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Lennartz S, Cao J, Pisuchpen N, Srinivas-Rao S, Locascio JJ, Parakh A, Hahn PF, Mileto A, Sahani D, Kambadakone A. Intra-patient variability of iodine quantification across different dual-energy CT platforms: assessment of normalization techniques. Eur Radiol 2024; 34:5131-5141. [PMID: 38189979 DOI: 10.1007/s00330-023-10560-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 11/18/2023] [Accepted: 12/08/2023] [Indexed: 01/09/2024]
Abstract
OBJECTIVES To investigate intra-patient variability of iodine concentration (IC) between three different dual-energy CT (DECT) platforms and to test different normalization approaches. METHODS Forty-four patients who underwent portal venous phase abdominal DECT on a dual-source (dsDECT), a rapid kVp switching (rsDECT), and a dual-layer detector platform (dlDECT) during cancer follow-up were retrospectively included. IC in the liver, pancreas, and kidneys and different normalized ICs (NICPV:portal vein; NICAA:abdominal aorta; NICALL:overall iodine load) were compared between the three DECT scanners for each patient. A longitudinal mixed effects analysis was conducted to elucidate the effect of the scanner type, scan order, inter-scan time, and contrast media amount on normalized iodine concentration. RESULTS Variability of IC was highest in the liver (dsDECT vs. dlDECT 28.96 (14.28-46.87) %, dsDECT vs. rsDECT 29.08 (16.59-62.55) %, rsDECT vs. dlDECT 22.85 (7.52-33.49) %), and lowest in the kidneys (dsDECT vs. dlDECT 15.76 (7.03-26.1) %, dsDECT vs. rsDECT 15.67 (8.86-25.56) %, rsDECT vs. dlDECT 10.92 (4.92-22.79) %). NICALL yielded the best reduction of IC variability throughout all tissues and inter-scanner comparisons, yet did not reduce the variability between dsDECT vs. dlDECT and rsDECT, respectively, in the liver. The scanner type remained a significant determinant for NICALL in the pancreas and the liver (F-values, 12.26 and 23.78; both, p < 0.0001). CONCLUSIONS We found tissue-specific intra-patient variability of IC across different DECT scanner types. Normalization mitigated variability by reducing physiological fluctuations in iodine distribution. After normalization, the scanner type still had a significant effect on iodine variability in the pancreas and liver. CLINICAL RELEVANCE STATEMENT Differences in iodine quantification between dual-energy CT scanners can partly be mitigated by normalization, yet remain relevant for specific tissues and inter-scanner comparisons, which should be taken into account at clinical routine imaging. KEY POINTS • Iodine concentration showed the least variability between scanner types in the kidneys (range 10.92-15.76%) and highest variability in the liver (range 22.85-29.08%). • Normalizing tissue-specific iodine concentrations against the overall iodine load yielded the greatest reduction of variability between scanner types for 2/3 inter-scanner comparisons in the liver and for all (3/3) inter-scanner comparisons in the kidneys and pancreas, respectively. • However, even after normalization, the dual-energy CT scanner type was found to be the factor significantly influencing variability of iodine concentration in the liver and pancreas.
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Affiliation(s)
- Simon Lennartz
- Department of Radiology, Abdominal Radiology Division, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany
| | - Jinjin Cao
- Department of Radiology, Abdominal Radiology Division, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA
| | - Nisanard Pisuchpen
- Department of Radiology, Abdominal Radiology Division, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA
- Department of Radiology, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand
| | - Shravya Srinivas-Rao
- Department of Radiology, Abdominal Radiology Division, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA
| | - Joseph J Locascio
- Harvard Catalyst Biostatistical Unit, Harvard Medical School/Massachusetts General Hospital, Boston, MA, USA
| | - Anushri Parakh
- Department of Radiology, Abdominal Radiology Division, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA
| | - Peter F Hahn
- Department of Radiology, Abdominal Radiology Division, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA
| | - Achille Mileto
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Dushyant Sahani
- Department of Radiology, University of Washington, UWMC Radiology RR218, 1959 NE Pacific St, Seattle, WA, 98195, USA
| | - Avinash Kambadakone
- Department of Radiology, Abdominal Radiology Division, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA.
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Zhang X, Jin Z, Sun H. Letter to the Editor: "Intra-patient variability of iodine quantification across different dual-energy CT platforms: assessment of normalization techniques". Eur Radiol 2024:10.1007/s00330-024-10832-2. [PMID: 38856780 DOI: 10.1007/s00330-024-10832-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Revised: 01/13/2024] [Accepted: 03/20/2024] [Indexed: 06/11/2024]
Affiliation(s)
- Xiaoxiao Zhang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
| | - Hao Sun
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
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Zhu YF, Liu ML, Zheng WT, Fu F, Xue ES, Fan XQ, Zhang HP, Lian GT, Ye Q. Predictive Model of CK7 Expression in Patients With Clear Cell Renal Cell Carcinoma by Combined Multimodal Ultrasound Diagnostic Techniques: A Retrospective Study. ULTRASOUND IN MEDICINE & BIOLOGY 2024; 50:520-527. [PMID: 38281886 DOI: 10.1016/j.ultrasmedbio.2023.12.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 11/18/2023] [Accepted: 12/07/2023] [Indexed: 01/30/2024]
Abstract
OBJECTIVE The aim of the work described here was to develop and validate a predictive model for cytokeratin 7 (CK7) expression in clear cell renal cell carcinoma (ccRCC) patients by combining multimodal ultrasound diagnostic techniques. METHODS This retrospective study enrolled 157 surgically confirmed ccRCC patients. All patients underwent pre-operative multimodal ultrasound diagnostic examinations, including B-mode ultrasound (US), color Doppler flow imaging (CDFI) and contrast-enhanced ultrasound (CEUS). The patients were randomly divided into a training group (103 cases) and a testing group (54 cases). Univariate and multivariate logistic regression analyses were performed in the training group to identify independent indicators associated with CK7 positivity. These indicators were included in the predictive model. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the model's discriminative ability and accuracy. Decision curve analysis (DCA) and nomogram visualization were used to assess the clinical utility of the predictive model. RESULTS Univariate logistic regression analysis revealed that US and CDFI observations were not correlated with CK7 expression and could not predict it. Multivariate logistic regression analysis identified age (odds ratio [OR] = 0.953, 95% confidence interval [CI]: 0.909-0.999), wash-in pattern (OR = 0.180, 95% CI: 0.063-0.513) and enhancement homogeneity (OR = 11.610, 95% CI: 1.394-96.675) as independent factors related to CK7 positivity in ccRCC. Incorporating these variables into the predictive model resulted in areas under the receiver operating characteristic curve of 0.812 (95% CI: 0.711-0.913) for the training group and 0.792 (95% CI: 0.667-0.924) for the testing group. The calibration curve and DCA revealed that the model had good accuracy and clinical utility of the model. CONCLUSION The combination of multimodal ultrasound diagnostic techniques in constructing a predictive model for CK7 expression in ccRCC patients has significant predictive value.
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Affiliation(s)
- Yi-Fan Zhu
- Department of Ultrasound/Fujian Provincial Institute of Ultrasonic Medicine, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, China
| | - Mao-Lin Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian Province, China
| | - Wen-Ting Zheng
- Department of Ultrasound/Fujian Provincial Institute of Ultrasonic Medicine, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, China
| | - Fen Fu
- Department of Ultrasound/Fujian Provincial Institute of Ultrasonic Medicine, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, China
| | - En-Sheng Xue
- Department of Ultrasound/Fujian Provincial Institute of Ultrasonic Medicine, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, China
| | - Xiao-Qing Fan
- Department of Ultrasound/Fujian Provincial Institute of Ultrasonic Medicine, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, China
| | - Hui-Ping Zhang
- Department of Ultrasound/Fujian Provincial Institute of Ultrasonic Medicine, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, China
| | - Guang-Tian Lian
- Department of Ultrasound/Fujian Provincial Institute of Ultrasonic Medicine, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, China
| | - Qin Ye
- Department of Ultrasound/Fujian Provincial Institute of Ultrasonic Medicine, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, China.
