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Wang N, Bing X, Li Y, Yao J, Dai Z, Yu D, Ouyang A. Study of radiomics based on dual-energy CT for nuclear grading and T-staging in renal clear cell carcinoma. Medicine (Baltimore) 2024; 103:e37288. [PMID: 38457546 PMCID: PMC10919525 DOI: 10.1097/md.0000000000037288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 12/23/2023] [Accepted: 01/25/2024] [Indexed: 03/10/2024] Open
Abstract
INTRODUCTION Clear cell renal cell carcinoma (ccRCC) is the most lethal subtype of renal cell carcinoma with a high invasive potential. Radiomics has attracted much attention in predicting the preoperative T-staging and nuclear grade of ccRCC. OBJECTIVE The objective was to evaluate the efficacy of dual-energy computed tomography (DECT) radiomics in predicting ccRCC grade and T-stage while optimizing the models. METHODS 200 ccRCC patients underwent preoperative DECT scanning and were randomized into training and validation cohorts. Radiomics models based on 70 KeV, 100 KeV, 150 KeV, iodine-based material decomposition images (IMDI), virtual noncontrasted images (VNC), mixed energy images (MEI) and MEI + IMDI were established for grading and T-staging. Receiver operating characteristic analysis and decision curve analysis (DCA) were performed. The area under the curve (AUC) values were compared using Delong test. RESULTS For grading, the AUC values of these models ranged from 0.64 to 0.97 during training and from 0.54 to 0.72 during validation. In the validation cohort, the performance of MEI + IMDI model was optimal, with an AUC of 0.72, sensitivity of 0.71, and specificity of 0.70. The AUC value for the 70 KeV model was higher than those for the 100 KeV, 150 KeV, and MEI models. For T-staging, these models achieved AUC values of 0.83 to 1.00 in training and 0.59 to 0.82 in validation. The validation cohort demonstrated AUCs of 0.82 and 0.70, sensitivities of 0.71 and 0.71, and specificities of 0.80 and 0.60 for the MEI + IMDI and IMDI models, respectively. In terms of grading and T-staging, the MEI + IMDI model had the highest AUC in validation, with IMDI coming in second. There were statistically significant differences between the MEI + IMDI model and the 70 KeV, 100 KeV, 150 KeV, MEI, and VNC models in terms of grading (P < .05) and staging (P ≤ .001). DCA showed that both MEI + IDMI and IDMI models outperformed other models in predicting grade and stage of ccRCC. CONCLUSIONS DECT radiomics models were helpful in grading and T-staging of ccRCC. The combined model of MEI + IMDI achieved favorable results.
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Affiliation(s)
- Ning Wang
- Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong Province, P. R. China
| | - Xue Bing
- Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong Province, P. R. China
| | - Yuhan Li
- Department of Radiology, Longkou Traditional Chinese Medicine Hospital, Yantai 265700, Shandong Province, P. R. China
| | - Jian Yao
- Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong Province, P. R. China
| | - Zhengjun Dai
- Scientific Research Department, Huiying Medical Technology Co., Ltd, Beijing 100192, P. R. China
| | - Dexin Yu
- Department of Radiology, Qilu Hospital of Shandong University, Jinan 250012, Shandong Province, P. R. China
| | - Aimei Ouyang
- Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong Province, P. R. China
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Zhu Q, Sun J, Zhu W, Chen W, Ye J. Spectral CT imaging versus conventional CT post-processing technique in differentiating malignant and benign renal tumors. Br J Radiol 2023; 96:20230147. [PMID: 37750940 PMCID: PMC10607386 DOI: 10.1259/bjr.20230147] [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: 02/12/2023] [Revised: 08/02/2023] [Accepted: 08/04/2023] [Indexed: 09/27/2023] Open
Abstract
OBJECTIVE Quantitative comparison of the diagnostic value of spectral CT imaging and conventional CT post-processing technique in differentiating malignant and benign renal tumors. METHODS A total of 209 patients with renal tumors who had undergone CT enhancement were assigned to three groups-clear cell renal cell carcinoma (ccRCC, n = 106), non-ccRCC (n = 60), and benign renal tumor (n = 43) groups. Parametric CT enhancement of each tumor based on spectral CT and conventional CT was performed using in-house software, and the iodine concentration, water content, slope, and density values among the three groups were compared. The receiver operating characteristic (ROC) curve analysis was performed to determine the optimum diagnostic thresholds, the area under the ROC curve (AUC), sensitivity, specificity, and accuracy of the above parameters. RESULTS The iodine concentration, slope, and density values were higher in the ccRCCs group compared to the non-ccRCCs and benign renal tumor groups (p < 0.05). Moreover, the iodine concentration, slope, and density values were higher in benign renal tumors compared to non-ccRCCs (p < 0.05). According to the ROC curve analysis, iodine concentration presented the highest diagnostic efficacy in differentiating ccRCCs/non-ccRCCs from benign renal tumors. The pairwise comparisons of the ROC curves and the diagnostic efficacies revealed that ROI-based CT enhancement was worse than the spectral CT imaging analysis in terms of density (p < 0.05). CONCLUSION Iodine concentration presented the highest diagnostic efficacy in differentiating ccRCCs/non-ccRCCs from benign renal tumors. ADVANCES IN KNOWLEDGE 1. The iodine concentration, slope, and density values were higher for the ccRCCs compared to non-ccRCCs and benign renal tumors.2. Iodine concentration presented the highest diagnostic efficacy in differentiating ccRCCs/non-ccRCCs from benign renal tumors.3. Spectral CT imaging analysis performed better than conventional CT in differentiating malignant and benign renal tumors.
