the utility of neuroimaging and chemical biomarker measures. METHODS A total of 819 subjects (229 cognitively normal, 398 with MCI, and 192 with AD) were enrolled at baseline and followed for 12 months using standard cognitive and functional measures typical of clinical trials. RESULTS The subjects with MCI were more memory impaired than the cognitively normal subjects but not as impaired as the subjects with AD. Nonmemory cognitive measures were only minimally impaired in the subjects with MCI. The subjects with MCI progressed to dementia in 12 months at a rate of 16.5% per year. Approximately 50% of the subjects with MCI were on antidementia therapies. There was minimal movement on the Alzheimer's Disease Assessment Scale-Cognitive Subscale for the normal control subjects, slight movement for the subjects with MCI of 1.1, and a modest change for the subjects with AD of 4.3. Baseline CSF measures of Abeta-42 separated the 3 groups as expected and successfully predicted the 12-month change in cognitive measures. CONCLUSION The Alzheimer's Disease Neuroimaging Initiative has successfully recruited cohorts of cognitively normal subjects, subjects with mild cognitive impairment (MCI), and subjects with Alzheimer disease with anticipated baseline characteristics. The 12-month progression rate of MCI was as predicted, and the CSF measures heralded progression of clinical measures over 12 months.
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Affiliation(s)
- R C Petersen
- Department of Neurology, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.
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Yaari R, Fleisher AS, Gamst AC, Bagwell VP, Thal LJ. Utility of the telephone interview for cognitive status for enrollment in clinical trials. Alzheimers Dement 2009; 2:104-9. [PMID: 19595866 DOI: 10.1016/j.jalz.2006.02.004] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2005] [Revised: 02/03/2006] [Accepted: 02/09/2006] [Indexed: 10/24/2022]
Abstract
BACKGROUND The modified Telephone Interview for Cognitive Status (TICS-m) assesses cognitive status via the telephone and has been used to recruit for clinical trials by screening for amnestic mild cognitive impairment (aMCI). The utility of screening for aMCI has not been validated, and it is unknown which questions best predict aMCI. METHODS The Alzheimer's Disease Cooperative Study (ADCS) used the TICS-m to recruit for an aMCI clinical trial. If telephone respondents screened positive for aMCI on the TICS-m, they were referred to a clinical site where they were assessed for the operational criteria of aMCI. Univariate analyses identified the TICS-m questions that best predicted aMCI, creating a final model using forward stepwise logistic regression. RESULTS Of 52,722 calls, 16,312 were screened for trial entry. Of these, 4,883 received the TICS-m. The 2,431 that screened positive for aMCI were referred to a clinic, and 527 arrived for clinical assessment. Of these, 266 met operational criteria for aMCI. The positive predictive value of the TICS-m in this population is 50.9% (95% confidence interval [CI], 46.2% to 54.8%). The final model included 5 variables: (1) 10-word list delayed recall (p < 0.001), (2) day of month (p = 0.002), (3) season (p = 0.009), (4) last name of current president (p = 0.020), and (5) month (p = 0.036). This model has a predictive accuracy of 0.61 (95% CI, 0.51 to 0.71) which is similar to the entire TICS-m. The predictive accuracy of the 10-word list delayed recall alone was 0.63 (95% CI, 0.54 to 0.72). CONCLUSION The TICS-m is not optimally efficient for recruitment of subjects for aMCI clinical trials. The 10-word delayed recall has a predictive accuracy similar to that of the entire TICS-m.
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Affiliation(s)
- Roy Yaari
- Department of Neurosciences, University of California-San Diego, La Jolla, CA, USA.