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Wang S, Tong X, Zhang J, Fan Y, Wei W, Li J, Liu Y, Hu M, Chen Q, Liu L. Estimation of renal function using iodine maps in dual-energy spectral computed tomography urography: a feasibility and accuracy study. Abdom Radiol (NY) 2024; 49:997-1005. [PMID: 38244037 DOI: 10.1007/s00261-023-04146-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 11/28/2023] [Accepted: 11/29/2023] [Indexed: 01/22/2024]
Abstract
PURPOSE To explore the feasibility of measuring glomerular filtration rate (GFR) using iodine maps in dual-energy spectral computed tomography urography (DEsCTU) and correlate them with the estimated GFR (eGFR) based on the equation of creatinine-cystatin C. MATERIALS AND METHODS One hundred and twenty-eight patients referred for DEsCTU were retrospectively enrolled. The DEsCTU protocol included non-contrast, nephrographic, and excretory phase imaging. The CT-derived GFR was calculated using the above 3-phase iodine maps (CT-GFRiodine) and 120 kVp-like images (CT-GFR120kvp) separately. CT-GFRiodine and CT-GFR120kvp were compared with eGFR using paired t-test, correlation analysis, and Bland-Altman plots. The receiver operating characteristic curves were used to test the renal function diagnostic performance with CT-GFR120kvp and CT-GFRiodine. RESULTS The difference between eGFR (89.91 ± 18.45 ml·min-1·1.73 m-2) as reference standard and CT-GFRiodine (90.06 ± 20.89 ml·min-1·1.73 m-2) was not statistically significant, showing excellent correlation (r = 0.88, P < 0.001) and agreement (± 19.75 ml·min-1·1.73 m-2, P = 0.866). The correlation between eGFR and CT-GFR120kvp (66.13 ± 19.18 ml·min-1·1.73 m-2) was poor (r = 0.36, P < 0.001), and the agreement was poor (± 40.65 ml·min-1·1.73 m-2, P < 0.001). There were 62 patients with normal renal function and 66 patients with decreased renal function based on eGFR. The CT-GFRiodine had the largest area under the curve (AUC) for distinguishing between normal and decreased renal function (AUC = 0.951). CONCLUSION The GFR can be calculated accurately using iodine maps in DEsCTU. DEsCTU could be a non-invasive and reliable one-stop-shop imaging technique for evaluating both the urinary tract morphology and renal function.
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Affiliation(s)
- Shigeng Wang
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Urology, Shahekou District, Lianhe Road, Dalian, China
| | - Xiaoyu Tong
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Urology, Shahekou District, Lianhe Road, Dalian, China
| | - Jingyi Zhang
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Urology, Shahekou District, Lianhe Road, Dalian, China
| | - Yong Fan
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Urology, Shahekou District, Lianhe Road, Dalian, China
| | - Wei Wei
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Urology, Shahekou District, Lianhe Road, Dalian, China
| | | | - Yijun Liu
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Urology, Shahekou District, Lianhe Road, Dalian, China
| | - Mengting Hu
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Urology, Shahekou District, Lianhe Road, Dalian, China
| | - Qiye Chen
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Urology, Shahekou District, Lianhe Road, Dalian, China
| | - Lei Liu
- Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
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Virarkar MK, Mileto A, Vulasala SSR, Ananthakrishnan L, Bhosale P. Dual-Energy Computed Tomography Applications in the Genitourinary Tract. Radiol Clin North Am 2023; 61:1051-1068. [PMID: 37758356 DOI: 10.1016/j.rcl.2023.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
By virtue of material differentiation capabilities afforded through dedicated postprocessing algorithms, dual-energy CT (DECT) has been shown to provide benefit in the evaluation of various diseases. In this article, we review the diagnostic use of DECT in the assessment of genitourinary diseases, with emphasis on its role in renal stone characterization, incidental renal and adrenal lesion characterization, retroperitoneal trauma, reduction of radiation, and contrast dose and cost-effectiveness potential. We also discuss future perspectives of the DECT scanning mode, including the use of novel contrast injection strategies and photon-counting detector computed tomography.
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Affiliation(s)
- Mayur K Virarkar
- Department of Radiology, University of Florida College of Medicine, Clinical Center, C90, 2nd Floor, 655 West 8th Street, Jacksonville, FL 32209, USA
| | - Achille Mileto
- Department of Radiology, Mayo Clinic, Mayo Building West, 2nd Floor, 200 First Street SW, Rochester, MN, 55905, USA
| | - Sai Swarupa R Vulasala
- Department of radiology, University of Florida College of Medicine, Clinical Center, C90, 2nd Floor, 655 West 8th Street, Jacksonville, FL, 32209, USA.
| | - Lakshmi Ananthakrishnan
- Department of Radiology, UT Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA
| | - Priya Bhosale
- Department of Diagnostic Radiology, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 1479, Houston, TX 77030, USA
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Zhang X, Zhang G, Xu L, Bai X, Zhang J, Chen L, Lu X, Yu S, Jin Z, Sun H. Prediction of World Health Organization /International Society of Urological Pathology (WHO/ISUP) Pathological Grading of Clear Cell Renal Cell Carcinoma by Dual-Layer Spectral CT. Acad Radiol 2023; 30:2321-2328. [PMID: 36543688 DOI: 10.1016/j.acra.2022.12.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 11/27/2022] [Accepted: 12/02/2022] [Indexed: 12/24/2022]
Abstract
RATIONALE AND OBJECTIVES To evaluate whether the dual-layer spectral computed tomography urography (DL-CTU) images could predict WHO/ISUP pathological grading of clear cell renal cell carcinoma (ccRCC). MATERIALS AND METHODS We retrospectively included patients (n = 50) with pathologically confirmed ccRCC who underwent preoperative DL-CTU (from October 2017 to February 2021). They were divided into low-grade (WHO/ISUP 1/2, n = 30) and high-grade groups (WHO/ISUP 3/4, n = 20). The lesion size, attenuation (HU), iodine concentration (IC), normalized IC(NIC), and other quantitative characteristics were compared between the two groups. HU, IC, and NIC were obtained by plotting ROI with two different methods (circular ROI in the solid component or irregular ROI along the tumor edge containing tumor necrotic components). Receiver operating characteristic curves and multivariable model were used to evaluate the ability of parameters to predict WHO/ISUP grade. RESULTS Transverse diameter (TD) of low-grade tumors was smaller, and HU in the non-contrast phase of the second method (HU-U-2) was lower than that of high-grade tumors (34.21±15.14 mm vs. 46.50 ± 20.68 mm, 27.33 ± 6.65 HU vs. 31.36 ± 6.09 HU, p< 0.05). The NIC in the nephrographic phase by the two methods (NIC-N-1 and NIC-N-2) of low-grade was higher than that of the high-grade group (0.78± 0.19 vs.0.58 ± 0.22, 0.73 ± 0.42 vs. 0.46 ± 0.22, p< 0.05). The final multivariable model composed of TD, HU-U-2, and NIC-N-1 could predict ccRCC grade with the area under the curve, sensitivity, specificity, and accuracy of 0.852, 70%, 90%, and 82%. CONCLUSION Quantitative indicators in DL-CTU images could help predict the WHO/ISUP grade of ccRCC.
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Affiliation(s)
- Xiaoxiao Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, BJ, P.R.China
| | - Gumuyang Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, BJ, P.R.China
| | - Lili Xu
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, BJ, P.R.China
| | - Xin Bai
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, BJ, P.R.China
| | - Jiahui Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, BJ, P.R.China
| | - Li Chen
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, BJ, P.R.China
| | - Xiaomei Lu
- CT Clinical Science, Philips Healthcare, Beijing, BJ, P.R.China
| | - Shenghui Yu
- CT Clinical Science, Philips Healthcare, Beijing, BJ, P.R.China
| | - Zhengyu Jin
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, BJ, P.R.China; National Center for Quality Control of Radiology, Beijing BJ, P.R.China
| | - Hao Sun
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, BJ, P.R.China; National Center for Quality Control of Radiology, Beijing BJ, P.R.China.