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Affiliation(s)
- Qingqiang Zhu
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Jun Sun
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Wenrong Zhu
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Wenxin Chen
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Jing Ye
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
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Jeong J, Wentland A, Mastrodicasa D, Fananapazir G, Wang A, Banerjee I, Patel BN. Synthetic dual-energy CT reconstruction from single-energy CT Using artificial intelligence. Abdom Radiol (NY) 2023; 48:3537-3549. [PMID: 37665385 DOI: 10.1007/s00261-023-04004-x] [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: 01/20/2023] [Revised: 06/30/2023] [Accepted: 07/03/2023] [Indexed: 09/05/2023]
Abstract
PURPOSE To develop and assess the utility of synthetic dual-energy CT (sDECT) images generated from single-energy CT (SECT) using two state-of-the-art generative adversarial network (GAN) architectures for artificial intelligence-based image translation. METHODS In this retrospective study, 734 patients (389F; 62.8 years ± 14.9) who underwent enhanced DECT of the chest, abdomen, and pelvis between January 2018 and June 2019 were included. Using 70-keV as the input images (n = 141,009) and 50-keV, iodine, and virtual unenhanced (VUE) images as outputs, separate models were trained using Pix2PixHD and CycleGAN. Model performance on the test set (n = 17,839) was evaluated using mean squared error, structural similarity index, and peak signal-to-noise ratio. To objectively test the utility of these models, synthetic iodine material density and 50-keV images were generated from SECT images of 16 patients with gastrointestinal bleeding performed at another institution. The conspicuity of gastrointestinal bleeding using sDECT was compared to portal venous phase SECT. Synthetic VUE images were generated from 37 patients who underwent a CT urogram at another institution and model performance was compared to true unenhanced images. RESULTS sDECT from both Pix2PixHD and CycleGAN were qualitatively indistinguishable from true DECT by a board-certified radiologist (avg accuracy 64.5%). Pix2PixHD had better quantitative performance compared to CycleGAN (e.g., structural similarity index for iodine: 87% vs. 46%, p-value < 0.001). sDECT using Pix2PixHD showed increased bleeding conspicuity for gastrointestinal bleeding and better removal of iodine on synthetic VUE compared to CycleGAN. CONCLUSIONS sDECT from SECT using Pix2PixHD may afford some of the advantages of DECT.
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Affiliation(s)
- Jiwoong Jeong
- Department of Radiology, Mayo Clinic, 13400 E. Shea Blvd, Scottsdale, AZ, 85259, USA.
- School of Computing and Augmented Intelligence, Arizona State University, 699 S Mill Ave, Tempe, AZ, 85281, USA.
| | - Andrew Wentland
- Department of Radiology, University of Wisconsin, 600 Highland Ave, Madison, WI, 53792, USA
| | - Domenico Mastrodicasa
- Department of Radiology, Stanford University, 300 Pasteur Dr., Stanford, CA, 94305, USA
| | - Ghaneh Fananapazir
- Department of Radiology, University of California Davis, 4860 Y Street, Suite 3100, Sacramento, CA, 95817, USA
| | - Adam Wang
- Department of Radiology, Stanford University, 300 Pasteur Dr., Stanford, CA, 94305, USA
| | - Imon Banerjee
- Department of Radiology, Mayo Clinic, 13400 E. Shea Blvd, Scottsdale, AZ, 85259, USA
| | - Bhavik N Patel
- Department of Radiology, Mayo Clinic, 13400 E. Shea Blvd, Scottsdale, AZ, 85259, USA
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Ehrengut C, Denecke T, Meyer HJ. Benefits of Dual-Layer Spectral CT Imaging in Staging and Preoperative Evaluation of Pancreatic Ductal Adenocarcinoma. J Clin Med 2023; 12:6145. [PMID: 37834789 PMCID: PMC10573525 DOI: 10.3390/jcm12196145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 09/10/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
Imaging of pancreatic malignancies is challenging but has a major impact on the patients therapeutic approach and outcome. In particular with pancreatic ductal adenocarcinoma (PDAC), usually a hypovascularized tumor, conventional CT imaging can be prone to errors in determining tumor extent and presence of metastatic disease. Dual-layer spectral detector CT (SDCT) is an emerging technique for acquiring spectral information without the need for prospective patient selection or specific protocols, with a detector capable of differentiating high- and low-energy photons to acquire full spectral images. In this review, we present the diagnostic benefits and capabilities of modern SDCT imaging with a focus on PDAC. We highlight the most useful virtual reconstructions in oncologic imaging and their benefits in staging and assessment of resectability in PDAC, including the assessment of tumor extent, vascular infiltration, and metastatic disease. We present imaging examples on a latest-generation SDCT scanner.
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Affiliation(s)
| | | | - Hans-Jonas Meyer
- Klinik und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Leipzig, 04103 Leipzig, Germany; (C.E.)
