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Arasu VA, Miglioretti DL, Sprague BL, Alsheik NH, Buist DS, Henderson LM, Herschorn SD, Lee JM, Onega T, Rauscher GH, Wernli KJ, Lehman CD, Kerlikowske K. Population-Based Assessment of the Association Between Magnetic Resonance Imaging Background Parenchymal Enhancement and Future Primary Breast Cancer Risk. J Clin Oncol 2019; 37:954-963. [PMID: 30625040 PMCID: PMC6494266 DOI: 10.1200/jco.18.00378] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
PURPOSE To evaluate comparative associations of breast magnetic resonance imaging (MRI) background parenchymal enhancement (BPE) and mammographic breast density with subsequent breast cancer risk. PATIENTS AND METHODS We examined women undergoing breast MRI in the Breast Cancer Surveillance Consortium from 2005 to 2015 (with one exam in 2000) using qualitative BPE assessments of minimal, mild, moderate, or marked. Breast density was assessed on mammography performed within 5 years of MRI. Among women diagnosed with breast cancer, the first BPE assessment was included if it was more than 3 months before their first diagnosis. Breast cancer risk associated with BPE was estimated using Cox proportional hazards regression. RESULTS Among 4,247 women, 176 developed breast cancer (invasive, n = 129; ductal carcinoma in situ,n = 47) over a median follow-up time of 2.8 years. More women with cancer had mild, moderate, or marked BPE than women without cancer (80% v 66%, respectively). Compared with minimal BPE, increasing BPE levels were associated with significantly increased cancer risk (mild: hazard ratio [HR], 1.80; 95% CI, 1.12 to 2.87; moderate: HR, 2.42; 95% CI, 1.51 to 3.86; and marked: HR, 3.41; 95% CI, 2.05 to 5.66). Compared with women with minimal BPE and almost entirely fatty or scattered fibroglandular breast density, women with mild, moderate, or marked BPE demonstrated elevated cancer risk if they had almost entirely fatty or scattered fibroglandular breast density (HR, 2.30; 95% CI, 1.19 to 4.46) or heterogeneous or extremely dense breasts (HR, 2.61; 95% CI, 1.44 to 4.72), with no significant interaction (P = .82). Combined mild, moderate, and marked BPE demonstrated significantly increased risk of invasive cancer (HR, 2.73; 95% CI, 1.66 to 4.49) but not ductal carcinoma in situ (HR, 1.48; 95% CI, 0.72 to 3.05). CONCLUSION BPE is associated with future invasive breast cancer risk independent of breast density. BPE should be considered for risk prediction models for women undergoing breast MRI.
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Affiliation(s)
- Vignesh A. Arasu
- Kaiser Permanente Medical Center, Vallejo, CA
- University of California, San Francisco, San Francisco, CA
| | - Diana L. Miglioretti
- University of California, Davis, Davis, CA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA
| | - Brian L. Sprague
- University of Vermont Cancer Center, University of Vermont, Burlington, VT
| | | | - Diana S.M. Buist
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA
| | | | - Sally D. Herschorn
- University of Vermont Cancer Center, University of Vermont, Burlington, VT
| | - Janie M. Lee
- University of Washington, and Seattle Cancer Care Alliance, Seattle, WA
| | - Tracy Onega
- Norris Cotton Cancer Center and Geisel School of Medicine at Dartmouth, Lebanon, NH
| | - Garth H. Rauscher
- Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, IL
| | - Karen J. Wernli
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA
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Lecler A, Balvay D, Cuenod C, Marais L, Zmuda M, Sadik J, Galatoire O, Farah E, El Methni J, Zuber K, Bergès O, Savatovsky J, Fournier L. Quality‐based pharmacokinetic model selection on DCE‐MRI for characterizing orbital lesions. J Magn Reson Imaging 2019; 50:1514-1525. [DOI: 10.1002/jmri.26747] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 03/15/2019] [Accepted: 03/18/2019] [Indexed: 12/18/2022] Open
Affiliation(s)
- Augustin Lecler
- Department of NeuroradiologyFoundation Adolphe de Rothschild Hospital Paris France
- Université Paris Descartes Sorbonne Paris Cité, INSERM UMR‐S970Cardiovascular Research Center – PARCC Paris France
| | - Daniel Balvay
- Université Paris Descartes Sorbonne Paris Cité, INSERM UMR‐S970Cardiovascular Research Center – PARCC Paris France
| | - Charles‐André Cuenod
- Université Paris Descartes Sorbonne Paris Cité, INSERM UMR‐S970Cardiovascular Research Center – PARCC Paris France
- Radiology Department, Hôpital Européen Georges PompidouUniversité Paris Descartes Sorbonne Paris Cité, Assistance Publique‐Hôpitaux de Paris Paris France
| | - Louise Marais
- Université Paris Descartes Sorbonne Paris Cité, INSERM UMR‐S970Cardiovascular Research Center – PARCC Paris France
| | - Mathieu Zmuda
- Department of Orbitopalpebral SurgeryFoundation Adolphe de Rothschild Hospital Paris France
| | - Jean‐Claude Sadik
- Department of NeuroradiologyFoundation Adolphe de Rothschild Hospital Paris France
| | - Olivier Galatoire
- Department of Orbitopalpebral SurgeryFoundation Adolphe de Rothschild Hospital Paris France
| | - Edgar Farah
- Department of Orbitopalpebral SurgeryFoundation Adolphe de Rothschild Hospital Paris France
| | - Jonathan El Methni
- MAP5, UMR CNRS 8145Université Paris Descartes Sorbonne Paris Cité France
| | - Kevin Zuber
- Department of Clinical ResearchFoundation Adolphe de Rothschild Hospital Paris France
| | - Olivier Bergès
- Department of NeuroradiologyFoundation Adolphe de Rothschild Hospital Paris France
| | - Julien Savatovsky
- Department of NeuroradiologyFoundation Adolphe de Rothschild Hospital Paris France
| | - Laure Fournier
- Université Paris Descartes Sorbonne Paris Cité, INSERM UMR‐S970Cardiovascular Research Center – PARCC Paris France
- Radiology Department, Hôpital Européen Georges PompidouUniversité Paris Descartes Sorbonne Paris Cité, Assistance Publique‐Hôpitaux de Paris Paris France
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203
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A radiomics nomogram may improve the prediction of IDH genotype for astrocytoma before surgery. Eur Radiol 2019; 29:3325-3337. [PMID: 30972543 DOI: 10.1007/s00330-019-06056-4] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Revised: 12/12/2018] [Accepted: 01/31/2019] [Indexed: 12/12/2022]
Abstract
OBJECTIVES To develop and validate a radiomics nomogram to preoperative prediction of isocitrate dehydrogenase (IDH) genotype for astrocytomas, which might contribute to the pretreatment decision-making and prognosis evaluating. METHODS One hundred five astrocytomas (Grades II-IV) with contrast-enhanced T1-weighted imaging (CE-T1WI), T2 fluid-attenuated inversion recovery (T2FLAIR), and apparent diffusion coefficient (ADC) map were enrolled in this study (training cohort: n = 74; validation cohort: n = 31). IDH1/2 genotypes were determined using Sanger sequencing. A total of 3882 radiomics features were extracted. Support vector machine algorithm was used to build the radiomics signature on the training cohort. Incorporating radiomics signature and clinico-radiological risk factors, the radiomics nomogram was developed. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to assess these models. Kaplan-Meier survival analysis and log rank test were performed to assess the prognostic value of the radiomics nomogram. RESULTS The radiomics signature was built by six selected radiomics features and yielded AUC values of 0.901 and 0.888 in the training and validation cohorts. The radiomics nomogram based on the radiomics signature and age performed better than the clinico-radiological model (training cohort, AUC = 0.913 and 0.817; validation cohort, AUC = 0.900 and 0.804). Additionally, the survival analysis showed that prognostic values of the radiomics nomogram and IDH genotype were similar (log rank test, p < 0.001; C-index = 0.762 and 0.687; z-score test, p = 0.062). CONCLUSIONS The radiomics nomogram might be a useful supporting tool for the preoperative prediction of IDH genotype for astrocytoma, which could aid pretreatment decision-making. KEY POINTS • The radiomics signature based on multiparametric and multiregional MRI images could predict IDH genotype of Grades II-IV astrocytomas. • The radiomics nomogram performed better than the clinico-radiological model, and it might be an easy-to-use supporting tool for IDH genotype prediction. • The prognostic value of the radiomics nomogram was similar with that of the IDH genotype, which might contribute to prognosis evaluating.
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204
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Orlhac F, Frouin F, Nioche C, Ayache N, Buvat I. Validation of A Method to Compensate Multicenter Effects Affecting CT Radiomics. Radiology 2019; 291:53-59. [DOI: 10.1148/radiol.2019182023] [Citation(s) in RCA: 171] [Impact Index Per Article: 34.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Fanny Orlhac
- From the UCA, Inria Sophia Antipolis–Méditerranée, Epione, 2004 route des Lucioles–BP 93, 06 902 Sophia Antipolis Cedex, France (F.O., N.A.); and Imagerie Moléculaire In Vivo, CEA-SHFJ, Inserm, CNRS, Université Paris-Sud, Université Paris-Saclay, Orsay, France (F.F., C.N., I.B.)
| | - Frédérique Frouin
- From the UCA, Inria Sophia Antipolis–Méditerranée, Epione, 2004 route des Lucioles–BP 93, 06 902 Sophia Antipolis Cedex, France (F.O., N.A.); and Imagerie Moléculaire In Vivo, CEA-SHFJ, Inserm, CNRS, Université Paris-Sud, Université Paris-Saclay, Orsay, France (F.F., C.N., I.B.)
| | - Christophe Nioche
- From the UCA, Inria Sophia Antipolis–Méditerranée, Epione, 2004 route des Lucioles–BP 93, 06 902 Sophia Antipolis Cedex, France (F.O., N.A.); and Imagerie Moléculaire In Vivo, CEA-SHFJ, Inserm, CNRS, Université Paris-Sud, Université Paris-Saclay, Orsay, France (F.F., C.N., I.B.)
| | - Nicholas Ayache
- From the UCA, Inria Sophia Antipolis–Méditerranée, Epione, 2004 route des Lucioles–BP 93, 06 902 Sophia Antipolis Cedex, France (F.O., N.A.); and Imagerie Moléculaire In Vivo, CEA-SHFJ, Inserm, CNRS, Université Paris-Sud, Université Paris-Saclay, Orsay, France (F.F., C.N., I.B.)
| | - Irène Buvat
- From the UCA, Inria Sophia Antipolis–Méditerranée, Epione, 2004 route des Lucioles–BP 93, 06 902 Sophia Antipolis Cedex, France (F.O., N.A.); and Imagerie Moléculaire In Vivo, CEA-SHFJ, Inserm, CNRS, Université Paris-Sud, Université Paris-Saclay, Orsay, France (F.F., C.N., I.B.)
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205
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Anderson AN, King JB, Anderson JS. Neuroimaging in Psychiatry and Neurodevelopment: why the emperor has no clothes. Br J Radiol 2019; 92:20180910. [PMID: 30864835 DOI: 10.1259/bjr.20180910] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Neuroimaging has been a dominant force in guiding research into psychiatric and neurodevelopmental disorders for decades, yet researchers have been unable to formulate sensitive or specific imaging tests for these conditions. The search for neuroimaging biomarkers has been constrained by limited reproducibility of imaging techniques, limited tools for evaluating neurochemistry, heterogeneity of patient populations not defined by brain-based phenotypes, limited exploration of temporal components of brain function, and relatively few studies evaluating developmental and longitudinal trajectories of brain function. Opportunities for development of clinically impactful imaging metrics include longer duration functional imaging data sets, new engineering approaches to mitigate suboptimal spatiotemporal resolution, improvements in image post-processing and analysis strategies, big data approaches combined with data sharing of multisite imaging samples, and new techniques that allow dynamical exploration of brain function across multiple timescales. Despite narrow clinical impact of neuroimaging methods, there is reason for optimism that imaging will contribute to diagnosis, prognosis, and treatment monitoring for psychiatric and neurodevelopmental disorders in the near future.
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Affiliation(s)
| | - Jace B King
- 2Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT
| | - Jeffrey S Anderson
- 2Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT
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206
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Considering tumour volume for motion corrected DWI of colorectal liver metastases increases sensitivity of ADC to detect treatment-induced changes. Sci Rep 2019; 9:3828. [PMID: 30846790 PMCID: PMC6405765 DOI: 10.1038/s41598-019-40565-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Accepted: 02/12/2019] [Indexed: 01/20/2023] Open
Abstract
ADC is a potential post treatment imaging biomarker in colorectal liver metastasis however measurements are affected by respiratory motion. This is compounded by increased statistical uncertainty in ADC measurement with decreasing tumour volume. In this prospective study we applied a retrospective motion correction method to improve the image quality of 15 tumour data sets from 11 patients. We compared repeatability of ADC measurements corrected for motion artefact against non-motion corrected acquisition of the same data set. We then applied an error model that estimated the uncertainty in ADC repeatability measurements therefore taking into consideration tumour volume. Test-retest differences in ADC for each tumour, was scaled to their estimated measurement uncertainty, and 95% confidence limits were calculated, with a null hypothesis that there is no difference between the model distribution and the data. An early post treatment scan (within 7 days of starting treatment) was acquired for 12 tumours from 8 patients. When accounting for both motion artefact and statistical uncertainty due to tumour volumes, the threshold for detecting significant post treatment changes for an individual tumour in this data set, reduced from 30.3% to 1.7% (95% limits of agreement). Applying these constraints, a significant change in ADC (5th and 20th percentiles of the ADC histogram) was observed in 5 patients post treatment. For smaller studies, motion correcting data for small tumour volumes increased statistical efficiency to detect post treatment changes in ADC. Lower percentiles may be more sensitive than mean ADC for colorectal metastases.