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Drljevic-Nielsen A, Mains JR, Thorup K, Andersen MB, Rasmussen F, Donskov F. Early reduction in spectral dual-layer detector CT parameters as favorable imaging biomarkers in patients with metastatic renal cell carcinoma. Eur Radiol 2022; 32:7323-7334. [PMID: 35511260 DOI: 10.1007/s00330-022-08793-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 03/30/2022] [Accepted: 04/03/2022] [Indexed: 01/03/2023]
Abstract
OBJECTIVES To associate the early change in DL-CT parameters and HU with survival outcomes and treatment response in patients with metastatic renal cell carcinoma (mRCC). METHODS DL-CT scans were performed at baseline and after 1 month of checkpoint immunotherapy or tyrosine kinase inhibitor therapy. Scans were reconstructed to conventional CT and DL-CT series, and used for assessment of HU, iodine concentration (IC), and the effective atomic number (Zeffective) in the combined RECISTv.1.1 target lesions. The relative changes, defined as ΔIC(combined), ΔZeffective(combined), and ΔHU(combined), were associated with progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). The reduction in the sum of diameters of target lesions ≥ 30% after 1 month was associated with OS, PFS, and ORR. RESULTS Overall, 115 and 104 mRCC patients were included at baseline and 1 month, respectively. Median IC(combined) decreased from 2.3 to 1.2 mg/ml (p < 0.001), Zeffective(combined) from 8.5 to 8.0 (p < 0.001), and HU(combined) from 86.0 to 64.00 HU (p < 0.001). After multivariate adjustments, the largest reductions in ΔIC(combined) (HR 0.47, 95% CI: 0.24-0.94, p = 0.033) and ΔZeffective(combined) (HR = 0.43, 95% CI: 0.21-0.87, p = 0.019) were associated with favorable OS; the largest reduction in ΔZeffective(combined) was associated with higher response (OR = 2.79, 95% CI: 1.12-6.94, p = 0.027). The largest reduction in ΔHU(combined) was solely associated with OS in univariate analysis (HR 0.45, 95% CI: 0.23-0.91). Reduction in SOD ≥ 30% at 1 month was not associated with outcomes (p > 0.075). CONCLUSIONS Early reductions at 1 month in ΔIC(combined) and ΔZeffective(combined) are associated with favorable outcomes in patients with mRCC. This information may reassure physicians and patients about treatment strategy. KEY POINTS • Early reductions following 1 month of therapy in spectral dual-layer detector CT-derived iodine concentration and the effective atomic number (Zeffective) are independent biomarkers for better overall survival in patients with metastatic renal cell carcinoma. • Early reduction after 1 month of therapy in the effective atomic number (Zeffective) is an independent imaging biomarker for better treatment response metastatic renal cell carcinoma.
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Affiliation(s)
- Aska Drljevic-Nielsen
- Department of Radiology, Aarhus University Hospital, Palle Juul-Jensens Blvd. 99, 8200, Aarhus N, Denmark.
- Department of Oncology, Aarhus University Hospital, Palle Juul-Jensens Blvd. 99, 8200, Aarhus N, Denmark.
| | - Jill R Mains
- Department of Radiology, Aarhus University Hospital, Palle Juul-Jensens Blvd. 99, 8200, Aarhus N, Denmark
| | - Kennet Thorup
- Department of Radiology, Aarhus University Hospital, Palle Juul-Jensens Blvd. 99, 8200, Aarhus N, Denmark
| | - Michael Brun Andersen
- Department of Radiology, Aarhus University Hospital, Palle Juul-Jensens Blvd. 99, 8200, Aarhus N, Denmark
- Department of Radiology, Herlev/Gentofte, Denmark
| | - Finn Rasmussen
- Department of Radiology, Aarhus University Hospital, Palle Juul-Jensens Blvd. 99, 8200, Aarhus N, Denmark
| | - Frede Donskov
- Department of Oncology, Aarhus University Hospital, Palle Juul-Jensens Blvd. 99, 8200, Aarhus N, Denmark
- Department of Oncology, University Hospital of Southern Denmark, Esbjerg, Denmark
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Chen W, Ye Y, Zhang D, Mao L, Guo L, Zhang H, Du X, Deng W, Liu B, Liu X. Utility of dual-layer spectral-detector CT imaging for predicting pathological tumor stages and histologic grades of colorectal adenocarcinoma. Front Oncol 2022; 12:1002592. [PMID: 36248968 PMCID: PMC9564703 DOI: 10.3389/fonc.2022.1002592] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/09/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives To assess the utility of Dual-layer spectral-detector CT (DLCT) in predicting the pT stage and histologic grade for colorectal adenocarcinoma (CRAC). Methods A total of 131 patients (mean 62.7 ± 12.9 years; 72 female, 59 male) with pathologically confirmed CRAC (35 pT1-2, 61 pT3, and 35 pT4; 32 high grade and 99 low grade), who received dual-phase DLCT were enrolled in this retrospective study. Normalized iodine concentration (NIC), slope of the spectral HU curve (λHU), and effective atomic number (Eff-Z) were measured for each lesion by two radiologists independently. Intraobserver reliability and interobserver agreement were assessed. The above values were compared between three pT-stage and two histologic-grade groups. The correlation between the pT stages and above values were assessed. Receiver operating characteristic (ROC) curves were calculated to evaluate the diagnostic efficacy. Results Intra-class correlation coefficients were ranged from 0.856 to 0.983 for all measurements. Eff-Z [7.21(0.09) vs 7.31 (0.10) vs 7.35 (0.19)], NICAP [0.11 (0.05) vs 0.15 (0.08) vs 0.15 (0.08)], NICVP [0.27 (0.06) vs 0.34 (0.11) vs 0.35 (0.12)], λHUAP [1.20 (0.45) vs 1.93 (1.18) vs 2.37 (0.91)], and λHUVP [2.07 (0.68) vs 2.35 (0.62) vs 3.09 (1.07)] were significantly different among pT stage groups (all P<0.001) and exhibited a positive correlation with pT stages (r= 0.503, 0.455, 0.394, 0.512, 0.376, respectively, all P<0.001). Eff-Z [7.37 (0.10) vs 7.28 (0.08)], NICAP[0.20 (0.10) vs 0.13 (0.08)], NICVP[0.35 (0.07) vs 0.31 (0.11)], and λHUAP [2.59 (1.11) vs 1.63 (0.75)] in the high-grade group were markedly higher than those in the low-grade group (all P<0.05). For discriminating the advanced- from early-stage CARC, the AUCs of Eff-Z, NICAP, NICVP, λHUAP, and λHUVP were 0.83, 0.80, 0.79, 0.86, and 0.68, respectively (all P<0.001). For discriminating the high- from low-grade CARC, the AUCs of Eff-Z, NICAP, NICVP, and λHUAP were 0.81, 0.81, 0.64, and 0.81, respectively (all P<0.05). Conclusions The quantitative parameters derived from DLCT may provide new markers for assessing pT stages and histologic differentiation in patients with CRAC.
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Affiliation(s)
- Weicui Chen
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yongsong Ye
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Daochun Zhang
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Taizhou, China
| | - Liting Mao
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Lei Guo
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Hanliang Zhang
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xiaohua Du
- Department of Pathology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Weiwei Deng
- Clinical and Technical Support, Philips Healthcare, Shanghai, China
| | - Bo Liu
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xian Liu
- Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
- *Correspondence: Xian Liu,
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Diagnosing cervical lymph node metastasis in oral squamous cell carcinoma based on third-generation dual-source, dual-energy computed tomography. Eur Radiol 2022; 33:162-171. [PMID: 36070090 DOI: 10.1007/s00330-022-09033-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 06/12/2022] [Accepted: 07/14/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To investigate the potential of dual-energy computed tomography (DECT) parameters in identifying metastatic cervical lymph nodes in oral squamous cell carcinoma (OSCC) patients and to explore the relationships between DECT and pathological features. METHODS Clinical and DECT data were collected from patients who underwent radical resection of OSCC and cervical lymph node dissection between November 2019 and June 2021. Microvascular density was assessed using the Weidner counting method. The electron density (ED) and effective atomic number (Zeff) in non - contrast phase and iodine concentration (IC), normalized IC, slope of the energy spectrum curve (λHU), and dual-energy index (DEI) in parenchymal phase were compared between metastatic and non - metastatic lymph nodes. Student's t-test, Pearson's rank correlation, and receiver operating characteristic curves were performed. RESULTS The inclusion criteria were met in 399 lymph nodes from 103 patients. Metastatic nodes (n = 158) displayed significantly decreased ED, IC, normalized IC, λHU, and DEI values compared with non-metastatic nodes (n = 241) (all p < 0.01). Strong correlations were found between IC (r = 0.776), normalized IC (r = 0.779), λHU (r = 0.738), DEI (r = 0.734), and microvascular density. Area under the curve (AUC) for normalized IC performed the highest (0.875) in diagnosing metastatic nodes. When combined with the width of nodes, AUC increased to 0.918. CONCLUSION DECT parameters IC, normalized IC, λHU, and DEI reflect pathologic changes in lymph nodes to a certain extent, and aid for detection of metastatic cervical lymph nodes from OSCC. KEY POINTS • Electron density, iodine concentration, normalized iodine concentration, λHU, and dual-energy index values showed significant differences between metastatic and non-metastatic nodes. • Strong correlations were found between iodine concentration, normalized iodine concentration, slope of the spectral Hounsfield unit curve, dual-energy index, and microvascular density. • DECT qualitative parameters reflect the pathologic changes in lymph nodes to a certain extent, and aid for the detection of metastatic cervical lymph nodes from oral squamous cell carcinoma.
