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Inter-reader agreement of pancreatic adenocarcinoma resectability assessment with photon counting versus energy integrating detector CT

Kim, Jesi; Mabud, Tarub; Huang, Chenchan; Lloret Del Hoyo, Juan; Petrocelli, Robert; Vij, Abhinav; Dane, Bari
PURPOSE/OBJECTIVE:To compare the inter-reader agreement of pancreatic adenocarcinoma resectability assessment at pancreatic protocol photon-counting CT (PCCT) with conventional energy-integrating detector CT (EID-CT). METHODS:A retrospective single institution database search identified all contrast-enhanced pancreatic mass protocol abdominal CT performed at an outpatient facility with both a PCCT and EID-CT from 4/11/2022 to 10/30/2022. Patients without pancreatic adenocarcinoma were excluded. Four fellowship-trained abdominal radiologists, blinded to CT type, independently assessed vascular tumor involvement (uninvolved, abuts ≤ 180°, encases > 180°; celiac, superior mesenteric artery (SMA), common hepatic artery (CHA), superior mesenteric vein (SMV), main portal vein), the presence/absence of metastases, overall tumor resectability (resectable, borderline resectable, locally advanced, metastatic), and diagnostic confidence. Fleiss's kappa was used to calculate inter-reader agreement. CTDIvol was recorded. Radiation dose metrics were compared with a two-sample t-test. A p < .05 indicated statistical significance. RESULTS:145 patients (71 men, mean[SD] age: 66[9] years) were included. There was substantial inter-reader agreement, for celiac artery, SMA, and SMV involvement at PCCT (kappa = 0.61-0.69) versus moderate agreement at EID-CT (kappa = 0.56-0.59). CHA had substantial inter-reader agreement at both PCCT (kappa = 0.67) and EIDCT (kappa = 0.70). For metastasis identification, radiologists had substantial inter-reader agreement at PCCT (kappa = 0.78) versus moderate agreement at EID-CT (kappa = 0.56). CTDIvol for PCCT and EID-CT were 16.9[7.4]mGy and 29.8[26.6]mGy, respectively (p < .001). CONCLUSION/CONCLUSIONS:There was substantial inter-reader agreement for involvement of 4/5 major peripancreatic vessels (celiac artery, SMA, CHA, and SMV) at PCCT compared with 2/5 for EID-CT. PCCT also afforded substantial inter-reader agreement for metastasis detection versus moderate agreement at EID-CT with statistically significant radiation dose reduction.
PMID: 38630314
ISSN: 2366-0058
CID: 5646592

Multicenter Validation of a T2-Weighted MRI Calculator to Differentiate Adrenal Adenoma From Adrenal Metastases

Tu, Wendy; Badawy, Mohamed; Carney, Benjamin W; Caoili, Elaine M; Corwin, Michael T; Elsayes, Khaled M; Mayo-Smith, William; Glazer, Daniel I; Bagga, Barun; Petrocelli, Robert; Taffel, Myles T; Schieda, Nicola
PMID: 37556601
ISSN: 1546-3141
CID: 5632972

Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate

Tong, Angela; Bagga, Barun; Petrocelli, Robert; Smereka, Paul; Vij, Abhinav; Qian, Kun; Grimm, Robert; Kamen, Ali; Keerthivasan, Mahesh B; Nickel, Marcel Dominik; von Busch, Heinrich; Chandarana, Hersh
BACKGROUND:Demand for prostate MRI is increasing, but scan times remain long even in abbreviated biparametric MRIs (bpMRI). Deep learning can be leveraged to accelerate T2-weighted imaging (T2WI). PURPOSE/OBJECTIVE:To compare conventional bpMRIs (CL-bpMRI) with bpMRIs including a deep learning-accelerated T2WI (DL-bpMRI) in diagnosing prostate cancer. STUDY TYPE/METHODS:Retrospective. POPULATION/METHODS:Eighty consecutive men, mean age 66 years (47-84) with suspected prostate cancer or prostate cancer on active surveillance who had a prostate MRI from December 28, 2020 to April 28, 2021 were included. Follow-up included prostate biopsy or stability of prostate-specific antigen (PSA) for 1 year. FIELD STRENGTH AND SEQUENCES/UNASSIGNED:. ASSESSMENT/RESULTS:CL-bpMRI and DL-bpMRI including the same conventional diffusion-weighted imaging (DWI) were presented to three radiologists (blinded to acquisition method) and to a deep learning computer-assisted detection algorithm (DL-CAD). The readers evaluated image quality using a 4-point Likert scale (1 = nondiagnostic, 4 = excellent) and graded lesions using Prostate Imaging Reporting and Data System (PI-RADS) v2.1. DL-CAD identified and assigned lesions of PI-RADS 3 or greater. STATISTICAL TESTS/METHODS:Quality metrics were compared using Wilcoxon signed rank test, and area under the receiver operating characteristic curve (AUC) were compared using Delong's test. SIGNIFICANCE/CONCLUSIONS:P = 0.05. RESULTS:Eighty men were included (age: 66 ± 9 years; 17/80 clinically significant prostate cancer). Overall image quality results by the three readers (CL-T2, DL-T2) are reader 1: 3.72 ± 0.53, 3.89 ± 0.39 (P = 0.99); reader 2: 3.33 ± 0.82, 3.31 ± 0.74 (P = 0.49); reader 3: 3.67 ± 0.63, 3.51 ± 0.62. In the patient-based analysis, the reader results of AUC are (CL-bpMRI, DL-bpMRI): reader 1: 0.77, 0.78 (P = 0.98), reader 2: 0.65, 0.66 (P = 0.99), reader 3: 0.57, 0.60 (P = 0.52). Diagnostic statistics from DL-CAD (CL-bpMRI, DL-bpMRI) are sensitivity (0.71, 0.71, P = 1.00), specificity (0.59, 0.44, P = 0.05), positive predictive value (0.23, 0.24, P = 0.25), negative predictive value (0.88, 0.88, P = 0.48). CONCLUSION/CONCLUSIONS:Deep learning-accelerated T2-weighted imaging may potentially be used to decrease acquisition time for bpMRI. EVIDENCE LEVEL/METHODS:3. TECHNICAL EFFICACY/UNASSIGNED:Stage 2.
PMID: 36651358
ISSN: 1522-2586
CID: 5419182

Current Concepts in the Imaging of Uterine Sarcomas

Petrocelli, Robert; Hindman, Nicole; Reinhold, Caroline
Uterine sarcomas are a group of rare uterine tumors comprised of multiple subtypes with different histologic characteristics, prognoses, and imaging appearances. Identification of uterine sarcomas and their differentiation from benign uterine disease on imaging is of critical importance for treatment planning to guide appropriate management and optimize patient outcomes. Herein, we review the spectrum of uterine sarcomas with a focus on the classification of primary sarcoma subtypes and presenting the typical MR imaging appearances.
PMID: 37169428
ISSN: 1557-8275
CID: 5542112

Prevalence of Malignancy in Adrenal Nodules with Heterogeneous Microscopic Fat on Chemical-Shift MRI: A Multiinstitutional Study

Taffel, Myles; Petrocelli, Robert D; Rigau, Danielle; Schieda, Nicola; Al-Rasheed, Sumaya; Carney, Benjamin; Chung, Ryan; Yao, Michael; Blake, Michael; Elsayes, Khaled M; Badawy, Mohamed; Klimkowski, Sergio; Remer, Erick; Wetzel, Adam; Pandya, Amit; Caoili, Elaine; Corwin, Michael T
PMID: 35920707
ISSN: 1546-3141
CID: 5288052

Crohn's disease active inflammation assessment with iodine density from dual-energy CT enterography: comparison with endoscopy and conventional interpretation

Dane, Bari; Kernizan, Amelia; O'Donnell, Thomas; Petrocelli, Robert; Rabbenou, Wendy; Bhattacharya, Sumona; Chang, Shannon; Megibow, Alec
PURPOSE/OBJECTIVE:To compare terminal ileum (TI) mucosal iodine density obtained at dual-energy CT enterography (DECTE) with conventional CT interpretation and endoscopy in patients with Crohn's disease (CD). MATERIALS AND METHODS/METHODS:) from the distal 2 cm ileum (TI) mucosa obtained using semiautomatic prototype software were compared with endoscopic assessment using Mann Whitney tests. The optimal threshold I% and I were determined from receiver operating curves (ROC). Sensitivity and specificity of conventional interpretation and determined iodine thresholds were compared using McNemar's test. Inter-reader agreement was assessed using kappa. A p < 0.05 indicated statistical significance. RESULTS:was similar for patients with and without endoscopic active inflammation (0.82[0.33]mg/mL and 0.77[0.28]mg/mL, respectively, p = 0.37). Conventional interpretation sensitivity and specificity (R1/R2) were 83.3%/91.7% and 72.7%/54.5%, respectively (all p > 0.05) with moderate inter-reader agreement (Κ = 0.542[95% CI 0.0202-0.088]). CONCLUSION/CONCLUSIONS:Mean normalized iodine density is highly sensitive and specific for endoscopic active inflammation. DECTE could be considered as a surrogate to endoscopy in CD patients. Despite trends towards improved sensitivity and specificity compared with conventional interpretation, future larger studies are needed.
PMID: 35833999
ISSN: 2366-0058
CID: 5269322