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207
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Analytical validation of single-kidney glomerular filtration rate and split renal function as measured with magnetic resonance renography. Magn Reson Imaging 2019; 59:53-60. [PMID: 30849485 DOI: 10.1016/j.mri.2019.03.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 03/01/2019] [Accepted: 03/04/2019] [Indexed: 01/04/2023]
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208
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Effect of Reconstruction Parameters on the Quantitative Analysis of Chest Computed Tomography. J Thorac Imaging 2019; 34:92-102. [DOI: 10.1097/rti.0000000000000389] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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209
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Sorensen T, Toutios A, Goldstein L, Narayanan S. Task-dependence of articulator synergies. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2019; 145:1504. [PMID: 31067947 PMCID: PMC6910022 DOI: 10.1121/1.5093538] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Revised: 02/15/2019] [Accepted: 02/19/2019] [Indexed: 06/09/2023]
Abstract
In speech production, the motor system organizes articulators such as the jaw, tongue, and lips into synergies whose function is to produce speech sounds by forming constrictions at the phonetic places of articulation. The present study tests whether synergies for different constriction tasks differ in terms of inter-articulator coordination. The test is conducted on utterances [ɑpɑ], [ɑtɑ], [ɑiɑ], and [ɑkɑ] with a real-time magnetic resonance imaging biomarker that is computed using a statistical model of the forward kinematics of the vocal tract. The present study is the first to estimate the forward kinematics of the vocal tract from speech production data. Using the imaging biomarker, the study finds that the jaw contributes least to the velar stop for [k], more to pharyngeal approximation for [ɑ], still more to palatal approximation for [i], and most to the coronal stop for [t]. Additionally, the jaw contributes more to the coronal stop for [t] than to the bilabial stop for [p]. Finally, the study investigates how this pattern of results varies by participant. The study identifies differences in inter-articulator coordination by constriction task, which support the claim that inter-articulator coordination differs depending on the active articulator synergy.
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Affiliation(s)
- Tanner Sorensen
- Signal Analysis and Interpretation Laboratory, Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, California 90089, USA
| | - Asterios Toutios
- Signal Analysis and Interpretation Laboratory, Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, California 90089, USA
| | - Louis Goldstein
- Department of Linguistics, University of Southern California, Los Angeles, California 90089, USA
| | - Shrikanth Narayanan
- Signal Analysis and Interpretation Laboratory, Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, California 90089, USA
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210
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Inter-platform reproducibility of ultrasonic attenuation and backscatter coefficients in assessing NAFLD. Eur Radiol 2019; 29:4699-4708. [PMID: 30783789 DOI: 10.1007/s00330-019-06035-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Revised: 12/24/2018] [Accepted: 01/22/2019] [Indexed: 12/17/2022]
Abstract
OBJECTIVES To assess inter-platform reproducibility of ultrasonic attenuation coefficient (AC) and backscatter coefficient (BSC) estimates in adults with known/suspected nonalcoholic fatty liver disease (NAFLD). METHODS This HIPAA-compliant prospective study was approved by an institutional review board; informed consent was obtained. Participants with known/suspected NAFLD were recruited and underwent same-day liver examinations with clinical ultrasound scanner platforms from two manufacturers. Each participant was scanned by the same trained sonographer who performed multiple data acquisitions in the right liver lobe using a lateral intercostal approach. Each data acquisition recorded a B-mode image and the underlying radio frequency (RF) data. AC and BSC were calculated using the reference phantom method. Inter-platform reproducibility was evaluated for AC and log-transformed BSC (logBSC = 10log10BSC) by intraclass correlation coefficient (ICC), Pearson's correlation, Bland-Altman analysis with computation of limits of agreement (LOAs), and within-subject coefficient of variation (wCV; applicable to AC). RESULTS Sixty-four participants were enrolled. Mean AC values measured using the two platforms were 0.90 ± 0.13 and 0.94 ± 0.15 dB/cm/MHz while mean logBSC values were - 30.6 ± 5.0 and - 27.9 ± 5.6 dB, respectively. Inter-platform ICC was 0.77 for AC and 0.70 for log-transformed BSC in terms of absolute agreement. Pearson's correlation coefficient was 0.81 for AC and 0.80 for logBSC. Ninety-five percent LOAs were - 0.21 to 0.13 dB/cm/MHz for AC, and - 9.48 to 3.98 dB for logBSC. The wCV was 7% for AC. CONCLUSIONS Hepatic AC and BSC are reproducible across two different ultrasound platforms in adults with known or suspected NAFLD. KEY POINTS • Ultrasonic attenuation coefficient and backscatter coefficient are reproducible between two different ultrasound platforms in adults with NAFLD. • This inter-platform reproducibility may qualify quantitative ultrasound biomarkers for generalized clinical application in patients with suspected/known NAFLD.
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211
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Lecler A, Duron L, Balvay D, Savatovsky J, Bergès O, Zmuda M, Farah E, Galatoire O, Bouchouicha A, Fournier LS. Combining Multiple Magnetic Resonance Imaging Sequences Provides Independent Reproducible Radiomics Features. Sci Rep 2019; 9:2068. [PMID: 30765732 PMCID: PMC6376058 DOI: 10.1038/s41598-018-37984-8] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 12/11/2018] [Indexed: 12/14/2022] Open
Abstract
To evaluate the relative contribution of different Magnetic Resonance Imaging (MRI) sequences for the extraction of radiomics features in a cohort of patients with lacrimal gland tumors. This prospective study was approved by the Institutional Review Board and signed informed consent was obtained from all participants. From December 2015 to April 2017, 37 patients with lacrimal gland lesions underwent MRI before surgery, including axial T1-WI, axial Diffusion-WI, coronal DIXON-T2-WI and coronal post-contrast DIXON-T1-WI. Two readers manually delineated both lacrimal glands to assess inter-observer reproducibility, and one reader performed two successive delineations to assess intra-observer reproducibility. Radiomics features were extracted using an in-house software to calculate 85 features per region-of-interest (510 features/patient). Reproducible features were defined as features presenting both an intra-class correlation coefficient ≥0.8 and a concordance correlation coefficient ≥0.9 across combinations of the three delineations. Among these features, the ones yielding redundant information were identified as clusters using hierarchical clustering based on the Spearman correlation coefficient. All the MR sequences provided reproducible radiomics features (range 14(16%)−37(44%)) and non-redundant clusters (range 5–14). The highest numbers of features and clusters were provided by the water and in-phase DIXON T2-WI and water and in-phase post-contrast DIXON T1-WI (37, 26, 26 and 26 features and 14,12, 9 and 11 clusters, respectively). A total of 145 reproducible features grouped into 51 independent clusters was provided by pooling all the MR sequences. All MRI sequences provided reproducible radiomics features yielding independent information which could potentially serve as biomarkers.
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Affiliation(s)
- A Lecler
- Department of Neuroradiology, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France. .,Université Paris Descartes Sorbonne Paris Cité, INSERM UMR-S970, Cardiovascular Research Center - PARCC, Paris, France.
| | - L Duron
- Department of Neuroradiology, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France.,Université Paris Descartes Sorbonne Paris Cité, INSERM UMR-S970, Cardiovascular Research Center - PARCC, Paris, France
| | - D Balvay
- Université Paris Descartes Sorbonne Paris Cité, INSERM UMR-S970, Cardiovascular Research Center - PARCC, Paris, France
| | - J Savatovsky
- Department of Neuroradiology, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - O Bergès
- Department of Neuroradiology, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - M Zmuda
- Department of Orbitopalpebral Surgery, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - E Farah
- Department of Orbitopalpebral Surgery, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - O Galatoire
- Department of Orbitopalpebral Surgery, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - A Bouchouicha
- Université Paris Descartes Sorbonne Paris Cité, INSERM UMR-S970, Cardiovascular Research Center - PARCC, Paris, France
| | - L S Fournier
- Université Paris Descartes Sorbonne Paris Cité, INSERM UMR-S970, Cardiovascular Research Center - PARCC, Paris, France.,Sorbonne Paris Cité University, Paris Université Paris Descartes Sorbonne Paris Cité, Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Radiology Department, Paris, France
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212
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Kim J, Lee KH, Kim J, Shin YJ, Lee KW. Improved repeatability of subsolid nodule measurement in low-dose lung screening with monoenergetic images: a phantom study. Quant Imaging Med Surg 2019; 9:171-179. [PMID: 30976541 DOI: 10.21037/qims.2018.10.06] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Background To investigate whether monoenergetic images captured with dual-layer spectral computed tomography (CT) can improve the repeatability of subsolid nodule measurement, and whether this approach can further reduce the radiation dose of CT while maintaining its measurement repeatability. Methods An anthropomorphic phantom with simulated subsolid nodules at three different levels was repeatedly scanned with both conventional single-energy CT and dual-layer spectral CT. A proxy for the measurement repeatability in the National Lung Screening Trial (proxy for NLST) was calculated with the typical CT protocol used in NLST. Using the dual-layer spectral CT, monoenergetic images of 40 to 110 keV, with an interval of 10 keV, were generated. The average diameter and volume of a total of 15,120 nodules in 840 CT images were measured by using a commercially-available computer-aided detection (CAD) system. The repeatability coefficient (RC), %RC, and 95% confidence intervals (CIs) of each image set were calculated and compared. Results At the same tube voltage and tube current-time product, monoenergetic images resulted in significantly lower RC than the proxy for NLST, indicating that measurement repeatability was enhanced. When the radiation dose was lowered by 30% or 55%, monoenergetic images showed significantly lower RC at high-energy keV than the proxy for NLST. The estimated measurement repeatability from monoenergetic images with 30% or 55% lower radiation dose was comparable to the repeatability from conventional single-energy CT images with standard radiation dose and iterative reconstruction. Conclusions Monoenergetic images captured by using dual-layer spectral CT can improve the repeatability of subsolid nodule measurement. The use of monoenergetic images would allow lung cancer screening with a lower radiation dose, while maintaining comparable measurement repeatability.
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Affiliation(s)
- Jihang Kim
- Department of Radiology, Seoul National University Bundang Hospital, Gyeonggi-do, Korea
| | - Kyung Hee Lee
- Department of Radiology, Seoul National University Bundang Hospital, Gyeonggi-do, Korea
| | - Junghoon Kim
- Department of Radiology, Seoul National University Bundang Hospital, Gyeonggi-do, Korea
| | - Yoon Joo Shin
- Department of Radiology, Seoul National University Bundang Hospital, Gyeonggi-do, Korea
| | - Kyung Won Lee
- Department of Radiology, Seoul National University Bundang Hospital, Gyeonggi-do, Korea
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213
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Lin C, Harmon S, Bradshaw T, Eickhoff J, Perlman S, Liu G, Jeraj R. Response-to-repeatability of quantitative imaging features for longitudinal response assessment. Phys Med Biol 2019; 64:025019. [PMID: 30566922 DOI: 10.1088/1361-6560/aafa0a] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Quantitative imaging biomarkers (QIBs) are often selected and ranked based on their repeatability performance. In the context of treatment response assessment, however, one must also consider how sensitive a QIB is to measuring changes in the tumour. This work introduces response-to-repeatability ratio (R/R), which weighs the ability of a QIB to detect significant changes with respect to its measurement repeatability and applies it to the case of PET texture features. R/R is evaluated as the proportion of measurable changes from baseline to follow-up for each candidate QIB. We analyse 47 texture features extracted from lesions in bone-metastatic prostate cancer patients who received double baseline and/or baseline to treatment follow-up 18F-NaF PET/CT scans. R/R evaluates the proportion of follow-up changes outside of the 95% limits of agreement (LOA) defined by test-retest values. Intraclass correlation coefficient (ICC) and coefficient of variation (CV) are calculated for each feature. Relationship between ICC and R/R are evaluated with the Spearman's correlation coefficient. R/R varied significantly across texture features: 41/47 (87%) features demonstrated R/R > 5%; 21/47 (45%) features demonstrated R/R > 10%, and 11/47 (23%) features demonstrated R/R > 20%. LOA of features ranged from [0.998, 1.001] to [0.22, 4.86]. Repeatability alone did not qualify a feature for its efficacy at detecting measurable change at follow-up, as shown by weak correlations between R/R and both CV and ICC (ρ = 0.23 and ρ = 0.40, respectively). Three features demonstrated excellent ICC (ICC > 0.75) and R/R greater than that of SUVmax (R/R = 41.8%): skewness (ICC = 0.92, R/R = 75.4%), kurtosis (ICC = 0.88, R/R = 47.0%) and diagonal moment (ICC = 0.88, R/R = 45.5%). R/R characterizes the sensitivity of candidate QIBs to detect measurable changes at follow-up. R/R supplements existing precision performance metrics (e.g. CV, ICC, and LOA) as an index to assess the utility of QIBs for response assessment.