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10
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Ersahin D, Rasla J, Singh A. Dual energy CT applications in oncological imaging. Semin Ultrasound CT MR 2022; 43:344-351. [PMID: 35738819 DOI: 10.1053/j.sult.2022.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Cancer is the second leading cause of death in the United States, killing more than 600.000 people each year.1 Despite several screening programs available, cancer diagnosis is often made incidentally during imaging studies performed for other reasons. Once the diagnosis is made, treatment assessment and surveillance of these patients heavily rely on radiological tools. Computed tomography (CT) in particular is one of the most commonly ordered modalities due to wide availability even in the most remote locations, and fast results. However, conventional CT often cannot definitively characterize a neoplastic lesion unless it was tailored toward answering a specific question. Furthermore, characterizing small lesions can be difficult with CT. An innovative technique called dual-energy CT (DECT) offers solutions to some of the challenges of conventional CT in oncological imaging.
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11
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Al Ashour BH, Azam F, Ibnshamsah F, Alrowais F, Al-Garni A, Al-Shamsi HO, Bukhari N. Metastatic Type II Papillary Renal Cell Carcinoma With Recurrent Complete Responses to Sunitinib: A Case Report With a Literature Review. Cureus 2022; 14:e25541. [PMID: 35800817 PMCID: PMC9246320 DOI: 10.7759/cureus.25541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/31/2022] [Indexed: 11/05/2022] Open
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Geng D, Chen X, Zhao XG, Xu XQ, Su GY, Zhou Y, Chen HB, Wu FY. Laryngeal and hypopharyngeal squamous cell carcinoma: association between quantitative parameters derived from dual-energy CT and histopathological prognostic factors. Acta Radiol 2022:2841851221095237. [PMID: 35502811 DOI: 10.1177/02841851221095237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Dual-energy computed tomography (DECT) can provide objective evaluation of laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC). PURPOSE To investigate the relationship between quantitative parameters acquired from DECT and histopathological prognostic factors in LHSCC. MATERIAL AND METHODS A total of 65 patients with LHSCC who underwent arterial phase and venous phase DECT scans were retrospectively enrolled. Iodine concentration (IC) and normalized IC (NIC) of the tumor were calculated in both the arterial (ICA and NICA) and venous (ICV and NICV) phases, and compared among different pathological grades, T stages, and lymph node stages. Receiver operating characteristic (ROC) curves were generated to evaluate their diagnostic performance. RESULTS There were significantly differences on ICA and NICA among three pathological grades (ICA, P = 0.001; NICA, P = 0.002). For differentiating moderately and poorly differentiated from well-differentiated LHSCC using ICA and NICA, the areas under curve (AUCs) were 0.753 and 0.726, respectively. High T stage (T3/4) LHSCC showed significantly higher ICA (P = 0.012) and NICA (P = 0.005) than low T stage (T1/2) LHSCC. The AUCs of the ICA and NICA were 0.674 and 0.703, respectively, in discriminating high from low T stage LHSCC. Lymph node metastasis (LNM)-positive (N1/2/3) LHSCC showed significantly higher ICA (P = 0.008) and NICA (P = 0.003) than LNM-negative (N0) LHSCC. For discriminating the LNM-positive from the LNM-negative group using ICA and NICA, the AUCs were 0.697 and 0.744, respectively. CONCLUSION ICA and NICA might be helpful in assessing histopathological prognostic factors in patients with LHSCC.
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Affiliation(s)
- Di Geng
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Xi Chen
- Department of Otolaryngology, First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Xing-Guo Zhao
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Xiao-Quan Xu
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Guo-Yi Su
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Yan Zhou
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Hai-Bing Chen
- Department of Otolaryngology, First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
| | - Fei-Yun Wu
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing, PR China
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Xv Y, Lv F, Guo H, Zhou X, Tan H, Xiao M, Zheng Y. Machine learning-based CT radiomics approach for predicting WHO/ISUP nuclear grade of clear cell renal cell carcinoma: an exploratory and comparative study. Insights Imaging 2021; 12:170. [PMID: 34800179 PMCID: PMC8605949 DOI: 10.1186/s13244-021-01107-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 10/09/2021] [Indexed: 12/14/2022] Open
Abstract
Purpose To investigate the predictive performance of machine learning-based CT radiomics for differentiating between low- and high-nuclear grade of clear cell renal cell carcinomas (CCRCCs). Methods This retrospective study enrolled 406 patients with pathologically confirmed low- and high-nuclear grade of CCRCCs according to the WHO/ISUP grading system, which were divided into the training and testing cohorts. Radiomics features were extracted from nephrographic-phase CT images using PyRadiomics. A support vector machine (SVM) combined with three feature selection algorithms such as least absolute shrinkage and selection operator (LASSO), recursive feature elimination (RFE), and ReliefF was performed to determine the most suitable classification model, respectively. Clinicoradiological, radiomics, and combined models were constructed using the radiological and clinical characteristics with significant differences between the groups, selected radiomics features, and a combination of both, respectively. Model performance was evaluated by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analyses. Results SVM-ReliefF algorithm outperformed SVM-LASSO and SVM-RFE in distinguishing low- from high-grade CCRCCs. The combined model showed better prediction performance than the clinicoradiological and radiomics models (p < 0.05, DeLong test), which achieved the highest efficacy, with an area under the ROC curve (AUC) value of 0.887 (95% confidence interval [CI] 0.798–0.952), 0.859 (95% CI 0.748–0.935), and 0.828 (95% CI 0.731–0.929) in the training, validation, and testing cohorts, respectively. The calibration and decision curves also indicated the favorable performance of the combined model. Conclusion A combined model incorporating the radiomics features and clinicoradiological characteristics can better predict the WHO/ISUP nuclear grade of CCRCC preoperatively, thus providing effective and noninvasive assessment. Supplementary Information The online version contains supplementary material available at 10.1186/s13244-021-01107-1.
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Affiliation(s)
- Yingjie Xv
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, Yuzhong, China.,Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, Yuzhong, China
| | - Fajin Lv
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, Yuzhong, China
| | - Haoming Guo
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, Yuzhong, China
| | - Xiang Zhou
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, Yuzhong, China
| | - Hao Tan
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, Yuzhong, China
| | - Mingzhao Xiao
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, Yuzhong, China.
| | - Yineng Zheng
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Chongqing, 400016, Yuzhong, China.