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Schade KA, Mergen V, Sartoretti T, Alkadhi H, Euler A. Pseudoenhancement in Cystic Renal Lesions - Impact of Virtual Monoenergetic Images of Photon-Counting Detector CT on Lesion Classification. Acad Radiol 2023; 30 Suppl 1:S305-S313. [PMID: 37150736 DOI: 10.1016/j.acra.2023.04.005] [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: 03/07/2023] [Revised: 03/30/2023] [Accepted: 04/03/2023] [Indexed: 05/09/2023]
Abstract
RATIONALE AND OBJECTIVES To investigate the impact of virtual monoenergetic images (VMI) from photon-counting detector CT (PCD-CT) on the enhancement and classification of renal cysts. MATERIALS AND METHODS Adults with renal cysts (≥7 mm) who received a triphasic examination on a clinical PCD-CT (120 kVp; IQ level 68) between July 2021 and March 2022 were retrospectively identified. Only non-enhancing cysts (enhancement<10 HU between unenhanced and venous phase at 70 keV) were included. VMI from 40 to 190 keV with increments of 10 keV were reconstructed from the venous phase. Enhancement was measured to classify each lesion as non-enhancing (<10 HU), equivocally enhancing (10-19 HU), and definitely enhancing (≥20 HU). Classification changes as a function of VMI were assessed. Pearson correlation coefficient, the Kruskal-Wallis and the Chi-square test were used. RESULTS A total of 86 patients (mean age, 74 ± 9 years; 74 male) with 160 non-enhancing renal cysts (17.6 ± 10 mm) were included. CT attenuation of the cysts increased from higher to lower VMI levels with a mean attenuation of 4 ± 11 HU at 190 keV to 36 ± 17 HU at 40 keV. Mean attenuation of the renal parenchyma was 43 ± 4 HU at 190 keV and 414 ± 71 HU at 40 keV. No cyst exhibited enhancement from 70 keV to 190 keV. At 40, 50, and 60 keV, 35% (56/160), 29% (47/160) and 9% (15/160) of cysts showed equivocal and 46% (74/160), 10% (16/160), and 0% (0/160) definite enhancement, respectively. There was no significant influence of size (P=.13), cyst location (P=.9) and BMI (P=.19) on enhancement classification. CONCLUSION VMI has a relevant impact on enhancement and classification of renal cysts with misclassification in a large number of cases at energy levels below 70 keV.
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Affiliation(s)
- Katharina Alexandra Schade
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland (K.A.S., V.M., T.S., H.A., A.E.)
| | - Victor Mergen
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland (K.A.S., V.M., T.S., H.A., A.E.)
| | - Thomas Sartoretti
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland (K.A.S., V.M., T.S., H.A., A.E.)
| | - Hatem Alkadhi
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland (K.A.S., V.M., T.S., H.A., A.E.)
| | - André Euler
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland (K.A.S., V.M., T.S., H.A., A.E.); Institute of Radiology, Kantonsspital Baden, Baden, Switzerland (A.E.).
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Agostini A, Borgheresi A, Mariotti F, Ottaviani L, Carotti M, Valenti M, Giovagnoni A. New frontiers in oncological imaging with Computed Tomography: from morphology to function. Semin Ultrasound CT MR 2023; 44:214-227. [DOI: 10.1053/j.sult.2023.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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Sauerbeck J, Adam G, Meyer M. Spectral CT in Oncology. ROFO-FORTSCHR RONTG 2023; 195:21-29. [PMID: 36167316 DOI: 10.1055/a-1902-9949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
BACKGROUND Spectral CT is gaining increasing clinical importance with multiple potential applications, including oncological imaging. Spectral CT-specific image data offers multiple advantages over conventional CT image data through various post-processing algorithms, which will be highlighted in the following review. METHODOLOGY The purpose of this review article is to provide an overview of potential useful oncologic applications of spectral CT and to highlight specific spectral CT pitfalls. The technical background, clinical advantages of primary and follow-up spectral CT exams in oncology, and the application of appropriate spectral tools will be highlighted. RESULTS/CONCLUSIONS Spectral CT imaging offers multiple advantages over conventional CT imaging, particularly in the field of oncology. The combination of virtual native and low monoenergetic images leads to improved detection and characterization of oncologic lesions. Iodine-map images may provide a potential imaging biomarker for assessing treatment response. KEY POINTS · The most important spectral CT reconstructions for oncology imaging are virtual unenhanced, iodine map, and virtual monochromatic reconstructions.. · The combination of virtual unenhanced and low monoenergetic reconstructions leads to better detection and characterization of the vascularization of solid tumors.. · Iodine maps can be a surrogate parameter for tumor perfusion and potentially used as a therapy monitoring parameter.. · For radiotherapy planning, the relative electron density and the effective atomic number of a tissue can be calculated.. CITATION FORMAT · Sauerbeck J, Adam G, Meyer M. Onkologische Bildgebung mittels Spektral-CT. Fortschr Röntgenstr 2023; 195: 21 - 29.
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Affiliation(s)
- Julia Sauerbeck
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, Hamburg, Germany
| | - Gerhard Adam
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, Hamburg, Germany
| | - Mathias Meyer
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, Hamburg, Germany
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Virtual monochromatic spectral attenuation curve analysis for evaluation of incidentally detected small renal lesions using rapid kilovoltage-switching dual-energy computed tomography. ABDOMINAL RADIOLOGY (NEW YORK) 2022; 47:3817-3827. [PMID: 35945346 DOI: 10.1007/s00261-022-03634-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 07/21/2022] [Accepted: 07/26/2022] [Indexed: 01/18/2023]
Abstract
PURPOSE To determine whether the spectral attenuation curve on a rapid kilovoltage-switching dual-energy computed tomography (DECT) scan can distinguish enhancing from nonenhancing incidental small (1-4 cm) renal lesions compared with conventional single-energy attenuation changes. METHODS This retrospective study enrolled 46 patients with 78 renal lesions (24 enhancing; 54 nonenhancing) who underwent DECT with DE mode performed during the portovenous or nephrographic phase. Final diagnosis of enhancing and nonenhancing masses was confirmed by pathology or imaging following the established criteria. Virtual monochromatic images (VMI) were reconstructed, and the slopes between the VMI dataset at 40-70 keV (Slope HU40-70), 40-100 keV (Slope HU40-100), and 40-140 keV (Slope HU40-140) were measured. Visual assessment of the curve pattern was recorded. Diagnostic accuracies were calculated with a cross-validated Mann-Whitney U test, and correlations of quantitative spectral parameters and intraclass correlation coefficient (ICC) were calculated using Spearman's rho correlation. RESULTS All quantitative and qualitative spectral analysis parameters significantly differentiated the enhancing and nonenhancing lesions (P < 0.001). The optimal slope thresholds calculated by cross-validation for Slope HU40-70, Slope HU40-100, and Slope HU40-140 were 3.0, 1.8 and 1.2, respectively for reader 1 and 3.0, 1.9 and 1.15, respectively for reader 2. Using a slope threshold at all datasets yielded a high diagnostic accuracy of 96 for reader 1 and 95 for reader 2. Using a ∆HU threshold of 20 HU yielded an accuracy of 100. Visual analysis of the curve pattern also yielded high accuracy of 94. CONCLUSIONS The spectral attenuation curve on rapid kilovoltage-switching DECT gives excellent diagnostic accuracy differentiating between incidental enhancing and nonenhancing renal lesions. This benefit of DECT will be most helpful when the true unenhanced phase is not performed.