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Affiliation(s)
- Christie Lin
- Department of Medical Physics, University of Wisconsin, Madison, WI, United States of America
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214
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Geethanath S, Vaughan JT. Accessible magnetic resonance imaging: A review. J Magn Reson Imaging 2019; 49:e65-e77. [DOI: 10.1002/jmri.26638] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 12/15/2018] [Accepted: 12/17/2018] [Indexed: 02/01/2023] Open
Affiliation(s)
- Sairam Geethanath
- Columbia Magnetic Resonance Research CenterColumbia University in the City of New York New York USA
| | - John Thomas Vaughan
- Columbia Magnetic Resonance Research CenterColumbia University in the City of New York New York USA
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215
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Jafari R, Sheth S, Spincemaille P, Nguyen TD, Prince MR, Wen Y, Guo Y, Deh K, Liu Z, Margolis D, Brittenham GM, Kierans AS, Wang Y. Rapid automated liver quantitative susceptibility mapping. J Magn Reson Imaging 2019; 50:725-732. [PMID: 30637892 DOI: 10.1002/jmri.26632] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 12/09/2018] [Accepted: 12/11/2018] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Accurate measurement of the liver iron concentration (LIC) is needed to guide iron-chelating therapy for patients with transfusional iron overload. In this work, we investigate the feasibility of automated quantitative susceptibility mapping (QSM) to measure the LIC. PURPOSE To develop a rapid, robust, and automated liver QSM for clinical practice. STUDY TYPE Prospective. POPULATION 13 healthy subjects and 22 patients. FIELD STRENGTH/SEQUENCES 1.5 T and 3 T/3D multiecho gradient-recalled echo (GRE) sequence. ASSESSMENT Data were acquired using a 3D GRE sequence with an out-of-phase echo spacing with respect to each other. All odd echoes that were in-phase (IP) were used to initialize the fat-water separation and field estimation (T2 *-IDEAL) before performing QSM. Liver QSM was generated through an automated pipeline without manual intervention. This IP echo-based initialization method was compared with an existing graph cuts initialization method (simultaneous phase unwrapping and removal of chemical shift, SPURS) in healthy subjects (n = 5). Reproducibility was assessed over four scanners at two field strengths from two manufacturers using healthy subjects (n = 8). Clinical feasibility was evaluated in patients (n = 22). STATISTICAL TESTS IP and SPURS initialization methods in both healthy subjects and patients were compared using paired t-test and linear regression analysis to assess processing time and region of interest (ROI) measurements. Reproducibility of QSM, R2 *, and proton density fat fraction (PDFF) among the four different scanners was assessed using linear regression, Bland-Altman analysis, and the intraclass correlation coefficient (ICC). RESULTS Liver QSM using the IP method was found to be ~5.5 times faster than SPURS (P < 0.05) in initializing T2 *-IDEAL with similar outputs. Liver QSM using the IP method were reproducibly generated in all four scanners (average coefficient of determination 0.95, average slope 0.90, average bias 0.002 ppm, 95% limits of agreement between -0.06 to 0.07 ppm, ICC 0.97). DATA CONCLUSION Use of IP echo-based initialization enables robust water/fat separation and field estimation for automated, rapid, and reproducible liver QSM for clinical applications. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:725-732.
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Affiliation(s)
- Ramin Jafari
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA.,Department of Radiology, Weill Medical College of Cornell University, New York, New York, USA
| | - Sujit Sheth
- Department of Pediatrics, Weill Medical College of Cornell University, New York, New York, USA
| | - Pascal Spincemaille
- Department of Radiology, Weill Medical College of Cornell University, New York, New York, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Medical College of Cornell University, New York, New York, USA
| | - Martin R Prince
- Department of Radiology, Weill Medical College of Cornell University, New York, New York, USA
| | - Yan Wen
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA.,Department of Radiology, Weill Medical College of Cornell University, New York, New York, USA
| | - Yihao Guo
- Department of Radiology, Weill Medical College of Cornell University, New York, New York, USA.,School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Kofi Deh
- Department of Radiology, Weill Medical College of Cornell University, New York, New York, USA
| | - Zhe Liu
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA.,Department of Radiology, Weill Medical College of Cornell University, New York, New York, USA
| | - Daniel Margolis
- Department of Radiology, Weill Medical College of Cornell University, New York, New York, USA
| | - Gary M Brittenham
- Department of Pediatrics, Columbia University, New York, New York, USA
| | - Andrea S Kierans
- Department of Radiology, Weill Medical College of Cornell University, New York, New York, USA
| | - Yi Wang
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA.,Department of Radiology, Weill Medical College of Cornell University, New York, New York, USA
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216
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Curtis WA, Fraum TJ, An H, Chen Y, Shetty AS, Fowler KJ. Quantitative MRI of Diffuse Liver Disease: Current Applications and Future Directions. Radiology 2019; 290:23-30. [DOI: 10.1148/radiol.2018172765] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
- William A. Curtis
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, Campus Box 8131, St Louis, MO 63110
| | - Tyler J. Fraum
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, Campus Box 8131, St Louis, MO 63110
| | - Hongyu An
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, Campus Box 8131, St Louis, MO 63110
| | - Yasheng Chen
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, Campus Box 8131, St Louis, MO 63110
| | - Anup S. Shetty
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, Campus Box 8131, St Louis, MO 63110
| | - Kathryn J. Fowler
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, Campus Box 8131, St Louis, MO 63110
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217
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Napel S, Mu W, Jardim‐Perassi BV, Aerts HJWL, Gillies RJ. Quantitative imaging of cancer in the postgenomic era: Radio(geno)mics, deep learning, and habitats. Cancer 2018; 124:4633-4649. [PMID: 30383900 PMCID: PMC6482447 DOI: 10.1002/cncr.31630] [Citation(s) in RCA: 110] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 07/11/2018] [Accepted: 07/17/2018] [Indexed: 11/07/2022]
Abstract
Although cancer often is referred to as "a disease of the genes," it is indisputable that the (epi)genetic properties of individual cancer cells are highly variable, even within the same tumor. Hence, preexisting resistant clones will emerge and proliferate after therapeutic selection that targets sensitive clones. Herein, the authors propose that quantitative image analytics, known as "radiomics," can be used to quantify and characterize this heterogeneity. Virtually every patient with cancer is imaged radiologically. Radiomics is predicated on the beliefs that these images reflect underlying pathophysiologies, and that they can be converted into mineable data for improved diagnosis, prognosis, prediction, and therapy monitoring. In the last decade, the radiomics of cancer has grown from a few laboratories to a worldwide enterprise. During this growth, radiomics has established a convention, wherein a large set of annotated image features (1-2000 features) are extracted from segmented regions of interest and used to build classifier models to separate individual patients into their appropriate class (eg, indolent vs aggressive disease). An extension of this conventional radiomics is the application of "deep learning," wherein convolutional neural networks can be used to detect the most informative regions and features without human intervention. A further extension of radiomics involves automatically segmenting informative subregions ("habitats") within tumors, which can be linked to underlying tumor pathophysiology. The goal of the radiomics enterprise is to provide informed decision support for the practice of precision oncology.
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Affiliation(s)
- Sandy Napel
- Department of RadiologyStanford UniversityStanfordCalifornia
| | - Wei Mu
- Department of Cancer PhysiologyH. Lee Moffitt Cancer CenterTampaFlorida
| | | | - Hugo J. W. L. Aerts
- Dana‐Farber Cancer Institute, Department of Radiology, Brigham and Women’s HospitalHarvard Medical SchoolBostonMassachusetts
| | - Robert J. Gillies
- Department of Cancer PhysiologyH. Lee Moffitt Cancer CenterTampaFlorida
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218
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Han A, Labyed Y, Sy EZ, Boehringer AS, Andre MP, Erdman JW, Loomba R, Sirlin CB, O'Brien WD. Inter-sonographer reproducibility of quantitative ultrasound outcomes and shear wave speed measured in the right lobe of the liver in adults with known or suspected non-alcoholic fatty liver disease. Eur Radiol 2018; 28:4992-5000. [PMID: 29869170 PMCID: PMC7235946 DOI: 10.1007/s00330-018-5541-9] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 04/27/2018] [Accepted: 05/14/2018] [Indexed: 12/17/2022]
Abstract
OBJECTIVES To assess inter-sonographer reproducibility of ultrasound attenuation coefficient (AC), backscatter coefficient (BSC) and shear wave speed (SWS) in adults with known/suspected non-alcoholic fatty liver disease (NAFLD). METHODS The institutional review board approved this HIPAA-compliant prospective study; informed consent was obtained. Participants with known/suspected NAFLD were recruited and underwent same-day liver examinations with a clinical scanner. Each participant was scanned by two of the six trained sonographers. Each sonographer performed multiple data acquisitions in the right liver lobe using a lateral intercostal approach. A data acquisition was a single operator button press that recorded a B-mode image, radio-frequency data, and the SWS value. AC and BSC were calculated from the radio-frequency data using the reference phantom method. SWS was calculated automatically using product software. Intraclass correlation coefficient (ICC) and within-subject coefficient of variation (wCV) were calculated for applicable metrics. RESULTS Sixty-one participants were recruited. Inter-sonographer ICC was 0.86 (95% confidence interval: 0.77-0.92) for AC and 0.87 (0.78-0.92) for log-transformed BSC (logBSC = 10log10BSC) using one acquisition per sonographer. ICC was 0.88 (0.80-0.93) for both AC and logBSC averaging 5 acquisitions. ICC for SWS was 0.57 (0.29-0.74) using one acquisition per sonographer, and 0.84 (0.66-0.93) using 10 acquisitions. The wCV was ~7% for AC, and 19-43% for SWS, depending on number of acquisitions. CONCLUSIONS Hepatic AC, BSC and SWS measures on a clinical scanner have good inter-sonographer reproducibility in adults with known or suspected NAFLD. Multiple acquisitions are required for SWS but not AC or BSC to achieve good inter-sonographer reproducibility. KEY POINTS • AC, BSC and SWS measurements are reproducible in adults with NAFLD. • Inter-sonographer reproducibility of SWS measurement improves with more acquisitions being averaged. • Multiple acquisitions are required for SWS but not AC or BSC.
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Affiliation(s)
- Aiguo Han
- Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 306 North Wright Street, Urbana, IL, 61801, USA
| | - Yassin Labyed
- Siemens Healthineers USA, 22010 South East 51st Street, Issaquah, WA, 98029, USA
| | - Ethan Z Sy
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 9452 Medical Center Drive, La Jolla, CA, 92037, USA
| | - Andrew S Boehringer
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 9452 Medical Center Drive, La Jolla, CA, 92037, USA
| | - Michael P Andre
- Department of Radiology, University of California at San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA
- San Diego VA Healthcare System, San Diego, CA, USA
| | - John W Erdman
- Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, 905 South Goodwin Avenue, Urbana, IL, 61801, USA
| | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology, Department of Medicine, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California at San Diego, 9452 Medical Center Drive, La Jolla, CA, 92037, USA
| | - William D O'Brien
- Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 306 North Wright Street, Urbana, IL, 61801, USA.
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219
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Smith A, Varney E, Zand K, Lewis T, Sirous R, York J, Florez E, Abou Elkassem A, Howard-Claudio CM, Roda M, Parker E, Scortegagna E, Joyner D, Sandlin D, Newsome A, Brewster P, Lirette ST, Griswold M. Precision analysis of a quantitative CT liver surface nodularity score. Abdom Radiol (NY) 2018; 43:3307-3316. [PMID: 29700590 DOI: 10.1007/s00261-018-1617-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
PURPOSE To evaluate precision of a software-based liver surface nodularity (LSN) score derived from CT images. METHODS An anthropomorphic CT phantom was constructed with simulated liver containing smooth and nodular segments at the surface and simulated visceral and subcutaneous fat components. The phantom was scanned multiple times on a single CT scanner with adjustment of image acquisition and reconstruction parameters (N = 34) and on 22 different CT scanners from 4 manufacturers at 12 imaging centers. LSN scores were obtained using a software-based method. Repeatability and reproducibility were evaluated by intraclass correlation (ICC) and coefficient of variation. Using abdominal CT images from 68 patients with various stages of chronic liver disease, inter-observer agreement and test-retest repeatability among 12 readers assessing LSN by software- vs. visual-based scoring methods were evaluated by ICC. RESULTS There was excellent repeatability of LSN scores (ICC:0.79-0.99) using the CT phantom and routine image acquisition and reconstruction parameters (kVp 100-140, mA 200-400, and auto-mA, section thickness 1.25-5.0 mm, field of view 35-50 cm, and smooth or standard kernels). There was excellent reproducibility (smooth ICC: 0.97; 95% CI 0.95, 0.99; CV: 7%; nodular ICC: 0.94; 95% CI 0.89, 0.97; CV: 8%) for LSN scores derived from CT images from 22 different scanners. Inter-observer agreement for the software-based LSN scoring method was excellent (ICC: 0.84; 95% CI 0.79, 0.88; CV: 28%) vs. good for the visual-based method (ICC: 0.61; 95% CI 0.51, 0.69; CV: 43%). Test-retest repeatability for the software-based LSN scoring method was excellent (ICC: 0.82; 95% CI 0.79, 0.84; CV: 12%). CONCLUSION The software-based LSN score is a quantitative CT imaging biomarker with excellent repeatability, reproducibility, inter-observer agreement, and test-retest repeatability.
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Affiliation(s)
- Andrew Smith
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA. .,Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA. .,Department of Radiology, UAB, JTN 452, 619 19th Street South, Birmingham, AL, 35249-6830, USA.
| | - Elliot Varney
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Kevin Zand
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Tara Lewis
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Reza Sirous
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - James York
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Edward Florez
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Asser Abou Elkassem
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA.,Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Manohar Roda
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Ellen Parker
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Eduardo Scortegagna
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - David Joyner
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - David Sandlin
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Ashley Newsome
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Parker Brewster
- Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Seth T Lirette
- Center for Data Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Michael Griswold
- Center for Data Science, University of Mississippi Medical Center, Jackson, MS, USA
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220
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Shukla-Dave A, Obuchowski NA, Chenevert TL, Jambawalikar S, Schwartz LH, Malyarenko D, Huang W, Noworolski SM, Young RJ, Shiroishi MS, Kim H, Coolens C, Laue H, Chung C, Rosen M, Boss M, Jackson EF. Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials. J Magn Reson Imaging 2018; 49:e101-e121. [PMID: 30451345 DOI: 10.1002/jmri.26518] [Citation(s) in RCA: 225] [Impact Index Per Article: 37.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 09/06/2018] [Accepted: 09/06/2018] [Indexed: 12/14/2022] Open
Abstract
Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121.