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A Method for Reducing Variability Across Dual-Energy CT Manufacturers in Quantification of Low Iodine Content Levels. AJR Am J Roentgenol 2021; 218:746-755. [PMID: 34668387 DOI: 10.2214/ajr.21.26714] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background: Clinical use of the dual-energy CT (DECT) iodine quantification technique is hindered by between-platform (i.e., across different manufacturers) variability in iodine concentration (IC), particularly at low iodine levels. Objective: To develop in an anthropomorphic phantom a method for reducing between-platform variability in quantification of low iodine content levels using DECT and to evaluate the method's performance in patients undergoing serial clinical DECT examinations on different platforms. Methods: An anthropomorphic phantom in three body sizes, incorporating varied lesion types and scanning conditions, was imaged with three distinct DECT implementations from different manufacturers at varying radiation exposures. A cross-platform iodine quantification model for correcting between-platform variability at low iodine content was developed using the phantom data. The model was tested in a retrospective series of 30 patients (20 men, 10 women; median age, 62 years) who each underwent three serial contrast-enhanced DECT examinations of the abdomen and pelvis (90 scans total) for routine oncology surveillance, using the same three DECT platforms as in the phantom. Estimated accuracy of phantom IC values was summarized using rootmean-squared error (RMSE) relative to known IC. Between-platform variability in patients was summarized using root-mean-square-deviation (RMSD). RMSE and RMSD were compared between platform-based IC (ICPB) and cross-platform IC (ICCP). ICPB was normalized to aorta and portal vein. Results: In the phantom study, mean RMSE of ICPB across platforms and other experimental conditions was 0.65 ± 0.18 mgI/mL compared with 0.40 ± 0.075 mgI/mL for ICCP (38% decrease in mean RMSE; P<.05). Intra-patient between-platform variability across serial DECT examinations was lower for ICPB than ICCP (RMSD: 97% vs 88%; P<.001). Between-platform variability was not reduced by normalization of ICPB to aorta (RMSD: 97% vs 101%; P=.12) or portal vein (RMSD: 97% vs 97%; P=.81). Conclusion: The developed cross-platform method significantly decreased between-platform variability occurring at low iodine content with platform-based DECT iodine quantification. Clinical Impact: With further validation, the cross-platform method, which has been implemented as a webbased app, may expand clinical use of DECT iodine quantification, yielding meaningful IC values that reflect tissue biologic viability or treatment response in patients who undergo serial examinations on different platforms.
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15
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Nogueira MS, Leal LB, Marcarini WD, Pimentel RL, Muller M, Vassallo PF, Campos LCG, Dos Santos L, Luiz WB, Mill JG, Barauna VG, de Carvalho LFDCES. Rapid diagnosis of COVID-19 using FT-IR ATR spectroscopy and machine learning. Sci Rep 2021; 11:15409. [PMID: 34635702 PMCID: PMC8505540 DOI: 10.1038/s41598-021-93511-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 06/10/2021] [Indexed: 12/13/2022] Open
Abstract
Early diagnosis of COVID-19 in suspected patients is essential for contagion control and damage reduction strategies. We investigated the applicability of attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy associated with machine learning in oropharyngeal swab suspension fluid to predict COVID-19 positive samples. The study included samples of 243 patients from two Brazilian States. Samples were transported by using different viral transport mediums (liquid 1 or 2). Clinical COVID-19 diagnosis was performed by the RT-PCR. We built a classification model based on partial least squares (PLS) associated with cosine k-nearest neighbours (KNN). Our analysis led to 84% and 87% sensitivity, 66% and 64% specificity, and 76.9% and 78.4% accuracy for samples of liquids 1 and 2, respectively. Based on this proof-of-concept study, we believe this method could offer a simple, label-free, cost-effective solution for high-throughput screening of suspect patients for COVID-19 in health care centres and emergency departments.
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Affiliation(s)
- Marcelo Saito Nogueira
- Tyndall National Institute, University College Cork, Lee Maltings Complex, Dyke Parade, Cork, T12R5CP, Ireland.
| | - Leonardo Barbosa Leal
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
| | - Wena Dantas Marcarini
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil.,Faculdade Vale do Cricaré, São Matheus, Brazil
| | - Raquel Lemos Pimentel
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
| | - Matheus Muller
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
| | | | | | - Leonardo Dos Santos
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
| | - Wilson Barros Luiz
- Department of Biological Science, Santa Cruz State University, Ilhéus, BA, Brazil
| | - José Geraldo Mill
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
| | - Valerio Garrone Barauna
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
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16
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Nogueira MS, Leal LB, Marcarini WD, Pimentel RL, Muller M, Vassallo PF, Campos LCG, Dos Santos L, Luiz WB, Mill JG, Barauna VG, de Carvalho LFDCES. Rapid diagnosis of COVID-19 using FT-IR ATR spectroscopy and machine learning. Sci Rep 2021. [PMID: 34635702 DOI: 10.1038/s41598-021-93511-] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/10/2023] Open
Abstract
Early diagnosis of COVID-19 in suspected patients is essential for contagion control and damage reduction strategies. We investigated the applicability of attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy associated with machine learning in oropharyngeal swab suspension fluid to predict COVID-19 positive samples. The study included samples of 243 patients from two Brazilian States. Samples were transported by using different viral transport mediums (liquid 1 or 2). Clinical COVID-19 diagnosis was performed by the RT-PCR. We built a classification model based on partial least squares (PLS) associated with cosine k-nearest neighbours (KNN). Our analysis led to 84% and 87% sensitivity, 66% and 64% specificity, and 76.9% and 78.4% accuracy for samples of liquids 1 and 2, respectively. Based on this proof-of-concept study, we believe this method could offer a simple, label-free, cost-effective solution for high-throughput screening of suspect patients for COVID-19 in health care centres and emergency departments.
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Affiliation(s)
- Marcelo Saito Nogueira
- Tyndall National Institute, University College Cork, Lee Maltings Complex, Dyke Parade, Cork, T12R5CP, Ireland.
| | - Leonardo Barbosa Leal
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
| | - Wena Dantas Marcarini
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
- Faculdade Vale do Cricaré, São Matheus, Brazil
| | - Raquel Lemos Pimentel
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
| | - Matheus Muller
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
| | | | | | - Leonardo Dos Santos
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
| | - Wilson Barros Luiz
- Department of Biological Science, Santa Cruz State University, Ilhéus, BA, Brazil
| | - José Geraldo Mill
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
| | - Valerio Garrone Barauna
- Department of Physiological Sciences, Federal University of Espírito Santo (UFES), Vitória, Brazil
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Vascular architectural patterns in clear cell renal cell carcinoma and clear cell papillary renal cell carcinoma. Virchows Arch 2021; 479:1187-1196. [PMID: 34611731 DOI: 10.1007/s00428-021-03214-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 08/18/2021] [Accepted: 09/27/2021] [Indexed: 10/20/2022]
Abstract
Renal cell carcinomas (RCC) are well-vascularized tumors. Although clear cell RCC (CCRCC) show a characteristic vascular network, some cases show overlapping features with other RCC. We aimed to evaluate vascular architectural patterns, microvessel density (MVD), and endothelial cell density (ECD) in CCRCC compared to clear cell papillary RCC (ccpRCC). Thirty-four RCC (17 CCRCC and 17 ccpRCC) were included in the study. CD34 was used to evaluate vascular architectural patterns by microscopic estimation in all cases. CD34, ERG, and Bioquant Osteo 2019 Imaging Analysis Software were used to evaluate MVD and ECD in 17 CCRCC and 15 ccpRCC. Mean MVD was 526.63 in CCRCC vs. 426.18 in ccpRCC (p = 0.16); mean ECD was 937.50 in CCRCC vs. 1060.21 in ccpRCC (p = 0.25). CD34 highlighted four distinct vascular architectural patterns: pseudoacinar, Golgi-like, lacunae, and scattered. Lacunae and pseudoacinar was the most frequent combination in CCRCC; lacunae and Golgi-like was the predominant combination among ccpRCC. Pseudoacinar was most extensive in CCRCC and least in ccpRCC; Golgi-like was predominant in ccpRCC and uncommon in CCRCC. The extent of pseudoacinar and Golgi-like vascular architectural patterns was significantly different between CCRCC and ccpRCC (p < 0.05). Pathologists acquainted with these different vascular architectural patterns may utilize them as an additional tool in the distinction of CCRCC from ccpRCC.