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Singh R, Rai R, Mroueh N, Kambadakone A. Role of Dual Energy Computed Tomography in Inflammatory Bowel Disease. Semin Ultrasound CT MR 2022; 43:320-332. [PMID: 35738817 DOI: 10.1053/j.sult.2022.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Dual-energy computed tomography (DECT), which allows material-based differential X-ray absorption behavior from near simultaneously acquired low- and high-kilovolt datasets is finding increasing applications in the evaluation of bowel diseases. In patients with inflammatory bowel disease, DECT techniques permit both qualitative and quantitative assessment. Particularly in patients with Crohn's disease, monoenergetic and iodine specific images have been explored. This article focuses on the principles and applications of DECT in inflammatory bowel disease along with review of its limitations and challenges.
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Affiliation(s)
- Ramandeep Singh
- Department of Radiology, Massachusetts General Hospital, Boston, MA
| | - Rubal Rai
- Department of Radiology, Massachusetts General Hospital, Boston, MA
| | - Nayla Mroueh
- Department of Radiology, Massachusetts General Hospital, Boston, MA
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Dual-layer spectral detector CT for contrast agent concentration, dose and injection rate reduction: Utility in imaging of the superior mesenteric artery. Eur J Radiol 2022; 150:110246. [DOI: 10.1016/j.ejrad.2022.110246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 02/12/2022] [Accepted: 03/07/2022] [Indexed: 11/20/2022]
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Euler A, Zadory M, Breiding PS, Sartoretti T, Ghafoor S, Froehlich JM, Donati OF. Realistic Kidney Tissue Surrogates for Multienergy Computed Tomography-Feasibility and Estimation of Energy-Dependent Attenuation Thresholds for Renal Lesion Enhancement in Low-kV and Virtual Monoenergetic Imaging. Invest Radiol 2021; 56:791-798. [PMID: 33899757 DOI: 10.1097/rli.0000000000000790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE The aims of this study were to assess if kidney tissue surrogates (KTSs) are superior to distilled water-iodine solutions in the emulation of energy-dependent computed tomography (CT) attenuation characteristics of renal parenchyma and to estimate attenuation thresholds for definite lesion enhancement for low-kV single-energy and low-keV dual-energy virtual monoenergetic imaging. METHODS A water-filled phantom (diameter, 30 cm) with multiple vials was imaged on a dual-source dual-energy CT (DS-DE) and a single-source split-filter dual-energy CT (SF-DE), both in single-energy mode at 80, 100, 120, 140 kVp and in dual-energy mode at 80/Sn150, 90/Sn150, and 100/Sn150 kVp for DS-DE and AuSn120 kVp for SF-DE. Single-energy images, linear-blended dual-energy images, and virtual monoenergetic imaging at energy levels from 40 to 190 keV were reconstructed. First, attenuation characteristics of KTS in solid and liquid consistencies were compared. Second, solid KTSs were developed to match the CT attenuation of unenhanced renal parenchyma at 120 kVp as retrospectively measured in 100 patients. Third, CT attenuation of KTS-iodine and water-iodine solutions at 8 different iodine concentrations (0-10 mg I/mL) were compared as a function of tube voltage and of keV level using multiple linear regression models. Energy-dependent attenuation thresholds for definite lesion enhancement were calculated. RESULTS Unenhanced renal parenchyma at 120 kVp measured on average 30 HU on both scanners in the patient cohort. Solid KTS with a water content of 80% emulated the attenuation of unenhanced renal parenchyma (30 HU) more accurately compared with water-iodine solutions (0 HU). Attenuation difference between KTS-iodine and water-iodine solutions converged with increasing iodine concentration and decreasing x-ray energy due to beam-hardening effects. A slight attenuation difference of approximately 2 HU was found between the 2 CT scanners. Attenuation thresholds for definite lesion enhancement were dependent on tube voltage and keV level and ranged from 16.6 to 33.2 HU and 3.2 to 68.3 HU for single-energy and dual-energy CT scan modes for DS-DE and from 16.1 to 34.3 HU and 3.3 to 92.2 HU for SF-DE. CONCLUSIONS Kidney tissue surrogates more accurately emulate the energy-dependent CT attenuation characteristics of renal parenchyma for multienergy CT compared with conventional water-iodine approaches. Energy-dependent thresholds for definite lesion enhancement could facilitate lesion characterization when imaging at different energies than the traditional 120 kVp.