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Affiliation(s)
- Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Nancy A Obuchowski
- Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Thomas L Chenevert
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Sachin Jambawalikar
- Department of Radiology, Columbia University Irving Medical Center, New York, New York, USA
| | - Lawrence H Schwartz
- Department of Radiology, Columbia University Irving Medical Center, New York, New York, USA
| | - Dariya Malyarenko
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Wei Huang
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Susan M Noworolski
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Robert J Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Mark S Shiroishi
- Division of Neuroradiology, Department of Radiology, University of Southern California, Los Angeles, California, USA
| | - Harrison Kim
- Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Catherine Coolens
- Department of Radiation Oncology, Princess Margaret Cancer Centre, Toronto, Canada
| | | | - Caroline Chung
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas, USA
| | - Mark Rosen
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Michael Boss
- Applied Physics Division, National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Edward F Jackson
- Departments of Medical Physics, Radiology, and Human Oncology, University of Wisconsin School of Medicine, Madison, Wisconsin, USA
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221
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Kim HJ, Cho HJ, Kim B, You MW, Lee JH, Huh J, Kim JK. Accuracy and precision of proton density fat fraction measurement across field strengths and scan intervals: A phantom and human study. J Magn Reson Imaging 2018; 50:305-314. [PMID: 30430684 DOI: 10.1002/jmri.26575] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Revised: 10/27/2018] [Accepted: 10/29/2018] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Complex-based chemical shift imaging-based magnetic resonance imaging (CSE-MRI) is emerging as a preferred method for noninvasively quantifying proton density fat fraction (PDFF), a promising quantitative imaging biomarker (QIB) for longitudinal hepatic steatosis measurement. PURPOSE To determine linearity, bias, repeatability, and reproducibility of the PDFF measurement using CSE-MRI (CSE-PDFF) across scan intervals, MR field strengths, and readers in phantom and nonalcoholic fatty liver disease (NAFLD) patients. STUDY TYPE Institutional Review Board (IRB)-approved prospective. SUBJECTS Fat-water phantom and 20 adult patients. FIELD STRENGTH/SEQUENCE 1.5 T and 3.0 T MR systems and a commercially available CSE-MRI sequence (IDEAL-IQ). ASSESSMENT Two independent readers measured CSE-PDFF of fat-water phantom and NAFLD patients across two field strengths and scan intervals (same-day and 2-week) each and in a combination of both. MR spectroscopy-based PDFF (MRS-PDFF) was used as the reference standard for phantom PDFF. STATISTICAL TESTS Linearity and bias of measurement were evaluated by linear regression analysis and Bland-Altman plots, respectively. Repeatability and reproducibility were assessed by coefficient of variance and repeatability / reproducibility coefficients (RC). The intraclass correlation coefficient was used to validate intra- and interobserver agreements. RESULTS CSE-PDFF showed high linearity and small bias (-0.6-0.4 PDFF%) with 95% limits of agreement within ±2.9 PDFF% across field strengths, 2-week interscan period, and readers in the clinical scans. CSE-PDFF was highly repeatable and reproducible both in phantom and clinical scans, with the largest observed RC across field strengths and 2-week interscan period being 3 PDFF%. DATA CONCLUSION CSE-PDFF is a robust QIB with high linearity, small bias, and excellent repeatability/reproducibility. A change of more than 3 PDFF% across field strengths within 2 weeks of scan interval likely reflects a true change, which is well within the clinically acceptable range. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:305-314.
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Affiliation(s)
- Hye Jin Kim
- Department of Radiology, Ajou University School of Medicine, Ajou University Hospital, Suwon, South Korea
| | - Hyo Jung Cho
- Department of Gastroenterology, Ajou University School of Medicine, Ajou University Hospital, Suwon, South Korea
| | - Bohyun Kim
- Department of Radiology, Ajou University School of Medicine, Ajou University Hospital, Suwon, South Korea
| | - Myung-Won You
- Department of Radiology, Kyung Hee University Hospital, Seoul, South Korea
| | - Jei Hee Lee
- Department of Radiology, Ajou University School of Medicine, Ajou University Hospital, Suwon, South Korea
| | - Jimi Huh
- Department of Radiology, Ajou University School of Medicine, Ajou University Hospital, Suwon, South Korea
| | - Jai Keun Kim
- Department of Radiology, Ajou University School of Medicine, Ajou University Hospital, Suwon, South Korea
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222
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Kubo T. Vendor free basics of radiation dose reduction techniques for CT. Eur J Radiol 2018; 110:14-21. [PMID: 30599851 DOI: 10.1016/j.ejrad.2018.11.002] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 10/19/2018] [Accepted: 11/04/2018] [Indexed: 11/16/2022]
Abstract
Although radiation dose in computed tomography (CT) decreased and CT became safer examinations than before, CT is the most significant source of the medical radiation exposure. Knowledge about available radiation dose reduction methods in CT is essential. Substantial improvement occurred regarding tube current selection (automatic exposure control) and image production method (iterative reconstruction). Optimizing the tube potential selection is expected to contribute to further CT radiation dose reduction. This review article summarizes the principles of radiation dose reduction in CT, principal methods of radiation dose reduction, auxiliary measures of radiation dose saving and recent issues of low dose CT.
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Affiliation(s)
- Takeshi Kubo
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan.
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223
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224
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Bae H, Tsuchiya J, Okamoto T, Ito I, Sonehara Y, Nagahama F, Kubota K, Tateishi U. Standardization of [F-18]FDG PET/CT for response evaluation by the Radiologic Society of North America-Quantitative Imaging Biomarker Alliance (RSNA-QIBA) profile: preliminary results from the Japan-QIBA (J-QIBA) activities for Asian international multicenter phase II trial. Jpn J Radiol 2018; 36:686-690. [PMID: 30251115 DOI: 10.1007/s11604-018-0780-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Accepted: 09/19/2018] [Indexed: 01/07/2023]
Abstract
PURPOSE In an Asian international multicenter phase II trial conducted in patients with peripheral T-cell lymphoma (PTCL), [F-18]FDG-PET/CT was used for evaluation of the therapeutic response. Standardization of the PET/CT scanners was necessary before patient enrollment. We therefore standardized the scanners by phantom tests based on the profile approved by the Quantitative Imaging Biomarkers Alliance (QIBA) of Radiological Society of North America (RSNA). MATERIALS AND METHODS The tests were conducted on 12 scanners in 12 facilities in compliance with the QIBA Profile and used National Electrical Manufacturers Association (NEMA) International Electrotechnical Commission (IEC) body phantoms. We measured three parameters (standardized uptake value [SUV], resolution and noise) and adjusted the imaging parameter values. The indexes recommended in the Japanese Society of Nuclear Medicine (JSNM) guideline were also evaluated. RESULTS In a total of 12 facilities, 6 facilities required no change in imaging conditions and 6 facilities required changes in imaging parameters. After revision, the three measurements (SUV, resolution and noise) met QIBA criteria at all sites, but 10 of the 12 scanners did not meet JSNM criteria. CONCLUSION We standardized imaging conditions using phantoms as required in the RSNA-QIBA profile for response evaluation by [F-18]FDG PET/CT images in a multicenter study.
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Affiliation(s)
- Hyeyeol Bae
- Department of Diagnostic Radiology and Nuclear Medicine, Tokyo Medical and Dental University, Tokyo, Japan
| | - Junichi Tsuchiya
- Department of Diagnostic Radiology and Nuclear Medicine, Tokyo Medical and Dental University, Tokyo, Japan
| | | | - Ikuko Ito
- Imaging Service Department, MICRON Inc, Tokyo, Japan
| | | | | | - Kazunori Kubota
- Department of Diagnostic Radiology and Nuclear Medicine, Tokyo Medical and Dental University, Tokyo, Japan
| | - Ukihide Tateishi
- Department of Diagnostic Radiology and Nuclear Medicine, Tokyo Medical and Dental University, Tokyo, Japan. .,Japan-Quantitative Imaging Biomarker Alliance (J-QIBA), Japan Radiologic Society, Tokyo, Japan.
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225
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MacKay JW, Low SBL, Smith TO, Toms AP, McCaskie AW, Gilbert FJ. Systematic review and meta-analysis of the reliability and discriminative validity of cartilage compositional MRI in knee osteoarthritis. Osteoarthritis Cartilage 2018; 26:1140-1152. [PMID: 29550400 DOI: 10.1016/j.joca.2017.11.018] [Citation(s) in RCA: 70] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Revised: 10/16/2017] [Accepted: 11/14/2017] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To assess reliability and discriminative validity of cartilage compositional magnetic resonance imaging (MRI) in knee osteoarthritis (OA). DESIGN The study was carried out per PRISMA recommendations. We searched MEDLINE and EMBASE (1974 - present) for eligible studies. We performed qualitative synthesis of reliability data. Where data from at least two discrimination studies were available, we estimated pooled standardized mean difference (SMD) between subjects with and without OA. Discrimination analyses compared controls and subjects with mild OA (Kellgren-Lawrence (KL) grade 1-2), severe OA (KL grade 3-4) and OA not otherwise specified (NOS) where not possible to stratify. We assessed quality of the evidence using Quality Appraisal of Diagnostic Reliability (QAREL) and Quality Assessment of Diagnostic Accuracy (QUADAS-2) tools. RESULTS Fifty-eight studies were included in the reliability analysis and 26 studies were included in the discrimination analysis, with data from a total of 2,007 knees. Intra-observer, inter-observer and test-retest reliability of compositional techniques were excellent with most intraclass correlation coefficients >0.8 and coefficients of variation <10%. T1rho and T2 relaxometry were significant discriminators between subjects with mild OA and controls, and between subjects with OA (NOS) and controls (P < 0.001). T1rho showed best discrimination for mild OA (SMD [95% CI] = 0.73 [0.40 to 1.06], P < 0.001) and OA (NOS) (0.60 [0.41 to 0.80], P < 0.001). Quality of evidence was moderate for both parts of the review. CONCLUSIONS Cartilage compositional MRI techniques are reliable and, in the case of T1rho and T2 relaxometry, can discriminate between subjects with OA and controls.
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Affiliation(s)
- J W MacKay
- Department of Radiology, University of Cambridge, Cambridge, UK.
| | - S B L Low
- Department of Radiology, Norfolk & Norwich University Hospital, Norwich, UK.
| | - T O Smith
- School of Health Sciences, University of East Anglia, Norwich, UK.
| | - A P Toms
- Department of Radiology, Norfolk & Norwich University Hospital, Norwich, UK.
| | - A W McCaskie
- Division of Trauma & Orthopaedics, Department of Surgery, University of Cambridge, Cambridge UK.
| | - F J Gilbert
- Department of Radiology, University of Cambridge, Cambridge, UK.
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Selby NM, Blankestijn PJ, Boor P, Combe C, Eckardt KU, Eikefjord E, Garcia-Fernandez N, Golay X, Gordon I, Grenier N, Hockings PD, Jensen JD, Joles JA, Kalra PA, Krämer BK, Mark PB, Mendichovszky IA, Nikolic O, Odudu A, Ong ACM, Ortiz A, Pruijm M, Remuzzi G, Rørvik J, de Seigneux S, Simms RJ, Slatinska J, Summers P, Taal MW, Thoeny HC, Vallée JP, Wolf M, Caroli A, Sourbron S. Magnetic resonance imaging biomarkers for chronic kidney disease: a position paper from the European Cooperation in Science and Technology Action PARENCHIMA. Nephrol Dial Transplant 2018; 33:ii4-ii14. [PMID: 30137584 PMCID: PMC6106645 DOI: 10.1093/ndt/gfy152] [Citation(s) in RCA: 90] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Indexed: 12/13/2022] Open
Abstract
Functional renal magnetic resonance imaging (MRI) has seen a number of recent advances, and techniques are now available that can generate quantitative imaging biomarkers with the potential to improve the management of kidney disease. Such biomarkers are sensitive to changes in renal blood flow, tissue perfusion, oxygenation and microstructure (including inflammation and fibrosis), processes that are important in a range of renal diseases including chronic kidney disease. However, several challenges remain to move these techniques towards clinical adoption, from technical validation through biological and clinical validation, to demonstration of cost-effectiveness and regulatory qualification. To address these challenges, the European Cooperation in Science and Technology Action PARENCHIMA was initiated in early 2017. PARENCHIMA is a multidisciplinary pan-European network with an overarching aim of eliminating the main barriers to the broader evaluation, commercial exploitation and clinical use of renal MRI biomarkers. This position paper lays out PARENCHIMA's vision on key clinical questions that MRI must address to become more widely used in patients with kidney disease, first within research settings and ultimately in clinical practice. We then present a series of practical recommendations to accelerate the study and translation of these techniques.