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18
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Zhang B, Wu Q, Qiu X, Ding X, Wang J, Li J, Sun P, Hu X. Effect of spectral CT on tumor microvascular angiogenesis in renal cell carcinoma. BMC Cancer 2021; 21:874. [PMID: 34330234 PMCID: PMC8325217 DOI: 10.1186/s12885-021-08586-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 07/13/2021] [Indexed: 12/12/2022] Open
Abstract
Background To examine the value of energetic-spectrum computed tomography (spectral CT) quantitative parameters in renal cell carcinoma (RCC) microvascular angiogenesis. Methods The authors evaluated 32 patients with pathologically confirmed RCC who underwent triple-phase contrast-enhanced CT with spectral CT imaging mode from January 2017 to December 2019. Quantitative parameters include parameters derived from iodine concentration (IC) and water concentration (WC) of 120 keV monochromatic images. All specimens were evaluated including the microvascular density (MVD), microvascular area (MVA) and so on. The correlation between IC and WC (including average values and random values) with microvascular parameters were analyzed with Pearson or Spearman rank correlation coefficients. Results The MVD of all tumors was 26.00 (15.00–43.75) vessels per field at × 400 magnification. The MVD of RCC correlated positively with the mean IC, mean WC, mean NWC, mean NIC, random IC, random NIC in renal cortical phase, WCD1, WCD2, NWCD2 and ICD1 (Spearman rank correlation coefficients, r range, 0.362–0.533; all p < 0.05). The MVA of all tumors was (16.16 ± 8.98) % per field at × 400 magnification. The MVA of RCC correlated positively with the mean IC, mean WC, mean NWC, mean NIC, random IC, random NIC in renal cortical, mean WC and mean NWC in renal parenchymal phase, WCD1, WCD2, WCD3, NWCD2, and NWCD3 (Pearson or Spearman rank correlation coefficients, r range, 0.357–0.576; all p < 0.05). Microvascular grading correlated positively with the mean NWC, mean NIC and random NIC in renal cortical phase, mean NWC in renal parenchymal phase, NWCD2, WCD3, NWCD3, NICD2 and NICD3 (Spearman rank correlation coefficients, r range, 0.367–0.520; all p < 0.05). As for tumor diameter (55.19 ± 19.15), μm, only NWCD3 was associated with it (Spearman rank correlation coefficients, r = 0.388; p < 0.05). Conclusions ICD and WCD of spectral CT have a potential for evaluating RCC microvascular angiogenesis. MVD, MVA and microvascular grade showed moderate positive correlation with ICD and WCD. ICD displayed more relevant than that of WCD. The parameters of renal cortical phase were the best in three phases. NICD and NWCD manifested stronger correlation with microvascular parameters than that of ICD and WCD.
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Affiliation(s)
- Bei Zhang
- Department of Radiology, First Hospital of Jilin University, No. 1, Xinmin Street, Changchun, Jilin Province, China
| | - Qiong Wu
- Department of Pathology, China-Japan Union Hospital, Jilin University, Changchun, China
| | - Xiang Qiu
- Department of Radiology, First Hospital of Jilin University, No. 1, Xinmin Street, Changchun, Jilin Province, China
| | - Xiaobo Ding
- Department of Radiology, First Hospital of Jilin University, No. 1, Xinmin Street, Changchun, Jilin Province, China
| | - Jin Wang
- Department of Urology Surgery, First Hospital of Jilin University, Changchun, China
| | - Jing Li
- Department of Radiology, First Hospital of Jilin University, No. 1, Xinmin Street, Changchun, Jilin Province, China
| | - Pengfei Sun
- Department of Radiology, First Hospital of Jilin University, No. 1, Xinmin Street, Changchun, Jilin Province, China
| | - Xiaohan Hu
- Department of Radiology, First Hospital of Jilin University, No. 1, Xinmin Street, Changchun, Jilin Province, China.
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MohammadEbrahimi S, Mohammadi A, Bergquist R, Dolatkhah F, Olia M, Tavakolian A, Pishgar E, Kiani B. Epidemiological characteristics and initial spatiotemporal visualisation of COVID-19 in a major city in the Middle East. BMC Public Health 2021; 21:1373. [PMID: 34247616 PMCID: PMC8272989 DOI: 10.1186/s12889-021-11326-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 06/18/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) emerged initially in China in December 2019 causing the COVID-19 disease, which quickly spread worldwide. Iran was one of the first countries outside China to be affected in a major way and is now under the spell of a fourth wave. This study aims to investigate the epidemiological characteristics of COVID-19 cases in north-eastern Iran through mapping the spatiotemporal trend of the disease. METHODS The study comprises data of 4000 patients diagnosed by laboratory assays or clinical investigation from the beginning of the disease on Feb 14, 2020, until May 11, 2020. Epidemiological features and spatiotemporal trends of the disease in the study area were explored by classical statistical approaches and Geographic Information Systems. RESULTS Most common symptoms were dyspnoea (69.4%), cough (59.4%), fever (54.4%) and weakness (19.5%). Approximately 82% of those who did not survive suffered from dyspnoea. The highest Case Fatality Rate (CFR) was related to those with cardiovascular disease (27.9%) and/or diabetes (18.1%). Old age (≥60 years) was associated with an almost five-fold increased CFR. Odds Ratio (OR) showed malignancy (3.8), nervous diseases (2.2), and respiratory diseases (2.2) to be significantly associated with increased CFR with developments, such as hospitalization at the ICU (2.9) and LOS (1.1) also having high correlations. Furthermore, spatial analyses revealed a geographical pattern in terms of both incidence and mortality rates, with COVID-19 first being observed in suburban areas from where the disease swiftly spread into downtown reaching a peak between 25 February to 06 March (4 incidences per km2). Mortality peaked 3 weeks later after which the infection gradually decreased. Out of patients investigated by the spatiotemporal approach (n = 727), 205 (28.2%) did not survive and 66.8% of them were men. CONCLUSIONS Older adults and people with severe co-morbidities were at higher risk for developing serious complications due to COVID-19. Applying spatiotemporal methods to identify the transmission trends and high-risk areas can rapidly be documented, thereby assisting policymakers in designing and implementing tailored interventions to control and prevent not only COVID-19 but also other rapidly spreading epidemics/pandemics.
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Affiliation(s)
- Shahab MohammadEbrahimi
- Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Student Research Committee, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Alireza Mohammadi
- Department of Geography and Urban Planning, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.
| | - Robert Bergquist
- Ingerod, Brastad, Sweden
- (Formerly with the UNICEF/UNDP/World Bank/WHO Special Program for Research and Training in Tropical Diseases, World Health Organization), Geneva, Switzerland
| | - Fatemeh Dolatkhah
- Student Research Committee, Mashhad University of Medical Sciences, Mashhad, Iran
- Department of Microbiology and Virology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mahsa Olia
- Department of Anaesthesiology, School of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Ayoub Tavakolian
- Department of Emergency Medicine, Faculty of Medicine, Sabzevar University of Medical Sciences, Sabzevar, Iran
| | - Elahe Pishgar
- Department of Human Geography and Logistics, Faculty of Earth Science, Shahid Beheshti University, Tehran, Iran
| | - Behzad Kiani
- Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
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Mastrodicasa D, Willemink MJ, Madhuripan N, Chima RS, Ho AA, Ding Y, Marin D, Patel BN. Diagnostic performance of single-phase dual-energy CT to differentiate vascular and nonvascular incidental renal lesions on portal venous phase: comparison with CT. Eur Radiol 2021; 31:9600-9611. [PMID: 34114058 DOI: 10.1007/s00330-021-08097-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 05/13/2021] [Accepted: 05/25/2021] [Indexed: 01/14/2023]
Abstract
OBJECTIVES To determine whether single-phase dual-energy CT (DECT) differentiates vascular and nonvascular renal lesions in the portal venous phase (PVP). Optimal iodine threshold was determined and compared to Hounsfield unit (HU) measurements. METHODS We retrospectively included 250 patients (266 renal lesions) who underwent a clinically indicated PVP abdominopelvic CT on a rapid-kilovoltage-switching single-source DECT (rsDECT) or a dual-source DECT (dsDECT) scanner. Iodine concentration and HU measurements were calculated by four experienced readers. Diagnostic accuracy was determined using biopsy results and follow-up imaging as reference standard. Area under the curve (AUC) was calculated for each DECT scanner to differentiate vascular from nonvascular lesions and vascular lesions from hemorrhagic/proteinaceous cysts. Univariable and multivariable logistic regression analyses evaluated the association between variables and the presence of vascular lesions. RESULTS A normalized iodine concentration threshold of 0.25 mg/mL yielded high accuracy in differentiating vascular and nonvascular lesions (AUC 0.93, p < 0.001), with comparable performance to HU measurements (AUC 0.93). Both iodine concentration and HU measurements were independently associated with vascular lesions when adjusted for age, gender, body mass index, and lesion size (AUC 0.95 and 0.95, respectively). When combined, diagnostic performance was higher (AUC 0.96). Both absolute and normalized iodine concentrations performed better than HU measurements (AUC 0.92 vs. AUC 0.87) in differentiating vascular lesions from hemorrhagic/proteinaceous cysts. CONCLUSION A single-phase (PVP) DECT scan yields high accuracy to differentiate vascular from nonvascular renal lesions. Iodine concentration showed a slightly higher performance than HU measurements in differentiating vascular lesions from hemorrhagic/proteinaceous cysts. KEY POINTS • A single-phase dual-energy CT scan in the portal venous phase differentiates vascular from nonvascular renal lesions with high accuracy (AUC 0.93). • When combined, iodine concentration and HU measurements showed the highest diagnostic performance (AUC 0.96) to differentiate vascular from nonvascular renal lesions. • Compared to HU measurements, iodine concentration showed a slightly higher performance in differentiating vascular lesions from hemorrhagic/proteinaceous cysts.