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Affiliation(s)
- André Euler
- From the Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, University of Zurich
| | | | - Philipe Sebastian Breiding
- From the Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, University of Zurich
| | | | - Soleen Ghafoor
- From the Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, University of Zurich
| | | | - Olivio Fabrizio Donati
- From the Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, University of Zurich
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Cao Y, Zhang J, Bao H, Zhang G, Yan X, Wang Z, Ren J, Chai Y, Zhao Z, Zhou J. Development of a Nomogram Combining Clinical Risk Factors and Dual-Energy Spectral CT Parameters for the Preoperative Prediction of Lymph Node Metastasis in Patients With Colorectal Cancer. Front Oncol 2021; 11:689176. [PMID: 34631524 PMCID: PMC8493878 DOI: 10.3389/fonc.2021.689176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 09/02/2021] [Indexed: 11/13/2022] Open
Abstract
Objective This study aimed to develop a dual-energy spectral computed tomography (DESCT) nomogram that incorporated both clinical factors and DESCT parameters for individual preoperative prediction of lymph node metastasis (LNM) in patients with colorectal cancer (CRC). Material and Methods We retrospectively reviewed 167 pathologically confirmed patients with CRC who underwent enhanced DESCT preoperatively, and these patients were categorized into training (n = 117) and validation cohorts (n = 50). The monochromatic CT value, iodine concentration value (IC), and effective atomic number (Eff-Z) of the primary tumors were measured independently in the arterial phase (AP) and venous phase (VP) by two radiologists. DESCT parameters together with clinical factors were input into the prediction model for predicting LNM in patients with CRC. Logistic regression analyses were performed to screen for significant predictors of LNM, and these predictors were presented as an easy-to-use nomogram. The receiver operating characteristic curve and decision curve analysis (DCA) were used to evaluate the clinical usefulness of the nomogram. Results The logistic regression analysis showed that carcinoembryonic antigen, carbohydrate antigen 199, pericolorectal fat invasion, ICAP, ICVP, and Eff-ZVP were independent predictors in the predictive model. Based on these predictors, a quantitative nomogram was developed to predict individual LNM probability. The area under the curve (AUC) values of the nomogram were 0.876 in the training cohort and 0.852 in the validation cohort, respectively. DCA showed that our nomogram has outstanding clinical utility. Conclusions This study presents a clinical nomogram that incorporates clinical factors and DESCT parameters and can potentially be used as a clinical tool for individual preoperative prediction of LNM in patients with CRC.
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Affiliation(s)
- Yuntai Cao
- Department of Radiology, Affiliated Hospital of Qinghai University, Xining, China.,Second Clinical School, Lanzhou University, Lanzhou, China.,Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China.,Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China.,Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
| | - Jing Zhang
- Department of Radiology, The Fifth Affiliated Hospital of Zunyi Medical University, Zhuhai, China
| | - Haihua Bao
- Department of Radiology, Affiliated Hospital of Qinghai University, Xining, China
| | - Guojin Zhang
- Department of Radiology, Sichuan Provincial People's Hospital, Chengdu, China
| | - Xiaohong Yan
- Department of Critical Medicine, Affiliated Hospital of Qinghai University, Xining, China
| | - Zhan Wang
- Department of Hepatopancreatobiliary Surgery, Affiliated Hospital of Qinghai University, Xining, China
| | - Jialiang Ren
- Department of Pharmaceuticals Diagnosis, General Electrics (GE) Healthcare, Beijing, China
| | - Yanjun Chai
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China
| | - Zhiyong Zhao
- Second Clinical School, Lanzhou University, Lanzhou, China.,Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China.,Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China.,Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
| | - Junlin Zhou
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China.,Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China.,Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
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Shen H, Yuan X, Liu D, Tu C, Wang X, Liu R, Wang X, Lan X, Fu K, Zhang J. Multiparametric dual-energy CT to differentiate stage T1 nasopharyngeal carcinoma from benign hyperplasia. Quant Imaging Med Surg 2021; 11:4004-4015. [PMID: 34476185 DOI: 10.21037/qims-20-1269] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 04/19/2021] [Indexed: 12/30/2022]
Abstract
Background Stage T1 nasopharyngeal carcinoma (NPCT1) and benign hyperplasia (BH) are 2 common causes of nasopharyngeal mucosa/submucosa thickening without specific clinical symptoms. The treatment management of these 2 entities is significantly different. Reliable differentiation between the 2 entities is critical for the treatment decision and prognosis of patients. Therefore, our study aims to explore the optimal energy level of noise-optimized virtual monoenergetic images [VMI (+)] derived from dual-energy computed tomography (DECT) to display NPCT1 and BH and to explore the clinical value of DECT for differentiating these 2 diseases. Methods A total of 91 patients (44 NPCT1, 47 BH) were enrolled. The demarcation of the lesion margins and overall image quality, noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were evaluated for 40-80 kiloelectron volts (keV) VMIs (+) and polyenergetic images in the contrast-enhanced phase. Image features were assessed in the contrast-enhanced images with optimal visualization of NPCT1 and BH. The demarcation of NPCT1 and BH in iodine-water maps was also assessed. The contrast-enhanced images were used to calculate the slope of the spectral Hounsfield unit curve (λHU) and normalized iodine concentration (NIC). The nonenhanced phase images were used to calculate the normalized effective atomic number (NZeff). The attenuation values on 40-80 keV VMIs (+) in the contrast-enhanced phase were recorded. The diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis. Results The 40 keV VMI (+) in the enhanced phase yielded higher demarcation of the lesion margins scores, overall image quality scores, noise, SNR, and CNR values than 50-80 keV VMIs (+) and polyenergetic images. NPCT1 yielded higher attenuation values on VMI (+) at 40 keV (A40), NIC, λHU, and NZeff values than BH. The multivariate logistic regression model combining image features (tumor symmetry) with quantitative parameters (A40, NIC, λHU, and NZeff) yielded the best performance for differentiating the 2 diseases (AUC: 0.963, sensitivity: 89.4%, specificity: 93.2%). Conclusions The combination of DECT-derived image features and quantitative parameters contributed to the differentiation between NPCT1 and BH.