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Affiliation(s)
- Nicholas M Selby
- Centre for Kidney Research and Innovation, University of Nottingham, UK
| | - Peter J Blankestijn
- Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Peter Boor
- Institute of Pathology and Department of Nephrology, RWTH University, Aachen, Germany
| | - Christian Combe
- Service de Néphrologie Transplantation Dialyse Aphérèse, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité—Universitätsmedizin Berlin, Berlin, Germany
| | - Eli Eikefjord
- Department of Health and Functioning, Western Norway University of Applied Sciences, Norway
| | | | - Xavier Golay
- Institute of Neurology, University College London, Queen Square, London, UK
| | - Isky Gordon
- Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Nicolas Grenier
- Service d'Imagerie Diagnostique et Interventionnelle de l'Adulte, Centre Hospitalier Universitaire de Bordeaux Place Amelie Raba-Leon, Bordeaux, France
| | | | - Jens D Jensen
- Departments of Renal and Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Jaap A Joles
- Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Philip A Kalra
- Department of Renal Medicine, Salford Royal Hospital and Division of Cardiovascular Sciences, University of Manchester, Manchester, UK
| | - Bernhard K Krämer
- Vth Department of Medicine, University Medical Center Mannheim, Medical Faculty Mannheim of the University Heidelberg, Mannheim, Germany
| | - Patrick B Mark
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Iosif A Mendichovszky
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge Biomedical Campus, Cambridge, UK
| | - Olivera Nikolic
- Faculty of Medicine,University of Novi Sad, Center of Radiology, Clinical Centre of Vojvodina, Serbia
| | - Aghogho Odudu
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Albert C M Ong
- Academic Nephrology Unit, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield Medical School, Sheffield, UK
| | - Alberto Ortiz
- Nephrology and Hypertension, IIS-Fundacion Jimenez Diaz UAM, Madrid, Spain
| | - Menno Pruijm
- Service of Nephrology and Hypertension, Department of Medicine, University Hospital of Lausanne (CHUV), Lausanne, Switzerland
| | - Giuseppe Remuzzi
- IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Bergamo, Italy
| | - Jarle Rørvik
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Sophie de Seigneux
- Service of Nephrology, Department of Medicine Specialties, University Hospital of Geneva, Geneva, Switzerland
| | - Roslyn J Simms
- Academic Nephrology Unit, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield Medical School, Sheffield, UK
| | - Janka Slatinska
- Department of Nephrology, Transplant Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Paul Summers
- Department of Medical Imaging and Radiation Sciences, Radiology Division, European Institute of Oncology (IEO), Milan, Italy
- QMRI Tech iSrl, Piazza dei Martiri Pennesi 20, Pescara, Italy
| | - Maarten W Taal
- Centre for Kidney Research and Innovation, University of Nottingham, UK
| | - Harriet C Thoeny
- University of Bern, Inselspital, Bern, Switzerland
- HFR Fribourg, Hôpital Cantonal, Fribourg, Switzerland
| | - Jean-Paul Vallée
- Radiology Department, Geneva University Hospital and University of Geneva, Geneva, Switzerland
| | - Marcos Wolf
- Center for Medical Physics and Biomedical Engineering, MR-Centre of Excellence, Medical University of Vienna, Vienna, Austria
| | - Anna Caroli
- IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Bergamo, Italy
| | - Steven Sourbron
- Leeds Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
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227
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Wyatt CR, Smith TB, Sammi MK, Rooney WD, Guimaraes AR. Multi-parametric T 2 * magnetic resonance fingerprinting using variable echo times. NMR IN BIOMEDICINE 2018; 31:e3951. [PMID: 30011109 DOI: 10.1002/nbm.3951] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Revised: 03/29/2018] [Accepted: 05/01/2018] [Indexed: 06/08/2023]
Abstract
The use of quantitative imaging biomarkers in the imaging of various disease states, including cancer and neurodegenerative disease, has increased in recent years. T1 , T2 , and T2 * relaxation time constants have been shown to be affected by tissue structure or contrast infusion. Acquiring these biomarkers simultaneously in a multi-parametric acquisition could provide more robust detection of tissue changes in various disease states including neurodegeneration and cancer. Traditional magnetic resonance fingerprinting (MRF) has been shown to provide quick, quantitative mapping of T1 and T2 relaxation time constants. In this study, T2 * relaxation is added to the MRF framework using variable echo times (TE). To demonstrate the feasibility of the method and compare incremental and golden angle spiral rotations, simulated phantom data was fit using the proposed method. Additionally, T1 /T2 /T2 */δf MRF as well as conventional T1 , T2 , and T2 * acquisitions were acquired in agar phantoms and the brains of three healthy volunteers. Golden angle spiral rotation was found to reduce inaccuracy resulting from off resonance effects. Strong correlations were found between conventional and MRF values in the T1 , T2 , and T2 * relaxation time constants of the agar phantoms and healthy volunteers. In this study, T2 * relaxation has been incorporated into the MRF framework by using variable echo times, while still fitting for T1 and T2 relaxation time constants. In addition to fitting these relaxation time constants, a novel method for fitting and correcting off resonance effects has been developed.
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Affiliation(s)
- Cory R Wyatt
- Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR, USA
- Department of Diagnostic Radiology, Oregon Health & Sciences University, Portland, OR, USA
| | - Travis B Smith
- Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR, USA
- Casey Eye Institute, Oregon Health & Sciences University, Portland, OR, USA
| | - Manoj K Sammi
- Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR, USA
| | - William D Rooney
- Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR, USA
| | - Alexander R Guimaraes
- Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR, USA
- Department of Diagnostic Radiology, Oregon Health & Sciences University, Portland, OR, USA
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228
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Bray TJP, Chouhan MD, Punwani S, Bainbridge A, Hall-Craggs MA. Fat fraction mapping using magnetic resonance imaging: insight into pathophysiology. Br J Radiol 2018; 91:20170344. [PMID: 28936896 PMCID: PMC6223159 DOI: 10.1259/bjr.20170344] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 07/18/2017] [Accepted: 09/06/2017] [Indexed: 02/06/2023] Open
Abstract
Adipose cells have traditionally been viewed as a simple, passive energy storage depot for triglycerides. However, in recent years it has become clear that adipose cells are highly physiologically active and have a multitude of endocrine, metabolic, haematological and immune functions. Changes in the number or size of adipose cells may be directly implicated in disease (e.g. in the metabolic syndrome), but may also be linked to other pathological processes such as inflammation, malignant infiltration or infarction. MRI is ideally suited to the quantification of fat, since most of the acquired signal comes from water and fat protons. Fat fraction (FF, the proportion of the acquired signal derived from fat protons) has, therefore, emerged as an objective, image-based biomarker of disease. Methods for FF quantification are becoming increasingly available in both research and clinical settings, but these methods vary depending on the scanner, manufacturer, imaging sequence and reconstruction software being used. Careful selection of the imaging method-and correct interpretation-can improve the accuracy of FF measurements, minimize potential confounding factors and maximize clinical utility. Here, we review methods for fat quantification and their strengths and weaknesses, before considering how they can be tailored to specific applications, particularly in the gastrointestinal and musculoskeletal systems. FF quantification is becoming established as a clinical and research tool, and understanding the underlying principles will be helpful to both imaging scientists and clinicians.
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Affiliation(s)
- Timothy JP Bray
- Centre for
Medical Imaging, University College London,University College London,
London, UK
| | - Manil D Chouhan
- Centre for
Medical Imaging, University College London,University College London,
London, UK
| | - Shonit Punwani
- Centre for
Medical Imaging, University College London,University College London,
London, UK
| | - Alan Bainbridge
- Department
of Medical Physics, University College London
Hospitals,University
College London Hospitals, London,
UK
| | - Margaret A Hall-Craggs
- Centre for
Medical Imaging, University College London,University College London,
London, UK
- Department
of Medical Physics, University College London
Hospitals,University
College London Hospitals, London,
UK
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229
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Lee Y, Callaghan MF, Acosta-Cabronero J, Lutti A, Nagy Z. Establishing intra- and inter-vendor reproducibility of T1
relaxation time measurements with 3T MRI. Magn Reson Med 2018; 81:454-465. [DOI: 10.1002/mrm.27421] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 05/28/2018] [Accepted: 06/04/2018] [Indexed: 11/11/2022]
Affiliation(s)
- Yoojin Lee
- Laboratory for Social and Neural Systems Research; University of Zurich; Zürich Switzerland
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging; UCL Institute of Neurology; London United Kingdom
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging; UCL Institute of Neurology; London United Kingdom
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience,; Lausanne University Hospital and University of Lausanne; Lausanne Switzerland
| | - Zoltan Nagy
- Laboratory for Social and Neural Systems Research; University of Zurich; Zürich Switzerland
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230
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Affiliation(s)
- Hanzhang Lu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, 600N. Wolfe Street, Park 322, Baltimore, MD, 21287, United States.
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231
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Tsutsui Y, Daisaki H, Akamatsu G, Umeda T, Ogawa M, Kajiwara H, Kawase S, Sakurai M, Nishida H, Magota K, Mori K, Sasaki M. Multicentre analysis of PET SUV using vendor-neutral software: the Japanese Harmonization Technology (J-Hart) study. EJNMMI Res 2018; 8:83. [PMID: 30128776 PMCID: PMC6102169 DOI: 10.1186/s13550-018-0438-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 08/09/2018] [Indexed: 01/16/2023] Open
Abstract
Background Recent developments in hardware and software for PET technologies have resulted in wide variations in basic performance. Multicentre studies require a standard imaging protocol and SUV harmonization to reduce inter- and intra-scanner variability in the SUV. The Japanese standardised uptake value (SUV) Harmonization Technology (J-Hart) study aimed to determine the applicability of vendor-neutral software on the SUV derived from positron emission tomography (PET) images. The effects of SUV harmonization were evaluated based on the reproducibility of several scanners and the repeatability of an individual scanner. Images were acquired from 12 PET scanners at nine institutions. PET images were acquired over a period of 30 min from a National Electrical Manufacturers Association (NEMA) International Electrotechnical Commission (IEC) body phantom containing six spheres of different diameters and an 18F solution with a background activity of 2.65 kBq/mL and a sphere-to-background ratio of 4. The images were reconstructed to determine parameters for harmonization and to evaluate reproducibility. PET images with 2-min acquisition × 15 contiguous frames were reconstructed to evaluate repeatability. Various Gaussian filters (GFs) with full-width at half maximum (FWHM) values ranging from 1 to 15 mm in 1-mm increments were also applied using vendor-neutral software. The SUVmax of spheres was compared with the reference range proposed by the Japanese Society of Nuclear Medicine (JSNM) and the digital reference object (DRO) of the NEMA phantom. The coefficient of variation (CV) of the SUVmax determined using 12 PET scanners (CVrepro) was measured to evaluate reproducibility. The CV of the SUVmax determined from 15 frames (CVrepeat) per PET scanner was measured to determine repeatability. Results Three PET scanners did not require an additional GF for harmonization, whereas the other nine required additional FWHM values of GF ranging from 5 to 9 mm. The pre- and post-harmonization CVrepro of six spheres were (means ± SD) 9.45% ± 4.69% (range, 3.83–15.3%) and 6.05% ± 3.61% (range, 2.30–10.7%), respectively. Harmonization significantly improved reproducibility of PET SUVmax (P = 0.0055). The pre- and post-harmonization CVrepeat of nine scanners were (means ± SD) 6.59% ± 1.29% (range, 5.00–8.98%) and 4.88% ± 1.64% (range, 2.65–6.72%), respectively. Harmonization also significantly improved the repeatability of PET SUVmax (P < 0.0001). Conclusions Harmonizing SUV using vendor-neutral software produced SUVmax for 12 scanners that fell within the JSNM reference range of a NEMA body phantom and improved SUVmax reproducibility and repeatability.
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Affiliation(s)
- Yuji Tsutsui
- Division of Radiology, Department of Medical Technology, Kyushu University Hospital, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Hiromitsu Daisaki
- Gunma Prefectural College of Health Sciences, 323-1 Kamioki-machi, Maebashi-shi, 371-0052, Japan
| | - Go Akamatsu
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, 4-9-1 Anagawa, Inage-ku, Chiba-shi, 263-8555, Japan.,Department of Molecular Imaging, Institute of Biomedical Research and Innovation, 2-2, Minatojima Minamimachi, Chuo-ku, Tokyo, 28 650-0047, Japan
| | - Takuro Umeda
- Department of Nuclear Medicine, Cancer Institute Hospital of Japanese Foundation for Cancer Research, 3-8-31 Ariake, Koto-ku, Tokyo, 135-8550, Japan
| | - Matsuyoshi Ogawa
- Department of Radiology, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama, 236-0004, Japan
| | - Hironori Kajiwara
- Department of Radiology, Center Hospital of National Center for Global Health and Medicine, 1-21-1 Toyama Shinjuku-ku, Tokyo, 162-8655, Japan
| | - Shigeto Kawase
- Department of Radiology, Kyoto University Hospital, 54 Kawaharacho, Syogoin, Sakyo-ku, Kyoto City, 606-8507, Japan
| | - Minoru Sakurai
- Clinical Imaging Center for Healthcare, Nippon Medical School, 1-12-15 Sendagi, Bunkyo-ku, Tokyo, 113-0022, Japan
| | - Hiroyuki Nishida
- Department of Molecular Imaging, Institute of Biomedical Research and Innovation, 2-2, Minatojima Minamimachi, Chuo-ku, Tokyo, 28 650-0047, Japan
| | - Keiichi Magota
- Division of Medical Imaging and Technology, Hokkaido University Hospital, Kita 14-jo Nishi 5-chome, Kita-ku, Sapporo-shi, Hokkaido, 060-8648, Japan
| | - Kazuaki Mori
- Department of Radiology, Toranomon Hospital, 2-2-2 Toranomon, Minato-ku, Tokyo, 105-8470, Japan
| | - Masayuki Sasaki
- Department of Health Science, Faculty of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan.
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232
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Han A, Andre MP, Deiranieh L, Housman E, Erdman JW, Loomba R, Sirlin CB, O’Brien WD. Repeatability and Reproducibility of the Ultrasonic Attenuation Coefficient and Backscatter Coefficient Measured in the Right Lobe of the Liver in Adults With Known or Suspected Nonalcoholic Fatty Liver Disease. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2018; 37:1913-1927. [PMID: 29359454 PMCID: PMC6056350 DOI: 10.1002/jum.14537] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Revised: 08/23/2017] [Accepted: 10/22/2017] [Indexed: 05/11/2023]
Abstract
OBJECTIVES To assess the repeatability and reproducibility of the ultrasonic attenuation coefficient (AC) and backscatter coefficient (BSC) measured in the livers of adults with known or suspected nonalcoholic fatty liver disease (NAFLD). METHODS The Institutional Review Board approved this Health Insurance Portability and Accountability Act-compliant prospective study; informed consent was obtained. Forty-one research participants with known or suspected NAFLD were recruited and underwent same-day ultrasound examinations of the right liver lobe with a clinical scanner by a clinical sonographer. Each participant underwent 2 scanning trials, with participant repositioning between trials. Two transducers were used in each trial. For each transducer, machine settings were optimized by the sonographer but then kept constant while 3 data acquisitions were obtained from the liver without participant repositioning and then from an external calibrated phantom. Raw RF echo data were recorded. The AC and BSC were measured within 2.6 to 3.0 MHz from a user-defined hepatic field of interest from each acquisition. The repeatability and reproducibility were analyzed by random-effects models. RESULTS The mean AC and log-transformed BSC (logBSC) were 0.94 dB/cm-MHz and -27.0 dB, respectively. Intraclass correlation coefficients were 0.88 to 0.94 for the AC and 0.87 to 0.95 for the logBSC acquired without participant repositioning. For between-trial repeated scans with participant repositioning, the intraclass correlation coefficients were 0.80 to 0.84 for the AC and 0.69 to 0.82 for the logBSC after averaging results from 3 within-trial images. The variability introduced by the transducer was less than the repeatability error. CONCLUSIONS Hepatic AC and BSC measures using a reference phantom technique on a clinical scanner are repeatable and reproducible between transducers in adults with known or suspected NAFLD.