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Affiliation(s)
- Domenico Mastrodicasa
- Department of Radiology, Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA, 94305, USA
| | - Martin J Willemink
- Department of Radiology, Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA, 94305, USA
| | - Nikhil Madhuripan
- Department of Radiology, Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA, 94305, USA.,Department of Radiology, University of Colorado, 12401 East 17th Avenue, Aurora, CO, 80045, USA
| | - Ranjit Singh Chima
- Department of Radiology, Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA, 94305, USA
| | - Amanzo A Ho
- Department of Radiology, Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA, 94305, USA
| | - Yuqin Ding
- Department of Radiology, Duke University Medical Center, 2301 Erwin Rd, Durham, NC, 27710, USA.,Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai Institute of Medical Imaging, Shanghai, 200032, People's Republic of China
| | - Daniele Marin
- Department of Radiology, Duke University Medical Center, 2301 Erwin Rd, Durham, NC, 27710, USA
| | - Bhavik N Patel
- Department of Radiology, Mayo Clinic, 13400 E Shea Blvd, Scottsdale, AZ, 85259, USA.
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21
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Campi R, Stewart GD, Staehler M, Dabestani S, Kuczyk MA, Shuch BM, Finelli A, Bex A, Ljungberg B, Capitanio U. Novel Liquid Biomarkers and Innovative Imaging for Kidney Cancer Diagnosis: What Can Be Implemented in Our Practice Today? A Systematic Review of the Literature. Eur Urol Oncol 2021; 4:22-41. [DOI: 10.1016/j.euo.2020.12.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Revised: 11/26/2020] [Accepted: 12/14/2020] [Indexed: 12/12/2022]
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22
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Wang L, Zhang Y, Chen Y, Tan J, Wang L, Zhang J, Yang C, Ma Q, Ge Y, Xu Z, Pan Z, Du L, Yan F, Yao W, Zhang H. The Performance of a Dual-Energy CT Derived Radiomics Model in Differentiating Serosal Invasion for Advanced Gastric Cancer Patients After Neoadjuvant Chemotherapy: Iodine Map Combined With 120-kV Equivalent Mixed Images. Front Oncol 2021; 10:562945. [PMID: 33585186 PMCID: PMC7874026 DOI: 10.3389/fonc.2020.562945] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 11/23/2020] [Indexed: 12/26/2022] Open
Abstract
Objectives The aim was to determine whether the dual-energy CT radiomics model derived from an iodine map (IM) has incremental diagnostic value for the model based on 120-kV equivalent mixed images (120 kVp) in preoperative restaging of serosal invasion with locally advanced gastric cancer (LAGC) after neoadjuvant chemotherapy (NAC). Methods A total of 155 patients (110 in the training cohort and 45 in the testing cohort) with LAGC who had standard NAC before surgery were retrospectively enrolled. All CT images were analyzed by two radiologists for manual classification. Volumes of interests (VOIs) were delineated semi-automatically, and 1,226 radiomics features were extracted from every segmented lesion in both IM and 120 kVp images, respectively. Spearman's correlation analysis and the least absolute shrinkage and selection operator (LASSO) penalized logistic regression were implemented for filtering unstable and redundant features and screening out vital features. Two predictive models (120 kVp and IM-120 kVp) based on 120 kVp selected features only and 120 kVp combined with IM selected features were established by multivariate logistic regression analysis. We then build a combination model (ComModel) developed with IM-120 kVp signature and ycT. The performance of these three models and manual classification were evaluated and compared. Result Three radiomics models showed great predictive accuracy and performance in both the training and testing cohorts (ComModel: AUC: training, 0.953, testing, 0.914; IM-120 kVp: AUC: training, 0.953, testing, 0.879; 120 kVp: AUC: training, 0.940, testing, 0.831). All these models showed higher diagnostic accuracy (ComModel: 88.9%, IM-120 kVp: 84.4%, 120 kVp: 80.0%) than manual classification (68.9%) in the testing group. ComModel and IM-120 kVp model had better performances than manual classification both in the training (both p<0.001) and testing cohorts (p<0.001 and p=0.034, respectively). Conclusions Dual-energy CT-based radiomics models demonstrated convincible diagnostic performance in differentiating serosal invasion in preoperative restaging for LAGC. The radiomics features derived from IM showed great potential for improving the diagnostic capability.
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Affiliation(s)
- Lingyun Wang
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yang Zhang
- Department of Radiology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Yong Chen
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingwen Tan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lan Wang
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Zhang
- Department of Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunxue Yang
- Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qianchen Ma
- Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yingqian Ge
- CHN DI CT Collaboration, Siemens Healthineers Ltd, Shanghai, China
| | - Zhihan Xu
- CHN DI CT Collaboration, Siemens Healthineers Ltd, Shanghai, China
| | - Zilai Pan
- Department of Radiology, Ruijin Hospital North, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lianjun Du
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiwu Yao
- Department of Radiology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huan Zhang
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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23
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Wang P, Tang Z, Xiao Z, Wu L, Hong R, Wang J. Dual-energy CT for differentiating early glottic squamous cell carcinoma from chronic inflammation and leucoplakia of vocal cord: comparison with simulated conventional 120 kVp CT. Clin Radiol 2020; 76:238.e17-238.e24. [PMID: 33375985 DOI: 10.1016/j.crad.2020.11.118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 11/25/2020] [Indexed: 11/18/2022]
Abstract
AIM To evaluate the value of dual-energy (DE) computed tomography (CT) in discriminating early glottic squamous cell carcinoma (eGSCC) from chronic inflammation and leucoplakia of the vocal cord, and to compare the diagnostic efficiency of DECT with that of simulated conventional 120 kVp CT. MATERIALS AND METHODS Seventy patients with glottic lesions confirmed by histopathology (38 cases with eGSCC, 11 cases with chronic inflammation, 21 cases with leucoplakia) were enrolled in this prospective study. The DECT-derived parameters were measured and compared using independent sample t-test. Receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic performance, and comparison of the area under the ROC curve (AUC) was made using the Z test to further select the best diagnostic parameters. RESULTS Significantly higher iodine concentration (IC), normalised IC (NIC), effective atomic number (Zeff), 40-100 keV (20 keV-interval), slope(k), and Mix-0.3 values were found in eGSCC than those in chronic inflammation, leucoplakia, and inflammation + leucoplakia (all p<0.05). Compared with attenuation measurement of simulated conventional 120 kVp CT, the NIC, 60 keV values derived from DECT showed significantly higher AUC in discriminating these glottic lesions (p<0.05). CONCLUSIONS DECT is more accurate for differentiating eGSCC from chronic inflammation and leucoplakia when compared with simulated conventional 120 kVp CT.