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Peavy GM, Salmon DP, Jacobson MW, Hervey A, Gamst AC, Wolfson T, Patterson TL, Goldman S, Mills PJ, Khandrika S, Galasko D. Effects of chronic stress on memory decline in cognitively normal and mildly impaired older adults. Am J Psychiatry 2009; 166:1384-91. [PMID: 19755573 PMCID: PMC2864084 DOI: 10.1176/appi.ajp.2009.09040461] [Citation(s) in RCA: 127] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
OBJECTIVE The literature provides evidence of a strong relationship between greater stress and memory loss, but few studies have examined this relationship with both variables measured over time. The authors sought to determine the prospective association between subjective and objective measures of chronic stress and rate of memory decline in cognitively normal and mildly impaired older adults. METHOD This longitudinal study was conducted at a university research center and included 61 cognitively normal subjects and 41 subjects with mild cognitive impairment (ages 65-97). Fifty-two subjects were followed for up to 3 years (mean=2 years) and received repeated stress and cognitive assessments. Exclusion criteria were dementia, significant medical or psychiatric conditions, and medication use (e.g., corticosteroids) that might affect cortisol level or cognitive functioning. The main outcome measure was a regression-based slope reflecting performance change on tests of global cognition and episodic memory as a function of baseline diagnosis, recent life events, and salivary cortisol. Examiners were blind to stress ratings and cortisol levels at the time of cognitive testing. RESULTS Higher event-based stress ratings collected over the follow-up period were associated with faster cognitive decline in subjects with mild cognitive impairment but not in cognitively normal subjects. In contrast, higher cortisol levels were associated with slower cognitive decline in subjects with mild cognitive impairment but not in cognitively normal subjects. CONCLUSIONS Chronic stress affects cognitive functioning differently in cognitively normal subjects and those with mild cognitive impairment. Cortisol, while likely to have neurotoxic effects over time, may enhance cognitive functioning in older adults compromised by existing cognitive deficits.
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Hightower GK, Letendre SL, Cherner M, Gibson SA, Ellis RJ, Wolfson TJ, Gamst AC, Ignacio CC, Heaton RK, Grant I, Richman DD, Smith DM. Select resistance-associated mutations in blood are associated with lower CSF viral loads and better neuropsychological performance. Virology 2009; 394:243-8. [PMID: 19762060 DOI: 10.1016/j.virol.2009.08.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2009] [Revised: 06/10/2009] [Accepted: 08/04/2009] [Indexed: 11/19/2022]
Abstract
BACKGROUND When antiretroviral therapy does not fully suppress HIV replication, suboptimal levels of antiretrovirals can select for antiretroviral resistant variants of HIV. These variants may exhibit reduced replication capacity and result in lower viral loads in blood. Our study evaluated whether antiretroviral resistance was associated with viral loads in the cerebrospinal fluid (CSF) and better neuropsychological (NP) performance. METHODS We enrolled 94 participants and each participant underwent a comprehensive neuromedical evaluation that used structured clinical assessments of medical history, ART and other medication use, comprehensive NP testing, and neurological and general physical signs of disease. Blood was collected by venipuncture, and all participants were offered lumbar puncture. Univariate and multivariate statistical methods were used to analyze the relationship between antiretroviral resistance, blood and CSF HIV RNA levels, substance use, and NP performance. RESULTS Antiretroviral resistance, detected in blood, was associated with lower CSF viral loads (p<0.01) and better NP performance (p=0.04) in multivariate analyses, independent of past and current ARV use and blood viral loads (model: p<0.01). However, HIV RNA levels in CSF did not independently correlate with NP performance. Low viral loads in the CSF limited our ability to investigate the relationship between antiretroviral resistance detected in CSF and NP performance. CONCLUSIONS Even in the absence of ART, antiretroviral resistance-associated mutations correlate with better NP performance possibly because these mutations reflect reduced neurovirulence compared with wild-type HIV.