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Affiliation(s)
- Aiguo Han
- Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 405 North Mathews Avenue, Urbana, IL 61801
| | - Michael P. Andre
- Department of Radiology, University of California, San Diego, 9500 Gilman Dr., San Diego, CA 92093, and the San Diego VA Healthcare System, San Diego
| | - Lisa Deiranieh
- Department of Radiology, University of California, San Diego, 9500 Gilman Dr., San Diego, CA 92093, and the San Diego VA Healthcare System, San Diego
| | - Elise Housman
- Department of Radiology, University of California, San Diego, 9500 Gilman Dr., San Diego, CA 92093, and the San Diego VA Healthcare System, San Diego
| | - John W. Erdman
- Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, 905 South Goodwin Avenue, Urbana, IL 61801
| | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, 9452 Medical Center Drive, La Jolla, CA 92037
| | - William D. O’Brien
- Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 405 North Mathews Avenue, Urbana, IL 61801
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233
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Armato SG, Nowak AK. Revised Modified Response Evaluation Criteria in Solid Tumors for Assessment of Response in Malignant Pleural Mesothelioma (Version 1.1). J Thorac Oncol 2018; 13:1012-1021. [DOI: 10.1016/j.jtho.2018.04.034] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Revised: 03/20/2018] [Accepted: 04/04/2018] [Indexed: 12/20/2022]
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234
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Duval T, Smith V, Stikov N, Klawiter EC, Cohen-Adad J. Scan-rescan of axcaliber, macromolecular tissue volume, and g-ratio in the spinal cord. Magn Reson Med 2018; 79:2759-2765. [PMID: 28994487 PMCID: PMC5821542 DOI: 10.1002/mrm.26945] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Revised: 09/01/2017] [Accepted: 09/03/2017] [Indexed: 01/25/2023]
Abstract
PURPOSE Recent MRI techniques have been introduced that can extract microstructural information in the white matter, such as the density or macromolecular content. Translating quantitative MRI to the clinic raises many challenges in terms of acquisition strategy, modeling of the MRI signal, artifact corrections, and metric extraction (template registration and partial volume effects). In this work, we investigated the scan-rescan repeatability of several quantitative MRI techniques in the human spinal cord. METHODS AxCaliber metrics, macromolecular tissue volume, and the fiber g-ratio were estimated in the spinal cord of eight healthy subjects, scanned and rescanned the same day in two different sessions. RESULTS Scan-rescan repeatability deviation was 3% for all metrics, in average in the white matter of all subjects. Intraclass correlation coefficient was up to 0.9. A three-way analysis of variance showed significant effects of white matter pathway, laterality, and subject. CONCLUSION The present study suggests that quantitative MRI gives stable measurements of white matter microstructure in the spinal cord of healthy subjects. Our findings remain to be evaluated in diseased populations. Magn Reson Med 79:2759-2765, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Tanguy Duval
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Victoria Smith
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Nikola Stikov
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Montreal Heart Institute, Montreal, QC, Canada
| | - Eric C. Klawiter
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montréal, QC, Canada
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235
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Dinh AH, Melodelima C, Souchon R, Moldovan PC, Bratan F, Pagnoux G, Mège-Lechevallier F, Ruffion A, Crouzet S, Colombel M, Rouvière O. Characterization of Prostate Cancer with Gleason Score of at Least 7 by Using Quantitative Multiparametric MR Imaging: Validation of a Computer-aided Diagnosis System in Patients Referred for Prostate Biopsy. Radiology 2018; 287:525-533. [DOI: 10.1148/radiol.2017171265] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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236
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Storelli L, Rocca MA, Pagani E, Van Hecke W, Horsfield MA, De Stefano N, Rovira A, Sastre-Garriga J, Palace J, Sima D, Smeets D, Filippi M. Measurement of Whole-Brain and Gray Matter Atrophy in Multiple Sclerosis: Assessment with MR Imaging. Radiology 2018; 288:554-564. [PMID: 29714673 DOI: 10.1148/radiol.2018172468] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Purpose To compare available methods for whole-brain and gray matter (GM) atrophy estimation in multiple sclerosis (MS) in terms of repeatability (same magnetic resonance [MR] imaging unit) and reproducibility (different system/field strength) for their potential clinical applications. Materials and Methods The softwares ANTs-v1.9, CIVET-v2.1, FSL-SIENAX/SIENA-5.0.1, Icometrix-MSmetrix-1.7, and SPM-v12 were compared. This retrospective study, performed between March 2015 and March 2017, collected data from (a) eight simulated MR images and longitudinal data (2 weeks) from 10 healthy control subjects to assess the cross-sectional and longitudinal accuracy of atrophy measures, (b) test-retest MR images in 29 patients with MS acquired within the same day at different imaging unit field strengths/manufacturers to evaluate precision, and (c) longitudinal data (1 year) in 24 patients with MS for the agreement between methods. Tissue segmentation, image registration, and white matter (WM) lesion filling were also evaluated. Multiple paired t tests were used for comparisons. Results High values of accuracy (0.87-0.97) for whole-brain and GM volumes were found, with the lowest values for MSmetrix. ANTs showed the lowest mean error (0.02%) for whole-brain atrophy in healthy control subjects, with a coefficient of variation of 0.5%. SPM showed the smallest mean error (0.07%) and coefficient of variation (0.08%) for GM atrophy. Globally, good repeatability (P > .05) but poor reproducibility (P < .05) were found for all methods. WM lesion filling technique mainly affected ANTs, MSmetrix, and SPM results (P < .05). Conclusion From this comparison, it would be possible to select a software for atrophy measurement, depending on the requirements of the application (research center, clinical trial) and its goal (accuracy and repeatability or reproducibility). An improved reproducibility is required for clinical application. © RSNA, 2018 Online supplemental material is available for this article.
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Affiliation(s)
- Loredana Storelli
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | - Maria A Rocca
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | - Wim Van Hecke
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | - Mark A Horsfield
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | - Nicola De Stefano
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | - Alex Rovira
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | - Jaume Sastre-Garriga
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | - Jacqueline Palace
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | - Diana Sima
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | - Dirk Smeets
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | - Massimo Filippi
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
| | -
- From the Neuroimaging Research Unit (L.S., M.A.R., E.P., M.F.) and Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience (M.A.R., M.F.), San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina 60, 20132 Milan, Italy; Department of Research and Development, Icometrix, Leuven, Belgium (W.V.H., D. Sima, D. Smeets); Xinapse Systems, Colchester, England (M.A.H.); Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy (N.D.S.); Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain (A.R.); Unit of Clinical Neuroimmunology, CEM-Cat, Hospital Universitari Vall d'Hebron, Barcelona, Spain (J.S.G.); and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England (J.P.)
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Andronesi OC, Arrillaga-Romany IC, Ly KI, Bogner W, Ratai EM, Reitz K, Iafrate AJ, Dietrich J, Gerstner ER, Chi AS, Rosen BR, Wen PY, Cahill DP, Batchelor TT. Pharmacodynamics of mutant-IDH1 inhibitors in glioma patients probed by in vivo 3D MRS imaging of 2-hydroxyglutarate. Nat Commun 2018; 9:1474. [PMID: 29662077 PMCID: PMC5902553 DOI: 10.1038/s41467-018-03905-6] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2017] [Accepted: 03/21/2018] [Indexed: 12/27/2022] Open
Abstract
Inhibitors of the mutant isocitrate dehydrogenase 1 (IDH1) entered recently in clinical trials for glioma treatment. Mutant IDH1 produces high levels of 2-hydroxyglurate (2HG), thought to initiate oncogenesis through epigenetic modifications of gene expression. In this study, we show the initial evidence of the pharmacodynamics of a new mutant IDH1 inhibitor in glioma patients, using non-invasive 3D MR spectroscopic imaging of 2HG. Our results from a Phase 1 clinical trial indicate a rapid decrease of 2HG levels by 70% (CI 13%, P = 0.019) after 1 week of treatment. Importantly, inhibition of mutant IDH1 may lead to the reprogramming of tumor metabolism, suggested by simultaneous changes in glutathione, glutamine, glutamate, and lactate. An inverse correlation between metabolic changes and diffusion MRI indicates an effect on the tumor-cell density. We demonstrate a feasible radiopharmacodynamics approach to support the rapid clinical translation of rationally designed drugs targeting IDH1/2 mutations for personalized and precision medicine of glioma patients.
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Affiliation(s)
- Ovidiu C Andronesi
- Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, 02129, USA.
| | - Isabel C Arrillaga-Romany
- Department of Neurology, Massachusetts General Hospital, Stephen E. and Catherine Pappas Center for Neuro-Oncology, Division of Hematology/Oncology, Harvard Medical School, Boston, MA, 02114, USA
| | - K Ina Ly
- Department of Neurology, Massachusetts General Hospital, Stephen E. and Catherine Pappas Center for Neuro-Oncology, Division of Hematology/Oncology, Harvard Medical School, Boston, MA, 02114, USA
| | - Wolfgang Bogner
- Department of Biomedical Imaging and Image-guided Therapy, High Field MR Centre, Medical University of Vienna, Vienna, 1090, Austria
| | - Eva M Ratai
- Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, 02129, USA
| | - Kara Reitz
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - A John Iafrate
- Department of Pathology, Massachusetts General Hospital, Center for Integrated Diagnostics, Harvard Medical School, Boston, MA, 02114, USA
| | - Jorg Dietrich
- Department of Neurology, Massachusetts General Hospital, Stephen E. and Catherine Pappas Center for Neuro-Oncology, Division of Hematology/Oncology, Harvard Medical School, Boston, MA, 02114, USA
| | - Elizabeth R Gerstner
- Department of Neurology, Massachusetts General Hospital, Stephen E. and Catherine Pappas Center for Neuro-Oncology, Division of Hematology/Oncology, Harvard Medical School, Boston, MA, 02114, USA
| | - Andrew S Chi
- Brain Tumor Center, Laura and Isaac Perlmutter Cancer Center, New York University Langone Medical Center and School of Medicine, New York, NY, 10016, USA
| | - Bruce R Rosen
- Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, 02129, USA
| | - Patrick Y Wen
- Dana-Farber Cancer Institute, Boston, MA, 02284, USA
| | - Daniel P Cahill
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Tracy T Batchelor
- Department of Neurology, Massachusetts General Hospital, Stephen E. and Catherine Pappas Center for Neuro-Oncology, Division of Hematology/Oncology, Harvard Medical School, Boston, MA, 02114, USA
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Töger J, Arvidsson PM, Bock J, Kanski M, Pedrizzetti G, Carlsson M, Arheden H, Heiberg E. Hemodynamic forces in the left and right ventricles of the human heart using 4D flow magnetic resonance imaging: Phantom validation, reproducibility, sensitivity to respiratory gating and free analysis software. PLoS One 2018; 13:e0195597. [PMID: 29621344 PMCID: PMC5886587 DOI: 10.1371/journal.pone.0195597] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Accepted: 03/26/2018] [Indexed: 01/17/2023] Open
Abstract
Purpose To investigate the accuracy, reproducibility and sensitivity to respiratory gating, field strength and ventricle segmentation of hemodynamic force quantification in the left and right ventricles of the heart (LV and RV) using 4D-flow magnetic resonance imaging (MRI), and to provide free hemodynamic force analysis software. Materials and methods A pulsatile flow phantom was imaged using 4D flow MRI and laser-based particle image velocimetry (PIV). Cardiac 4D flow MRI was performed in healthy volunteers at 1.5T (n = 23). Reproducibility was investigated using MR scanners from two different vendors on the same day (n = 8). Subsets of volunteers were also imaged without respiratory gating (n = 17), at 3T on the same day (n = 6), and 1–12 days later on the same scanner (n = 9, median 6 days). Agreement was measured using the intraclass correlation coefficient (ICC). Results Phantom validation showed good accuracy for both scanners (Scanner 1: bias -14±9%, y = 0.82x+0.08, R2 = 0.96, Scanner 2: bias -12±8%, y = 0.99x-0.08, R2 = 1.00). Force reproducibility was strong in the LV (0.09±0.07 vs 0.09±0.07 N, bias 0.00±0.04 N, ICC = 0.87) and RV (0.09±0.06 vs 0.09±0.05 N, bias 0.00±0.03, ICC = 0.83). Strong to very strong agreement was found for scans with and without respiratory gating (LV/RV: ICC = 0.94/0.95), scans on different days (ICC = 0.92/0.87), and 1.5T and 3T scans (ICC = 0.93/0.94). Conclusion Software for quantification of hemodynamic forces in 4D-flow MRI was developed, and results show high accuracy and strong to very strong reproducibility for both the LV and RV, supporting its use for research and clinical investigations. The software including source code is released freely for research.