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Affiliation(s)
- Hesong Shen
- Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - Xiaoqian Yuan
- Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - Daihong Liu
- Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - Chunrong Tu
- Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - Xing Wang
- Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - Renwei Liu
- Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - Xiaoxia Wang
- Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - Xiaosong Lan
- Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - Kaiwen Fu
- Department of Pathology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
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Han D, Yu Y, He T, Yu N, Dang S, Wu H, Ren J, Duan X. Effect of radiomics from different virtual monochromatic images in dual-energy spectral CT on the WHO/ISUP classification of clear cell renal cell carcinoma. Clin Radiol 2021; 76:627.e23-627.e29. [PMID: 33985770 DOI: 10.1016/j.crad.2021.02.033] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 02/10/2021] [Indexed: 12/24/2022]
Abstract
AIM To investigate the effect of radiomics obtained from different virtual monochromatic images (VMIs) in dual-energy spectral computed tomography (CT) on the World Health Organization/International Association for Urological Pathology (WHO/ISUP) classification of clear cell renal cell carcinoma (ccRCC). MATERIALS AND METHODS A retrospective study of 99 ccRCC patients who underwent contrast-enhanced dual-energy CT was undertaken. ccRCC was confirmed at surgery or biopsy and graded according to the WHO/ISUP pathological grading criteria as low grade (n=68, grade I and II) or high grade (n=31, grade III and IV). Radiomics risk scores (RRSs) for differentiating high and low grades of ccRCC were constructed from 11 sets of VMI in (40-140 keV, 10 keV interval) the cortical phase. Receiver operating characteristic (ROC) curves were drawn and the area under the curves (AUCs) was calculated to evaluate the discriminatory power of RRS for each VMI. The Hosmer-Lemeshow test was used to evaluate the goodness-of-fit of each model and the decision curve was used to analyse its net benefit to patients. RESULTS The AUC values for distinguishing low-from high-grade ccRCC with RRS of 40-140 keV VMIs were all >0.920. The Hosmer-Lemeshow test showed that the p-values of RRS of VMIs were >0.05, suggesting good fits. In the decision curve analysis, RRS from the 40-140 keV VMIs had similar decision curves and provided better net benefits than considering all patients either as high-grade or low-grade. CONCLUSIONS The RRS obtained from multiple VMIs in dual-energy spectral CT have high diagnostic efficiencies for distinguishing between low- and high-grade ccRCC with no significant differences between different VMIs.
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Affiliation(s)
- D Han
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Y Yu
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - T He
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - N Yu
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - S Dang
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - H Wu
- Pathology Department, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - J Ren
- GE Healthcare China, Beijing, China
| | - X Duan
- Department of Medical Image, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
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Parakh A, Lennartz S, An C, Rajiah P, Yeh BM, Simeone FJ, Sahani DV, Kambadakone AR. Dual-Energy CT Images: Pearls and Pitfalls. Radiographics 2021; 41:98-119. [PMID: 33411614 PMCID: PMC7853765 DOI: 10.1148/rg.2021200102] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 07/10/2020] [Accepted: 07/16/2020] [Indexed: 01/10/2023]
Abstract
Dual-energy CT (DECT) is a tremendous innovation in CT technology that allows creation of numerous imaging datasets by enabling discrete acquisitions at more than one energy level. The wide range of images generated from a single DECT acquisition provides several benefits such as improved lesion detection and characterization, superior determination of material composition, reduction in the dose of iodine, and more robust quantification. Technological advances and the proliferation of various processing methods have led to the availability of diverse vendor-based DECT approaches, each with a different acquisition and image reconstruction process. The images generated from various DECT scanners differ from those from conventional single-energy CT because of differences in their acquisition techniques, material decomposition methods, image reconstruction algorithms, and postprocessing methods. DECT images such as virtual monochromatic images, material density images, and virtual unenhanced images have different imaging appearances, texture features, and quantitative capabilities. This heterogeneity creates challenges in their routine interpretation and has certain associated pitfalls. Some artifacts such as residual iodine on virtual unenhanced images and an appearance of pseudopneumatosis in a gas-distended bowel loop on material-density iodine images are specific to DECT, while others such as pseudoenhancement seen on virtual monochromatic images are also observed at single-energy CT. Recognizing the potential pitfalls associated with DECT is necessary for appropriate and accurate interpretation of the results of this increasingly important imaging tool. Online supplemental material is available for this article. ©RSNA, 2021.
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Affiliation(s)
- Anushri Parakh
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (A.P., S.L., F.J.S., A.R.K.); Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, Calif (C.A., B.M.Y.); Department of Radiology, Mayo Clinic, Rochester, Minn (P.R.); Department of Radiology, University of Washington, Seattle, Wash (D.V.S.); and Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany (S.L.)
| | - Simon Lennartz
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (A.P., S.L., F.J.S., A.R.K.); Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, Calif (C.A., B.M.Y.); Department of Radiology, Mayo Clinic, Rochester, Minn (P.R.); Department of Radiology, University of Washington, Seattle, Wash (D.V.S.); and Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany (S.L.)
| | - Chansik An
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (A.P., S.L., F.J.S., A.R.K.); Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, Calif (C.A., B.M.Y.); Department of Radiology, Mayo Clinic, Rochester, Minn (P.R.); Department of Radiology, University of Washington, Seattle, Wash (D.V.S.); and Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany (S.L.)
| | - Prabhakar Rajiah
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (A.P., S.L., F.J.S., A.R.K.); Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, Calif (C.A., B.M.Y.); Department of Radiology, Mayo Clinic, Rochester, Minn (P.R.); Department of Radiology, University of Washington, Seattle, Wash (D.V.S.); and Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany (S.L.)
| | - Benjamin M. Yeh
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (A.P., S.L., F.J.S., A.R.K.); Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, Calif (C.A., B.M.Y.); Department of Radiology, Mayo Clinic, Rochester, Minn (P.R.); Department of Radiology, University of Washington, Seattle, Wash (D.V.S.); and Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany (S.L.)
| | - Frank J. Simeone
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (A.P., S.L., F.J.S., A.R.K.); Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, Calif (C.A., B.M.Y.); Department of Radiology, Mayo Clinic, Rochester, Minn (P.R.); Department of Radiology, University of Washington, Seattle, Wash (D.V.S.); and Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany (S.L.)
| | - Dushyant V. Sahani
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (A.P., S.L., F.J.S., A.R.K.); Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, Calif (C.A., B.M.Y.); Department of Radiology, Mayo Clinic, Rochester, Minn (P.R.); Department of Radiology, University of Washington, Seattle, Wash (D.V.S.); and Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany (S.L.)
| | - Avinash R. Kambadakone
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (A.P., S.L., F.J.S., A.R.K.); Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, Calif (C.A., B.M.Y.); Department of Radiology, Mayo Clinic, Rochester, Minn (P.R.); Department of Radiology, University of Washington, Seattle, Wash (D.V.S.); and Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany (S.L.)