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Yokoo T, Bydder M, Hamilton G, Middleton MS, Gamst AC, Wolfson T, Hassanein T, Patton HM, Lavine JE, Schwimmer JB, Sirlin CB. Nonalcoholic fatty liver disease: diagnostic and fat-grading accuracy of low-flip-angle multiecho gradient-recalled-echo MR imaging at 1.5 T. Radiology 2009; 251:67-76. [PMID: 19221054 DOI: 10.1148/radiol.2511080666] [Citation(s) in RCA: 263] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
PURPOSE To assess the accuracy of four fat quantification methods at low-flip-angle multiecho gradient-recalled-echo (GRE) magnetic resonance (MR) imaging in nonalcoholic fatty liver disease (NAFLD) by using MR spectroscopy as the reference standard. MATERIALS AND METHODS In this institutional review board-approved, HIPAA-compliant prospective study, 110 subjects (29 with biopsy-confirmed NAFLD, 50 overweight and at risk for NAFLD, and 31 healthy volunteers) (mean age, 32.6 years +/- 15.6 [standard deviation]; range, 8-66 years) gave informed consent and underwent MR spectroscopy and GRE MR imaging of the liver. Spectroscopy involved a long repetition time (to suppress T1 effects) and multiple echo times (to estimate T2 effects); the reference fat fraction (FF) was calculated from T2-corrected fat and water spectral peak areas. Imaging involved a low flip angle (to suppress T1 effects) and multiple echo times (to estimate T2* effects); imaging FF was calculated by using four analysis methods of progressive complexity: dual echo, triple echo, multiecho, and multiinterference. All methods except dual echo corrected for T2* effects. The multiinterference method corrected for multiple spectral interference effects of fat. For each method, the accuracy for diagnosis of fatty liver, as defined with a spectroscopic threshold, was assessed by estimating sensitivity and specificity; fat-grading accuracy was assessed by comparing imaging and spectroscopic FF values by using linear regression. RESULTS Dual-echo, triple-echo, multiecho, and multiinterference methods had a sensitivity of 0.817, 0.967, 0.950, and 0.983 and a specificity of 1.000, 0.880, 1.000, and 0.880, respectively. On the basis of regression slope and intercept, the multiinterference (slope, 0.98; intercept, 0.91%) method had high fat-grading accuracy without statistically significant error (P > .05). Dual-echo (slope, 0.98; intercept, -2.90%), triple-echo (slope, 0.94; intercept, 1.42%), and multiecho (slope, 0.85; intercept, -0.15%) methods had statistically significant error (P < .05). CONCLUSION Relaxation- and interference-corrected fat quantification at low-flip-angle multiecho GRE MR imaging provides high diagnostic and fat-grading accuracy in NAFLD.
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Affiliation(s)
- Takeshi Yokoo
- Department of Radiology, University of California, San Diego Medical Center, University of California at San Diego, MR3 Laboratory, 408 Dickinson St, San Diego, CA 92103-8226, USA
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Ramos GA, Kfir M, Lee S, D'Agostini D, Wolfson T, Gamst AC, Pretorius DH. 489: Benefits of a systematic approach in the evaluation of fetal facial 3D volumes. Am J Obstet Gynecol 2008. [DOI: 10.1016/j.ajog.2008.09.518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Fleisher AS, Sun S, Taylor C, Ward CP, Gamst AC, Petersen RC, Jack CR, Aisen PS, Thal LJ. Volumetric MRI vs clinical predictors of Alzheimer disease in mild cognitive impairment. Neurology 2008; 70:191-9. [PMID: 18195264 DOI: 10.1212/01.wnl.0000287091.57376.65] [Citation(s) in RCA: 133] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To compare volumetric MRI of whole brain and medial temporal lobe structures to clinical measures for predicting progression from amnestic mild cognitive impairment (MCI) to Alzheimer disease (AD). METHODS Baseline MRI scans from 129 subjects with amnestic MCI were obtained from participants in the Alzheimer's Disease Cooperative Study group's randomized, placebo-controlled clinical drug trial of donepezil, vitamin E, or placebo. Measures of whole brain, ventricular, hippocampal, and entorhinal cortex volumes were acquired. Participants were followed with clinical and cognitive evaluations until formal criteria for AD were met, or completion of 36 months of follow-up. Logistic regression modeling was done to assess the predictive value of all MRI measures, risk factors such as APOE genotype, age, family history of AD, education, sex, and cognitive test scores for progression to AD. Least angle regression modeling was used to determine which variables would produce an optimal predictive model, and whether adding MRI measures to a model with only clinical measures would improve predictive accuracy. RESULTS Of the four MRI measures evaluated, only ventricular volumes and hippocampal volumes were predictive of progression to AD. Maximal predictive accuracy using only MRI measures was obtained by hippocampal volumes by themselves (60.4%). When clinical variables were added to the model, the predictive accuracy increased to 78.8%. Use of MRI measures did not improve predictive accuracy beyond that obtained by cognitive measures alone. APOE status, MRI, or demographic variables were not necessary for the optimal predictive model. This optimal model included the Delayed 10-word list recall, New York University Delayed Paragraph Recall, and the Alzheimer's Disease Assessment Scale-Cognitive Subscale total score. CONCLUSION In moderate stages of amnestic mild cognitive impairment, common cognitive tests provide better predictive accuracy than measures of whole brain, ventricular, entorhinal cortex, or hippocampal volumes for assessing progression to Alzheimer disease.