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Affiliation(s)
- Johannes Töger
- Lund University, Skane University Hospital, Department of Clinical Sciences Lund, Clinical Physiology, Lund, Sweden
| | - Per M. Arvidsson
- Lund University, Skane University Hospital, Department of Clinical Sciences Lund, Clinical Physiology, Lund, Sweden
| | - Jelena Bock
- Lund University, Skane University Hospital, Department of Clinical Sciences Lund, Clinical Physiology, Lund, Sweden
| | - Mikael Kanski
- Lund University, Skane University Hospital, Department of Clinical Sciences Lund, Clinical Physiology, Lund, Sweden
| | - Gianni Pedrizzetti
- Department of Engineering and Architecture, University of Trieste, Trieste, Italy
| | - Marcus Carlsson
- Lund University, Skane University Hospital, Department of Clinical Sciences Lund, Clinical Physiology, Lund, Sweden
| | - Håkan Arheden
- Lund University, Skane University Hospital, Department of Clinical Sciences Lund, Clinical Physiology, Lund, Sweden
| | - Einar Heiberg
- Lund University, Skane University Hospital, Department of Clinical Sciences Lund, Clinical Physiology, Lund, Sweden
- Department of Biomedical Engineering, Faculty of Engineering, Lund University, Lund, Sweden
- * E-mail:
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239
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Variability induced by the MR imager in dynamic contrast-enhanced imaging of the prostate. Diagn Interv Imaging 2018; 99:255-264. [DOI: 10.1016/j.diii.2017.12.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2017] [Revised: 12/03/2017] [Accepted: 12/07/2017] [Indexed: 12/22/2022]
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Multiparametric Magnetic Resonance Imaging of the Prostate: Repeatability of Volume and Apparent Diffusion Coefficient Quantification. Invest Radiol 2018; 52:538-546. [PMID: 28463931 PMCID: PMC5544576 DOI: 10.1097/rli.0000000000000382] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVES The aim of this study was to evaluate the repeatability of a region of interest (ROI) volume and mean apparent diffusion coefficient (ADC) in standard-of-care 3 T multiparametric magnetic resonance imaging (mpMRI) of the prostate obtained with the use of endorectal coil. MATERIALS AND METHODS This prospective study was Health Insurance Portability and Accountability Act compliant, with institutional review board approval and written informed consent. Men with confirmed or suspected treatment-naive prostate cancer scheduled for mpMRI were offered a repeat mpMRI within 2 weeks. Regions of interest corresponding to the whole prostate gland, the entire peripheral zone (PZ), normal PZ, and suspected tumor ROI (tROI) on axial T2-weighted, dynamic contrast-enhanced subtract, and ADC images were annotated and assessed using Prostate Imaging Reporting and Data System (PI-RADS) v2. Repeatability of the ROI volume for each of the analyzed image types and mean ROI ADC was summarized with repeatability coefficient (RC) and RC%. RESULTS A total of 189 subjects were approached to participate in the study. Of 40 patients that gave initial agreement, 15 men underwent 2 mpMRI examinations and completed the study. Peripheral zone tROIs were identified in 11 subjects. Tumor ROI volume was less than 0.5 mL in 8 of 11 subjects. PI-RADS categories were identical between baseline-repeat studies in 11/15 subjects and differed by 1 point in 4/15. Peripheral zone tROI volume RC (RC%) was 233 mm (71%) on axial T2-weighted, 422 mm (112%) on ADC, and 488 mm (119%) on dynamic contrast-enhanced subtract. Apparent diffusion coefficient ROI mean RC (RC%) were 447 × 10 mm/s (42%) in PZ tROI and 471 × 10 mm/s (30%) in normal PZ. Significant difference in repeatability of the tROI volume across series was observed (P < 0.005). The mean ADC RC% was lower than volume RC% for tROI ADC (P < 0.05). CONCLUSIONS PI-RADS v2 overall assessment was highly repeatable. Multiparametric magnetic resonance imaging sequences differ in volume measurement repeatability. The mean tROI ADC is more repeatable compared with tROI volume in ADC. Repeatability of prostate ADC is comparable with that in other abdominal organs.
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deSouza NM, Winfield JM, Waterton JC, Weller A, Papoutsaki MV, Doran SJ, Collins DJ, Fournier L, Sullivan D, Chenevert T, Jackson A, Boss M, Trattnig S, Liu Y. Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives. Eur Radiol 2018; 28:1118-1131. [PMID: 28956113 PMCID: PMC5811587 DOI: 10.1007/s00330-017-4972-z] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Revised: 05/24/2017] [Accepted: 06/28/2017] [Indexed: 12/18/2022]
Abstract
For body imaging, diffusion-weighted MRI may be used for tumour detection, staging, prognostic information, assessing response and follow-up. Disease detection and staging involve qualitative, subjective assessment of images, whereas for prognosis, progression or response, quantitative evaluation of the apparent diffusion coefficient (ADC) is required. Validation and qualification of ADC in multicentre trials involves examination of i) technical performance to determine biomarker bias and reproducibility and ii) biological performance to interrogate a specific aspect of biology or to forecast outcome. Unfortunately, the variety of acquisition and analysis methodologies employed at different centres make ADC values non-comparable between them. This invalidates implementation in multicentre trials and limits utility of ADC as a biomarker. This article reviews the factors contributing to ADC variability in terms of data acquisition and analysis. Hardware and software considerations are discussed when implementing standardised protocols across multi-vendor platforms together with methods for quality assurance and quality control. Processes of data collection, archiving, curation, analysis, central reading and handling incidental findings are considered in the conduct of multicentre trials. Data protection and good clinical practice are essential prerequisites. Developing international consensus of procedures is critical to successful validation if ADC is to become a useful biomarker in oncology. KEY POINTS • Standardised acquisition/analysis allows quantification of imaging biomarkers in multicentre trials. • Establishing "precision" of the measurement in the multicentre context is essential. • A repository with traceable data of known provenance promotes further research.
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Affiliation(s)
- N. M. deSouza
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - J. M. Winfield
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - J. C. Waterton
- Manchester Academic Health Sciences Institute, University of Manchester, Manchester, UK
| | - A. Weller
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - M.-V. Papoutsaki
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - S. J. Doran
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - D. J. Collins
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Surrey, SM2 5PT UK
| | - L. Fournier
- Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, Radiology Department, Université Paris Descartes Sorbonne Paris Cité, Paris, France
| | - D. Sullivan
- Duke Comprehensive Cancer Institute, Durham, NC USA
| | - T. Chenevert
- Department of Radiology, University of Michigan Health System, Ann Arbor, MI USA
| | - A. Jackson
- Manchester Academic Health Sciences Institute, University of Manchester, Manchester, UK
| | - M. Boss
- Applied Physics Division, National Institute of Standards and Technology (NIST), Boulder, CO USA
| | - S. Trattnig
- Department of Biomedical Imaging and Image guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Y. Liu
- European Organisation for Research and Treatment of Cancer, Headquarters, Brussels, Belgium
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Obuchowski NA. Interpreting Change in Quantitative Imaging Biomarkers. Acad Radiol 2018; 25:372-379. [PMID: 29191687 DOI: 10.1016/j.acra.2017.09.023] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Revised: 09/26/2017] [Accepted: 09/27/2017] [Indexed: 10/18/2022]
Abstract
RATIONALE AND OBJECTIVES Quantitative imaging biomarkers (QIBs) are becoming increasingly adopted into clinical practice to monitor changes in patients' conditions. The repeatability coefficient (RC) is the clinical cut-point used to discern between changes in a biomarker's measurements due to measurement error and changes that exceed measurement error, thus indicating real change in the patient. Imaging biomarkers have characteristics that make them difficult for estimating the repeatability coefficient, including nonconstant error, non-Gaussian distributions, and measurement error that must be estimated from small studies. METHODS We conducted a Monte Carlo simulation study to investigate how well three statistical methods for estimating the repeatability coefficient perform under five settings common for QIBs. RESULTS When the measurement error is constant and replicates are normally distributed, all of the statistical methods perform well. When the measurement error is proportional to the true value, approaches that use the log transformation or coefficient of variation perform similarly. For other common settings, none of the methods for estimating the repeatability coefficient perform adequately. CONCLUSION Many of the common approaches to estimating the repeatability coefficient perform well for only limited scenarios. The optimal approach depends strongly on the pattern of the within-subject variability; thus, a precision profile is critical in evaluating the technical performance of QIBs. Asymmetric bounds for detecting regression vs progression can be implemented and should be used when clinically appropriate.
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Moreau B, Iannessi A, Hoog C, Beaumont H. How reliable are ADC measurements? A phantom and clinical study of cervical lymph nodes. Eur Radiol 2018; 28:3362-3371. [PMID: 29476218 PMCID: PMC6028847 DOI: 10.1007/s00330-017-5265-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 12/11/2017] [Accepted: 12/20/2017] [Indexed: 12/11/2022]
Abstract
Objective To assess the reliability of ADC measurements in vitro and in cervical lymph nodes of healthy volunteers. Methods We used a GE 1.5 T MRI scanner and a first ice-water phantom according to recommendations released by the Quantitative Imaging Biomarker Alliance (QIBA) for assessing ADC against reference values. We analysed the target size effect by using a second phantom made of six inserted spheres with diameters ranging from 10 to 37 mm. Thirteen healthy volunteers were also scanned to assess the inter- and intra-observer reproducibility of volumetric ADC measurements of cervical lymph nodes. Results On the ice-water phantom, the error in ADC measurements was less than 4.3 %. The spatial bias due to the non-linearity of gradient fields was found to be 24 % at 8 cm from the isocentre. ADC measure reliability decreased when addressing small targets due to partial volume effects (up to 12.8 %). The mean ADC value of cervical lymph nodes was 0.87.10-3 ± 0.12.10-3 mm2/s with a good intra-observer reliability. Inter-observer reproducibility featured a bias of -5.5 % due to segmentation issues. Conclusion ADC is a potentially important imaging biomarker in oncology; however, variability issues preclude its broader adoption. Reliable use of ADC requires technical advances and systematic quality control. Key Points • ADC is a promising quantitative imaging biomarker. • ADC has a fair inter-reader variability and good intra-reader variability. • Partial volume effect, post-processing software and non-linearity of scanners are limiting factors. • No threshold values for detecting cervical lymph node malignancy can be drawn. Electronic supplementary material The online version of this article (10.1007/s00330-017-5265-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Bastien Moreau
- Department of Radiology, Centre Antoine Lacassagne, 06100, Nice, France
| | - Antoine Iannessi
- Department of Radiology, Centre Antoine Lacassagne, 06100, Nice, France
| | - Christopher Hoog
- Department of Radiology, Centre Antoine Lacassagne, 06100, Nice, France
| | - Hubert Beaumont
- Research and Development Department, Median Technologies, Les deux arcs - 1800 route des crêtes - Bat. B, 06560, Valbonne, France.
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Kaneta T, Daisaki H, Ogawa M, Liu ET, Iizuka H, Arisawa T, Hino-Shishikura A, Yoshida K, Inoue T. Use of count-based image reconstruction to evaluate the variability and repeatability of measured standardised uptake values. PLoS One 2018; 13:e0192549. [PMID: 29432459 PMCID: PMC5809066 DOI: 10.1371/journal.pone.0192549] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Accepted: 01/25/2018] [Indexed: 12/02/2022] Open
Abstract
Standardized uptake values (SUVs) are the most widely used quantitative imaging biomarkers in PET. It is important to evaluate the variability and repeatability of measured SUVs. Phantom studies seem to be essential for this purpose; however, repetitive phantom scanning is not recommended due to the decay of radioactivity. In this study, we performed count-based image reconstruction to avoid the influence of decay using two different PET/CT scanners. By adjusting the ratio of 18F-fluorodeoxyglucose solution to tap water, a NEMA IEC body phantom was set for SUVs of 4.0 inside six hot spheres. The PET data were obtained using two scanners (Aquiduo and Celesteion; Toshiba Medical Systems, Tochigi, Japan). We set the start time for image reconstruction when the total radioactivity in the phantom was 2.53 kBq/cc, and employed the counts of the first 2-min acquisition as the standard. To maintain the number of counts for each image, we set the acquisition time for image reconstruction depending on the decay of radioactivity. We obtained 50 images, and calculated the SUVmax and SUVpeak of all six spheres in each image. The average values of the SUVmax were used to calculate the recovery coefficients to compare those measured by the two different scanners. Bland-Altman analyses of the SUVs measured by the two scanners were also performed. The measured SUVs using the two scanners exhibited a 10–30% difference, and the standard deviation (SD) of the measured SUVs was between 0.1–0.2. The Celesteion always exhibited higher values than the Aquiduo. The smaller sphere exhibited a larger SD, and the SUVpeak had a smaller SD than the SUVmax. The Bland-Altman analyses showed poor agreement between the SUVs measured by the two scanners. The recovery coefficient curves obtained from the two scanners were considerably different. The Celesteion exhibited higher recovery coefficients than the Aquiduo, especially at approximately 20-mm-diameter. Additionally, the curves were lower than those calculated from the standard 30-min acquisition images. We propound count-based image reconstruction to evaluate the variability and repeatability of measured SUVs. These results are also applicable for the standardization and harmonization of SUVs in multi-institutional studies.
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Affiliation(s)
- Tomohiro Kaneta
- Department of Radiology, Yokohama City University, Yokohama, Japan
- * E-mail:
| | - Hiromitsu Daisaki
- Department of Radiological Technology, Gunma Prefectual College of Health Sciences, Maebashi, Japan
| | - Matsuyoshi Ogawa
- Department of Radiology, Yokohama City University, Yokohama, Japan
| | - En-Tao Liu
- Department of Radiology, Yokohama City University, Yokohama, Japan
| | - Hitoshi Iizuka
- Department of Radiology, Yokohama City University, Yokohama, Japan
| | - Tetsu Arisawa
- Department of Radiology, Yokohama City University, Yokohama, Japan
| | | | - Keisuke Yoshida
- Department of Radiology, Yokohama City University, Yokohama, Japan
| | - Tomio Inoue
- Department of Radiology, Yokohama City University, Yokohama, Japan
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West J, Romu T, Thorell S, Lindblom H, Berin E, Holm ACS, Åstrand LL, Karlsson A, Borga M, Hammar M, Leinhard OD. Precision of MRI-based body composition measurements of postmenopausal women. PLoS One 2018; 13:e0192495. [PMID: 29415060 PMCID: PMC5802932 DOI: 10.1371/journal.pone.0192495] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 01/24/2018] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVES To determine precision of magnetic resonance imaging (MRI) based fat and muscle quantification in a group of postmenopausal women. Furthermore, to extend the method to individual muscles relevant to upper-body exercise. MATERIALS AND METHODS This was a sub-study to a randomized control trial investigating effects of resistance training to decrease hot flushes in postmenopausal women. Thirty-six women were included, mean age 56 ± 6 years. Each subject was scanned twice with a 3.0T MR-scanner using a whole-body Dixon protocol. Water and fat images were calculated using a 6-peak lipid model including R2*-correction. Body composition analyses were performed to measure visceral and subcutaneous fat volumes, lean volumes and muscle fat infiltration (MFI) of the muscle groups' thigh muscles, lower leg muscles, and abdominal muscles, as well as the three individual muscles pectoralis, latissimus, and rhomboideus. Analysis was performed using a multi-atlas, calibrated water-fat separated quantification method. Liver-fat was measured as average proton density fat-fraction (PDFF) of three regions-of-interest. Precision was determined with Bland-Altman analysis, repeatability, and coefficient of variation. RESULTS All of the 36 included women were successfully scanned and analysed. The coefficient of variation was 1.1% to 1.5% for abdominal fat compartments (visceral and subcutaneous), 0.8% to 1.9% for volumes of muscle groups (thigh, lower leg, and abdomen), and 2.3% to 7.0% for individual muscle volumes (pectoralis, latissimus, and rhomboideus). Limits of agreement for MFI was within ± 2.06% for muscle groups and within ± 5.13% for individual muscles. The limits of agreement for liver PDFF was within ± 1.9%. CONCLUSION Whole-body Dixon MRI could characterize a range of different fat and muscle compartments with high precision, including individual muscles, in the study-group of postmenopausal women. The inclusion of individual muscles, calculated from the same scan, enables analysis for specific intervention programs and studies.