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Ma YC, Zhang SH, Xie ZY, Guo F, Chen AQ. Comparison of spectral computed tomography imaging parameters between squamous cell carcinoma and adenocarcinoma at the gastroesophageal junction. Technol Health Care 2020; 29:619-627. [PMID: 33285653 DOI: 10.3233/thc-202343] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To compare the spectral computed tomography (CT) imaging parameters between squamous cell carcinoma (SCC) and adenocarcinoma (AC) at the gastroesophageal junction (GEJ). METHODS A total of 80 patients were enrolled in this retrospective study. Among them, 35 were diagnosed with SCC (SCC group) and 45 were diagnosed with AC (AC group). All patients underwent an enhanced scan with spectral CT. The following CT imaging parameters were evaluated: iodine concentration (IC), water content (WC), effective atomic number (Eff-Z) and slope of the spectral HU curve (λHU) of lesions. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of spectral CT imaging parameters for diagnosis of SCC and AC. RESULTS Patients with SCC had lower IC, Eff-Z, and λHU in arterial phase and venous phase compared with AC (p< 0.05). There were no significant differences in WC between the two groups. ROC curve analyses revealed that IC, Eff-Z, and λHU in arterial phase and venous phase were predictors for diagnosis of SCC and AC (AUC > 0.5). Moreover, the IC, Eff-Z and λHU in venous phase had better differential diagnostic performances than that in arterial phase. CONCLUSIONS Spectral CT could be useful in the differential diagnosis of SCC and AC at the GEJ. Therefore, a routine spectral CT scan is recommended for patients with carcinoma of the GEJ.
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Affiliation(s)
- Yi-Chuan Ma
- Department of Radiology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China
| | - Shun-Hua Zhang
- Department of Medical Imaging, Bengbu Medical College, Bengbu, Anhui, China
| | - Zong-Yu Xie
- Department of Radiology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China
| | - Fei Guo
- Department of Radiology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China
| | - Ai-Qi Chen
- Department of Radiology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China
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Building a dual-energy CT service line in abdominal radiology. Eur Radiol 2020; 31:4330-4339. [PMID: 33210201 DOI: 10.1007/s00330-020-07441-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 10/08/2020] [Accepted: 10/23/2020] [Indexed: 10/23/2022]
Abstract
As the access of radiology practices to dual-energy CT (DECT) has increased worldwide, seamless integration into clinical workflows and optimized use of this technology are desirable. In this article, we provide basic concepts of commercially available DECT hardware implementations, discuss financial and logistical aspects, provide tips for protocol building and image routing strategies, and review radiation dose considerations to establish a DECT service line in abdominal imaging. KEY POINTS: • Tube-based and detector-based DECT implementations with varying features and strengths are available on the imaging market. • Thorough assessment of financial and logistical aspects is key to successful implementation of a DECT service line. • Optimized protocol building and image routing strategies are of critical importance for effective use and seamless inception of DECT in routine clinical workflows.
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18
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Krishna S, Schieda N, Pedrosa I, Hindman N, Baroni RH, Silverman SG, Davenport MS. Update on MRI of Cystic Renal Masses Including Bosniak Version 2019. J Magn Reson Imaging 2020; 54:341-356. [PMID: 33009722 DOI: 10.1002/jmri.27364] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 08/27/2020] [Accepted: 08/28/2020] [Indexed: 12/15/2022] Open
Abstract
Incidental cystic renal masses are common, usually benign, and almost always indolent. Since 1986, the Bosniak classification has been used to express the risk of malignancy in a cystic renal mass detected at imaging. Historically, magnetic resonance imaging (MRI) was not included in that classification. The proposed Bosniak v.2019 update has formally incorporated MRI, included definitions of imaging terms designed to improve interobserver agreement and specificity for malignancy, and incorporated a variety of masses that were incompletely defined or not included in the original classification. For example, at unenhanced MRI, homogeneous masses markedly hyperintense at T2 -weighted imaging (similar to cerebrospinal fluid) and homogeneous masses markedly hyperintense at fat suppressed T1 -weighted imaging (approximately ≥2.5 times more intense than adjacent renal parenchyma) are classified as Bosniak II and may be safely ignored, even when they have not been imaged with a complete renal mass MRI protocol. MRI has specific advantages and is recommended to evaluate masses that at computed tomography (CT) 1) have abundant thick or nodular calcifications; 2) are homogeneous, hyperattenuating, ≥3 cm, and nonenhancing; or 3) are heterogeneous and nonenhancing. Although MRI is generally excellent for characterizing cystic renal masses, there are unique weaknesses of MRI that bear consideration. These details and others related to MRI of cystic renal masses are described in this review, with an emphasis on Bosniak v.2019. A website (https://bosniak-calculator.herokuapp.com/) and mobile phone apps named "Bosniak Calculator" have been developed for ease of assignment of Bosniak classes. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.