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Affiliation(s)
- A S Fleisher
- Department of Neurosciences, University of California, San Diego, CA, USA.
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Fennema-Notestine C, Gamst AC, Quinn BT, Pacheco J, Jernigan TL, Thal L, Buckner R, Killiany R, Blacker D, Dale AM, Fischl B, Dickerson B, Gollub RL. Feasibility of multi-site clinical structural neuroimaging studies of aging using legacy data. Neuroinformatics 2007; 5:235-45. [PMID: 17999200 DOI: 10.1007/s12021-007-9003-9] [Citation(s) in RCA: 83] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2007] [Accepted: 10/05/2007] [Indexed: 11/28/2022]
Abstract
The application of advances in biomedical computing to medical imaging research is enabling scientists to conduct quantitative clinical imaging studies using data collected across multiple sites to test new hypotheses on larger cohorts, increasing the power to detect subtle effects. Given that many research groups have valuable existing (legacy) data, one goal of the Morphometry Biomedical Informatics Research Network (BIRN) Testbed is to assess the feasibility of pooled analyses of legacy structural neuroimaging data in normal aging and Alzheimer's disease. The present study examined whether such data could be meaningfully reanalyzed as a larger combined data set by using rigorous data curation, image analysis, and statistical modeling methods; in this case, to test the hypothesis that hippocampal volume decreases with age and to investigate findings of hippocampal asymmetry. This report describes our work with legacy T1-weighted magnetic resonance (MR) and demographic data related to normal aging that have been shared through the BIRN by three research sites. Results suggest that, in the present application, legacy MR data from multiple sites can be pooled to investigate questions of scientific interest. In particular, statistical analyses suggested that a mixed-effects model employing site as a random effect best fits the data, accounting for site-specific effects while taking advantage of expected comparability of age-related effects. In the combined sample from three sites, significant age-related decline of hippocampal volume and right-dominant hippocampal asymmetry were detected in healthy elderly controls. These expected findings support the feasibility of combining legacy data to investigate novel scientific questions.
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Affiliation(s)
- Christine Fennema-Notestine
- Department of Psychiatry, University of California-San Diego, 9500 Gilman Drive #0841, La Jolla, CA 92093-0841, USA.
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Morris TA, Castrejon S, Devendra G, Gamst AC. No Difference in Risk for Thrombocytopenia During Treatment of Pulmonary Embolism and Deep Venous Thrombosis With Either Low-Molecular-Weight Heparin or Unfractionated Heparin. Chest 2007; 132:1131-9. [PMID: 17646239 DOI: 10.1378/chest.06-2518] [Citation(s) in RCA: 60] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
Abstract
BACKGROUND Low-molecular-weight heparin (LMWH) is a popular alternative to unfractionated heparin (UH) for the treatment of pulmonary embolism (PE) and deep vein thrombosis (DVT), in part based on the perception of a lower risk for heparin-induced thrombocytopenia (HIT). To investigate the evidence supporting this perception, we performed a metaanalysis to compare the incidence of thrombocytopenia between LMWH and UH during PE and/or DVT treatment. METHODS Randomized trials comparing LMWH with UH for PE and/or DVT treatment were searched for in the MEDLINE database, bibliographies, and by correspondence with published investigators. Two reviewers independently selected high-quality studies and extracted data regarding heparin-associated thrombocytopenia (HAT), HIT confirmed by laboratory testing, and heparin-induced thrombocytopenia with thrombosis (HITT). Outcome rates between LMWH and UH were compared using a binomial, generalized linear mixed model with a logit link and Gaussian random effects for study. RESULTS Thirteen studies involving 5,275 patients met inclusion criteria. There were no statistically significant differences in HAT rates between the two treatments (LMWH, 1.2%; UH, 1.5%; p = 0.246). The incidence of documented HIT and HITT was too low to make an adequate comparison between groups. CONCLUSIONS Our review disclosed no statistically significant difference in HAT between LMWH and UH and insufficient evidence to conclude that HIT and HITT rates were different between them. There was no evidence from randomized comparative trials to support the contention that patients receiving treatment for PE or DVT with UH are more prone to these complications than those receiving LMWH.
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Affiliation(s)
- Timothy A Morris
- Division of Pulmonary and Critical Care Medicine, Department of Family and Preventative Medicine, University of San Diego, CA, USA.
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