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Affiliation(s)
- Janne West
- Department of Medical and Health Sciences (IMH), Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Advanced MR Analytics AB, Linköping, Sweden
| | - Thobias Romu
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Advanced MR Analytics AB, Linköping, Sweden
- Department of Biomedical Engineering (IMT), Linköping University, Linköping, Sweden
| | - Sofia Thorell
- Department of Medical and Health Sciences (IMH), Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden
| | - Hanna Lindblom
- Department of Medical and Health Sciences (IMH), Linköping University, Linköping, Sweden
| | - Emilia Berin
- Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden
| | - Anna-Clara Spetz Holm
- Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden
| | - Lotta Lindh Åstrand
- Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden
| | - Anette Karlsson
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Department of Biomedical Engineering (IMT), Linköping University, Linköping, Sweden
| | - Magnus Borga
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Advanced MR Analytics AB, Linköping, Sweden
- Department of Biomedical Engineering (IMT), Linköping University, Linköping, Sweden
| | - Mats Hammar
- Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden
| | - Olof Dahlqvist Leinhard
- Department of Medical and Health Sciences (IMH), Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
- Advanced MR Analytics AB, Linköping, Sweden
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Jackson EF. Quantitative Imaging: The Translation from Research Tool to Clinical Practice. Radiology 2018; 286:499-501. [DOI: 10.1148/radiol.2017172258] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Edward F. Jackson
- From the Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, 1111 Highland Ave, 1016 WIMR, Madison, WI 53705
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Vonder M, van der Aalst CM, Vliegenthart R, van Ooijen PMA, Kuijpers D, Gratama JW, de Koning HJ, Oudkerk M. Coronary Artery Calcium Imaging in the ROBINSCA Trial: Rationale, Design, and Technical Background. Acad Radiol 2018; 25:118-128. [PMID: 28843465 DOI: 10.1016/j.acra.2017.07.010] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Revised: 07/18/2017] [Accepted: 07/20/2017] [Indexed: 01/20/2023]
Abstract
RATIONALE AND OBJECTIVES To describe the rationale, design, and technical background of coronary artery calcium (CAC) imaging in the large-scale population-based cardiovascular disease screening trial (Risk Or Benefit IN Screening for CArdiovascular Diseases [ROBINSCA]). MATERIALS AND METHODS First, literature search was performed to review the logistics, setup, and settings of previously performed CAC imaging studies, and current clinical CAC imaging protocols of participating centers in the ROBINSCA trial were evaluated. A second literature search was performed to evaluate the impact of computed tomography parameter settings on CAC score. RESULTS Based on literature reviews and experts opinion an imaging protocol accompanied by data management protocol was created for ROBINSCA. The imaging protocol should consist of a fixed tube voltage, individually tailored tube current setting, mid-diastolic electrocardiography-triggering, fixed field-of-view, fixed reconstruction kernel, fixed slice thickness, overlapping reconstruction and without iterative reconstruction. The analysis of scans is performed with one type and version of CAC scoring software, by two dedicated and experienced researchers. The data management protocol describes the organization of data handling between the coordinating center, participating centers, and core analysis center. CONCLUSION In this paper we describe the rationale and technical considerations to be taken in developing CAC imaging protocol, and we present a detailed protocol that can be implemented for CAC screening purposes.
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Affiliation(s)
- Marleen Vonder
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands
| | - Carlijn M van der Aalst
- Erasmus MC-University Medical Centre, Department of Public Health, Rotterdam, The Netherlands
| | - Rozemarijn Vliegenthart
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands
| | - Peter M A van Ooijen
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, Department of Radiology, Groningen, The Netherlands
| | - Dirkjan Kuijpers
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands; Department of Radiology, Haaglanden Medical Center Bronovo, The Hague, The Netherlands
| | - Jan Willem Gratama
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands; Department of Radiology, Gelre Hospital, Apeldoorn, The Netherlands
| | - Harry J de Koning
- Erasmus MC-University Medical Centre, Department of Public Health, Rotterdam, The Netherlands
| | - Matthijs Oudkerk
- University of Groningen, University Medical Center Groningen, Center for Medical Imaging North-East Netherlands (CMI-NEN), Groningen, The Netherlands.
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Barnes A, Alonzi R, Blackledge M, Charles-Edwards G, Collins DJ, Cook G, Coutts G, Goh V, Graves M, Kelly C, Koh DM, McCallum H, Miquel ME, O’Connor J, Padhani A, Pearson R, Priest A, Rockall A, Stirling J, Taylor S, Tunariu N, van der Meulen J, Walls D, Winfield J, Punwani S. UK quantitative WB-DWI technical workgroup: consensus meeting recommendations on optimisation, quality control, processing and analysis of quantitative whole-body diffusion-weighted imaging for cancer. Br J Radiol 2018; 91:20170577. [PMID: 29076749 PMCID: PMC5966219 DOI: 10.1259/bjr.20170577] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 10/09/2017] [Accepted: 10/11/2017] [Indexed: 01/28/2023] Open
Abstract
OBJECTIVE Application of whole body diffusion-weighted MRI (WB-DWI) for oncology are rapidly increasing within both research and routine clinical domains. However, WB-DWI as a quantitative imaging biomarker (QIB) has significantly slower adoption. To date, challenges relating to accuracy and reproducibility, essential criteria for a good QIB, have limited widespread clinical translation. In recognition, a UK workgroup was established in 2016 to provide technical consensus guidelines (to maximise accuracy and reproducibility of WB-MRI QIBs) and accelerate the clinical translation of quantitative WB-DWI applications for oncology. METHODS A panel of experts convened from cancer centres around the UK with subspecialty expertise in quantitative imaging and/or the use of WB-MRI with DWI. A formal consensus method was used to obtain consensus agreement regarding best practice. Questions were asked about the appropriateness or otherwise on scanner hardware and software, sequence optimisation, acquisition protocols, reporting, and ongoing quality control programs to monitor precision and accuracy and agreement on quality control. RESULTS The consensus panel was able to reach consensus on 73% (255/351) items and based on consensus areas made recommendations to maximise accuracy and reproducibly of quantitative WB-DWI studies performed at 1.5T. The panel were unable to reach consensus on the majority of items related to quantitative WB-DWI performed at 3T. CONCLUSION This UK Quantitative WB-DWI Technical Workgroup consensus provides guidance on maximising accuracy and reproducibly of quantitative WB-DWI for oncology. The consensus guidance can be used by researchers and clinicians to harmonise WB-DWI protocols which will accelerate clinical translation of WB-DWI-derived QIBs.
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Affiliation(s)
- Anna Barnes
- Centre for Medical Imaging, University College London,University College London, London, UK
| | - Roberto Alonzi
- Clinical Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Matthew Blackledge
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, Institute of Cancer Research,Institute of Cancer Research, Sutton, UK
| | | | | | | | - Glynn Coutts
- MR Physics, The Christie NHS Foundation Trust, The Christie NHS Foundation Trust, Manchester, UK
| | | | - Martin Graves
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust,Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Charles Kelly
- Department of Radiology, Northern Centre for CancerCare, Newcastle upon Tyne Hospitals, NHS Foundations Trust,Northern Centre for CancerCare, Newcastle upon Tyne Hospitals, NHS Foundations Trust, Newcastle upon Tyne, UK
| | | | - Hazel McCallum
- Department of Radiology, Northern Centre for CancerCare, Newcastle upon Tyne Hospitals, NHS Foundations Trust,Northern Centre for CancerCare, Newcastle upon Tyne Hospitals, NHS Foundations Trust, Newcastle upon Tyne, UK
| | | | | | - Anwar Padhani
- Paul Strickland Cancer Centre, Mount Vernon Cancer Centre, Northwood, UK
| | | | - Andrew Priest
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust,Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Andrea Rockall
- Department of Radiology, The Royal Marsden Hospital Foundation Trust,The Royal Marsden Hospital Foundation Trust, Surrey, UK
| | | | | | | | - Jan van der Meulen
- Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine,London School of Hygiene and Tropical Medicine, London, UK
| | - Darren Walls
- Institute Nuclear Medicine, University College London, London, UK
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Pinkert MA, Salkowski LR, Keely PJ, Hall TJ, Block WF, Eliceiri KW. Review of quantitative multiscale imaging of breast cancer. J Med Imaging (Bellingham) 2018; 5:010901. [PMID: 29392158 PMCID: PMC5777512 DOI: 10.1117/1.jmi.5.1.010901] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2017] [Accepted: 12/19/2017] [Indexed: 12/12/2022] Open
Abstract
Breast cancer is the most common cancer among women worldwide and ranks second in terms of overall cancer deaths. One of the difficulties associated with treating breast cancer is that it is a heterogeneous disease with variations in benign and pathologic tissue composition, which contributes to disease development, progression, and treatment response. Many of these phenotypes are uncharacterized and their presence is difficult to detect, in part due to the sparsity of methods to correlate information between the cellular microscale and the whole-breast macroscale. Quantitative multiscale imaging of the breast is an emerging field concerned with the development of imaging technology that can characterize anatomic, functional, and molecular information across different resolutions and fields of view. It involves a diverse collection of imaging modalities, which touch large sections of the breast imaging research community. Prospective studies have shown promising results, but there are several challenges, ranging from basic physics and engineering to data processing and quantification, that must be met to bring the field to maturity. This paper presents some of the challenges that investigators face, reviews currently used multiscale imaging methods for preclinical imaging, and discusses the potential of these methods for clinical breast imaging.
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Affiliation(s)
- Michael A. Pinkert
- Morgridge Institute for Research, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Laboratory for Optical and Computational Instrumentation, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Medical Physics, Madison, Wisconsin, United States
| | - Lonie R. Salkowski
- University of Wisconsin–Madison, Department of Medical Physics, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Radiology, Madison, Wisconsin, United States
| | - Patricia J. Keely
- University of Wisconsin–Madison, Department of Cell and Regenerative Biology, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Biomedical Engineering, Madison, Wisconsin, United States
| | - Timothy J. Hall
- University of Wisconsin–Madison, Department of Medical Physics, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Biomedical Engineering, Madison, Wisconsin, United States
| | - Walter F. Block
- University of Wisconsin–Madison, Department of Medical Physics, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Radiology, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Biomedical Engineering, Madison, Wisconsin, United States
| | - Kevin W. Eliceiri
- Morgridge Institute for Research, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Laboratory for Optical and Computational Instrumentation, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Medical Physics, Madison, Wisconsin, United States
- University of Wisconsin–Madison, Department of Biomedical Engineering, Madison, Wisconsin, United States
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Wang R, Duan X, Shen C, Han D, Ma J, Wu H, Xu X, Qin T, Fan Q, Zhang Z, Shi W, Guo Y. A retrospective study of SPECT/CT scans using SUV measurement of the normal pelvis with Tc-99m methylene diphosphonate. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2018; 26:895-908. [PMID: 30103368 DOI: 10.3233/xst-180391] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
OBJECTIVE To perform quantitative measurement based on the standardized uptake value (SUV) of Tc-99m methylene diphosphonate (MDP) in the normal pelvis using a single-photon emission tomography (SPECT)/computed tomography (CT) scanner. MATERIAL AND METHODS This retrospective study was performed on 31 patients with cancer undergoing bone SPECT/CT scans with 99mTc-MDP. SUVmax and SUVmean of the normal pelvis were calculated based on the body weight. SUVmax and SUVmean of the bilateral anterior superior iliac spine, posterior superior iliac spine, facies auricularis ossis ilii, ischial tuberosity, and sacrum were also calculated. Furthermore, the correlation of SUVmax and SUVmean of all parts of pelvis with weight, height, and CT was assessed. RESULTS The data for 31 patients (20 women and 11 men; mean age 58.97±9.12 years; age range 37-87 years) were collected. SUVmax and SUVmean changed from 1.65±0.40 to 3.8±1.0 and from 1.15±0.25 to 2.07±0.58, respectively. The coefficient of variation of SUVmax and SUVmean ranged from 0.22 to 0.31. SUVmax and SUVmean had no statistically significant difference between men and women. SUVmax and SUVmean also showed no significant correlation with weight and height. However, part of SUVmax and SUVmean showed a significant correlation with CT. In addition, SUVmax and SUVmean of the bilateral ischial tuberosity showed a significant correlation with CT values. CONCLUSIONS Determination of the SUV value of the normal pelvis with 99m Tc-MDP SPECT/CT is feasible and highly reproducible. SUVs of the normal pelvis showed a relatively large variability. As a quantitative imaging biomarker, SUVs might require standardization with adequate reference data for the participant to minimize variability.
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Affiliation(s)
- Ruifeng Wang
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Xiaoyi Duan
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Cong Shen
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Dong Han
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Junchao Ma
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Hulin Wu
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Xiaotong Xu
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Tao Qin
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Qiuju Fan
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Zhaoguo Zhang
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Weihua Shi
- Department of Medical Image, The Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China
| | - Youmin Guo
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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