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Affiliation(s)
- P Wang
- Department of Radiology, Eye & ENT Hospital of Shanghai Medical School, Fudan University, Shanghai, 200031, PR China; Department of Radiology, The Affiliated Renmin Hospital of Jiangsu University, Zhenjiang, Jiangsu, 212002, PR China
| | - Z Tang
- Department of Radiology, Eye & ENT Hospital of Shanghai Medical School, Fudan University, Shanghai, 200031, PR China.
| | - Z Xiao
- Department of Radiology, Eye & ENT Hospital of Shanghai Medical School, Fudan University, Shanghai, 200031, PR China
| | - L Wu
- Department of Otolaryngology, Eye & ENT Hospital of Shanghai Medical School, Fudan University, Shanghai, PR China
| | - R Hong
- Department of Radiology, Eye & ENT Hospital of Shanghai Medical School, Fudan University, Shanghai, 200031, PR China
| | - J Wang
- Department of Otolaryngology, Eye & ENT Hospital of Shanghai Medical School, Fudan University, Shanghai, PR China
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Thiravit S, Brunnquell C, Cai LM, Flemon M, Mileto A. Use of dual-energy CT for renal mass assessment. Eur Radiol 2020; 31:3721-3733. [PMID: 33210200 DOI: 10.1007/s00330-020-07426-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 08/11/2020] [Accepted: 10/14/2020] [Indexed: 12/22/2022]
Abstract
Although dual-energy CT (DECT) may prove useful in a variety of abdominal imaging tasks, renal mass evaluation represents the area where this technology can be most impactful in abdominal imaging compared to routinely performed contrast-enhanced-only single-energy CT exams. DECT post-processing techniques, such as creation of virtual unenhanced and iodine density images, can help in the characterization of incidentally discovered renal masses that would otherwise remain indeterminate based on post-contrast imaging only. The purpose of this article is to review the use of DECT for renal mass assessment, including its benefits and existing limitations. KEY POINTS: • If DECT is selected as the scanning mode for most common abdominal protocols, many incidentally found renal masses can be fully triaged within the same exam. • Virtual unenhanced and iodine density DECT images can provide additional information when renal masses are discovered in the post-contrast-only setting. • For renal mass evaluation, virtual unenhanced and iodine density DECT images should be interpreted side-by-side to troubleshoot pitfalls that can potentially lead to erroneous interpretation.
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Affiliation(s)
- Shanigarn Thiravit
- Department of Radiology, University of Washington School of Medicine, 1959 NE Pacific Street, Box 357115, Seattle, WA, 98195, USA.,Division of Diagnostic Radiology, Department of Radiology, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Christina Brunnquell
- Department of Radiology, University of Washington School of Medicine, 1959 NE Pacific Street, Box 357115, Seattle, WA, 98195, USA
| | - Larry M Cai
- Department of Radiology, University of Washington School of Medicine, 1959 NE Pacific Street, Box 357115, Seattle, WA, 98195, USA
| | - Mena Flemon
- Department of Radiology, University of Washington School of Medicine, 1959 NE Pacific Street, Box 357115, Seattle, WA, 98195, USA
| | - Achille Mileto
- Department of Radiology, University of Washington School of Medicine, 1959 NE Pacific Street, Box 357115, Seattle, WA, 98195, USA.
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Li CX, Lu Q, Huang BJ, Wang PL, Wang WP. Routine or enhanced imaging to differentiate between type 1 and type 2 papillary renal cell carcinoma. Clin Radiol 2020; 76:135-142. [PMID: 33092815 DOI: 10.1016/j.crad.2020.09.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 09/24/2020] [Indexed: 10/23/2022]
Abstract
AIM To investigate imaging features and differentiating qualities of type 1 and type 2 papillary renal cell carcinoma (pRCC) by different imaging techniques. MATERIALS AND METHODS From 2007 to 2019, 107 patients with type 1 pRCC (T1-pRCC) and 147 with type 2 pRCC (T2-pRCC) were included in this retrospective study. All patients underwent conventional ultrasound (US); some also underwent contrast-enhanced ultrasound (CEUS), contrast-enhanced computed tomography (CECT), or contrast-enhanced magnetic resonance imaging (CE-MRI). Tumour Fuhrman grade or World Health Organization (WHO)/International Society of Urological Pathology (ISUP) grade (after June 2016) and invasive ranges were recorded. The two types of pRCC were analysed and compared for imaging features including tumour position, size, margin, echo type, and colour Doppler flow imaging (CDFI) using US as well as enhanced features from CEUS, CECT, or CE-MRI. RESULTS T2-pRCC showed a higher Fuhrman grade (p<0.001) and greater propensity to invade extrarenal tissue (p<0.001) than T1-pRCC. On US imaging, T2-pRCC was more likely to be a cystic-solid lesion (p<0.001), and colour flow with a higher resistance index (RI; p=0.014) was more easily detected (p=0.001) in T2-pRCC than in T1-pRCC. Within contrast-enhanced examinations, more T2-pRCC lesions had blurred tumour borders (p=0.003), hypervascular characteristics (p=0.003), and heterogeneous enhancement (p<0.001) than those of T1-pRCC. CONCLUSIONS T2-pRCC manifests more aggressively than T1-pRCC. T2-pRCC has a higher proportion of hypervascular and heterogeneous enhancement than T1-RCC.
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Affiliation(s)
- C-X Li
- Department of Ultrasound, Zhongshan Hospital, Fudan University, No. 180 of Fenglin Road, Shanghai, 200032, China; Shanghai Institute of Medical Imaging, Fudan University, No. 180 of Fenglin Road, Shanghai, 200032, China
| | - Q Lu
- Department of Ultrasound, Zhongshan Hospital, Fudan University, No. 180 of Fenglin Road, Shanghai, 200032, China
| | - B-J Huang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, No. 180 of Fenglin Road, Shanghai, 200032, China; Shanghai Institute of Medical Imaging, Fudan University, No. 180 of Fenglin Road, Shanghai, 200032, China.
| | - P-L Wang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, No. 180 of Fenglin Road, Shanghai, 200032, China
| | - W-P Wang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, No. 180 of Fenglin Road, Shanghai, 200032, China; Shanghai Institute of Medical Imaging, Fudan University, No. 180 of Fenglin Road, Shanghai, 200032, China.
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Normalized Dual-Energy Iodine Ratio Best Differentiates Renal Cell Carcinoma Subtypes Among Quantitative Imaging Biomarkers From Perfusion CT and Dual-Energy CT. AJR Am J Roentgenol 2020; 215:1389-1397. [PMID: 33052738 DOI: 10.2214/ajr.19.22612] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVE. The objective of our study was to assess and compare the diagnostic accuracy of perfusion CT (PCT) and dual-energy CT (DECT) in differentiating clear cell renal cell carcinoma (ccRCC) from non-ccRCC. MATERIALS AND METHODS. This retrospective study included 51 patients with 52 renal cell carcinomas (RCCs) (36 ccRCCs and 16 non-ccRCCs) who underwent both PCT and DECT before surgery or biopsy between January 2014 and December 2018. Three independent readers measured blood flow, blood volume (BV), and permeability using PCT and iodine concentration (IC) and iodine ratio using DECT. Interreader agreement was calculated using the intraclass correlation coefficient (ICC). Multivariable logistic regression analysis was performed to assess PCT and DECT models. Size-specific dose estimates of the two methods were compared. RESULTS. BV (ICC, 0.93) and iodine ratio (ICC, 0.85) were the most reproducible parameters. Both PCT and DECT were significant models (p < 0.05, all readers) for differentiating ccRCC from non-ccRCC. There was no significant difference in diagnostic accuracy between PCT and DECT (p > 0.05). BV and iodine ratio were independent predictors of nonccRCC (p < 0.05). However, the mean size-specific dose estimate was 16 times lower with DECT than with PCT (p < 0.001). The AUC of iodine ratio was 0.95, and sensitivity, specificity, and accuracy with an iodine ratio cutoff of 63.72% was 0.90, 0.86, and 0.87, respectively. CONCLUSION. PCT and DECT had comparable and high diagnostic accuracy in differentiating RCC subtypes; however, because of the significantly lower radiation dose of DECT, iodine ratio may be used as the best independent predictor.
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