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Affiliation(s)
- Satheesh Krishna
- Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Nicola Schieda
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Ivan Pedrosa
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Nicole Hindman
- Department of Radiology, New York University Langone Medical Center, New York, New York, USA
| | - Ronaldo H Baroni
- Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Stuart G Silverman
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Matthew S Davenport
- Departments of Radiology and Urology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
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Han D, Yu Y, Yu N, Dang S, Wu H, Jialiang R, He T. Prediction models for clear cell renal cell carcinoma ISUP/WHO grade: comparison between CT radiomics and conventional contrast-enhanced CT. Br J Radiol 2020; 93:20200131. [PMID: 32706977 DOI: 10.1259/bjr.20200131] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
OBJECTIVE Comparing the prediction models for the ISUP/WHO grade of clear cell renal cell carcinoma (ccRCC) based on CT radiomics and conventional contrast-enhanced CT (CECT). METHODS The corticomedullary phase images of 119 cases of low-grade (I and II) and high-grade (III and IV) ccRCC based on 2016 ISUP/WHO pathological grading criteria were analyzed retrospectively. The patients were randomly divided into training and validation set by stratified sampling according to 7:3 ratio. Prediction models of ccRCC differentiation were constructed using CT radiomics and conventional CECT findings in the training setandwere validated using validation set. The discrimination, calibration, net reclassification index (NRI) and integrated discrimination improvement index (IDI) of the two prediction models were further compared. The decision curve was used to analyze the net benefit of patients under different probability thresholds of the two models. RESULTS In the training set, the C-statistics of radiomics prediction model was statistically higher than that of CECT (p < 0.05), with NRI of 9.52% and IDI of 21.6%, both with statistical significance (p < 0.01).In the validation set, the C-statistics of radiomics prediction model was also higher but did not show statistical significance (p = 0.07). The NRI and IDI was 14.29 and 33.7%, respectively, both statistically significant (p < 0.01). Validation set decision curve analysis showed the net benefit improvement of CT radiomics prediction model in the range of 3-81% over CECT. CONCLUSION The prediction model using CT radiomics in corticomedullary phase is more effective for ccRCC ISUP/WHO grade than conventional CECT. ADVANCES IN KNOWLEDGE As a non-invasive analysis method, radiomics can predict the ISUP/WHO grade of ccRCC more effectively than traditional enhanced CT.
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Affiliation(s)
- Dong Han
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - Yong Yu
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - Nan Yu
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - Shan Dang
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - Hongpei Wu
- Department of Pathology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | | | - Taiping He
- Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
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Dual energy CT in clinical routine: how it works and how it adds value. Emerg Radiol 2020; 28:103-117. [PMID: 32483665 DOI: 10.1007/s10140-020-01785-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 05/04/2020] [Indexed: 02/06/2023]
Abstract
Dual energy computed tomography (DECT), also known as spectral CT, refers to advanced CT technology that separately acquires high and low energy X-ray data to enable material characterization applications for substances that exhibit different energy-dependent x-ray absorption behavior. DECT supports a variety of post-processing applications that add value in routine clinical CT imaging, including material selective and virtual non-contrast images using two- and three-material decomposition algorithms, virtual monoenergetic imaging, and other material characterization techniques. Following a review of acquisition and post-processing techniques, we present a case-based approach to highlight the added value of DECT in common clinical scenarios. These scenarios include improved lesion detection, improved lesion characterization, improved ease of interpretation, improved prognostication, inherently more robust imaging protocols to account for unexpected pathology or suboptimal contrast opacification, length of stay reduction, reduced utilization by avoiding unnecessary follow-up examinations, and radiation dose reduction. A brief discussion of post-processing workflow approaches, challenges, and solutions is also included.
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Meyer M, Nelson RC, Vernuccio F, González F, Farjat AE, Patel BN, Samei E, Henzler T, Schoenberg SO, Marin D. Virtual Unenhanced Images at Dual-Energy CT: Influence on Renal Lesion Characterization. Radiology 2019; 291:381-390. [DOI: 10.1148/radiol.2019181100] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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Systematic Review and Meta-Analysis Investigating the Diagnostic Yield of Dual-Energy CT for Renal Mass Assessment. AJR Am J Roentgenol 2019; 212:1044-1053. [PMID: 30835518 DOI: 10.2214/ajr.18.20625] [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: 12/26/2022]
Abstract
OBJECTIVE. The objective of our study was to perform a systematic review and meta-analysis to evaluate the diagnostic accuracy of dual-energy CT (DECT) for renal mass evaluation. MATERIALS AND METHODS. In March 2018, we searched MEDLINE, Cochrane Database of Systematic Reviews, Embase, and Web of Science databases. Analytic methods were based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Pooled estimates for sensitivity, specificity, and diagnostic odds ratios were calculated for DECT-based virtual monochromatic imaging (VMI) and iodine quantification techniques as well as for conventional attenuation measurements from renal mass CT protocols. I2 was used to evaluate heterogeneity. The methodologic quality of the included studies and potential bias were assessed using items from the Quality Assessment Tool for Diagnostic Accuracy Studies 2 (QUADAS-2). RESULTS. Of the 1043 articles initially identified, 13 were selected for inclusion (969 patients, 1193 renal masses). Cumulative data of sensitivity, specificity, and summary diagnostic odds ratio for VMI were 87% (95% CI, 80-92%; I2, 92.0%), 93% (95% CI, 90-96%; I2, 18.0%), and 183.4 (95% CI, 30.7-1093.4; I2, 61.6%), respectively. Cumulative data of sensitivity, specificity, and summary diagnostic odds ratio for iodine quantification were 99% (95% CI, 97-100%; I2, 17.6%), 91% (95% CI, 89-94%; I2, 84.2%), and 511.5 (95% CI, 217-1201; I2, 0%). No significant differences in AUCs were found when comparing iodine quantification to conventional attenuation measurements (p = 0.79). CONCLUSION. DECT yields high accuracy for renal mass evaluation. Determination of iodine content with the iodine quantification technique shows diagnostic accuracy similar to conventional attenuation measurements from renal mass CT protocols. The iodine quantification technique may be used to characterize incidental renal masses when a dedicated renal mass protocol is not available.
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