Multi-Center Follow-up Study to Develop a Classification System Which Differentiates Mucinous Cystic Neoplasm of the Liver and Benign Hepatic Cyst Using Machine Learning

Hardie, Andrew D; Chamberlin, Jordan H; Boyum, James H; Sharbidre, Kedar G; Petrocelli, Robert; Flemming, Brian P; Zahid, Mohd; Venkatesh, Sudhakar K; Mruthyunjayappa, Smitha; Hajdu, Cristina H; Kovacs, Mark D
RATIONALE AND OBJECTIVES/OBJECTIVE:To date, no clinically useful classification system has been developed for reliably differentiating mucinous cystic neoplasm (MCN) from a benign hepatic cyst (BHC) in the liver. The objective was to use machine learning and a multi-center study design to develop and assess the performance of a novel classification system for predicting whether a hepatic cystic lesion represents MCN or BHC. MATERIALS AND METHODS/METHODS:A multi-center cohort study identified 154 surgically resected hepatic cystic lesions in 154 subjects which were pathologic confirmed as MCN (43) or BHC (111). Readers at each institution recorded seven pre-determined imaging features previously identified as potential differentiating features from prior publications. The contribution of each of these features to differentiating MCN from BHC was assessed by machine learning to develop an optimal classification system. RESULTS:Although several of the assessed imaging features demonstrated statistical significance, only 3 imaging features were found by machine learning to significantly contribute to a potential classification system: (1) solid enhancing nodule (2) all septations arising from an external macro-lobulation (3) whether the lesion was solitary or one of multiple cystic liver lesions. The optimal classification system had only four categories and correctly identified 144/154 lesion (93.5%). CONCLUSION/CONCLUSIONS:This multi-center follow-up study was able to use machine learning to develop a highly accurate classification system for differentiation of hepatic MCN from BHC, which could be readily applied to clinical practice.
PMID: 34598868
ISSN: 1878-4046
CID: 5067612

Deep Learning Reconstruction Enables Highly Accelerated Biparametric MR Imaging of the Prostate

Johnson, Patricia M; Tong, Angela; Donthireddy, Awani; Melamud, Kira; Petrocelli, Robert; Smereka, Paul; Qian, Kun; Keerthivasan, Mahesh B; Chandarana, Hersh; Knoll, Florian
BACKGROUND:Early diagnosis and treatment of prostate cancer (PCa) can be curative; however, prostate-specific antigen is a suboptimal screening test for clinically significant PCa. While prostate magnetic resonance imaging (MRI) has demonstrated value for the diagnosis of PCa, the acquisition time is too long for a first-line screening modality. PURPOSE/OBJECTIVE:To accelerate prostate MRI exams, utilizing a variational network (VN) for image reconstruction. STUDY TYPE/METHODS:Retrospective. SUBJECTS/METHODS:One hundred and thirteen subjects (train/val/test: 70/13/30) undergoing prostate MRI. FIELD STRENGTH/SEQUENCE/UNASSIGNED:3.0 T; a T2 turbo spin echo (TSE) T2-weighted image (T2WI) sequence in axial and coronal planes, and axial echo-planar diffusion-weighted imaging (DWI). ASSESSMENT/RESULTS:, and apparent diffusion coefficient map-according to the Prostate Imaging Reporting and Data System (PI-RADS v2.1), for both VN and standard reconstructions. Accuracy of PI-RADS ≥3 for clinically significant cancer was computed. Projected scan time of the retrospectively under-sampled biparametric exam was also computed. STATISTICAL TESTS/UNASSIGNED:One-sided Wilcoxon signed-rank test was used for comparison of image quality. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for lesion detection and grading. Generalized estimating equation with cluster effect was used to compare differences between standard and VN bp-MRI. A P-value of <0.05 was considered statistically significant. RESULTS:(Reader 1: 3.20 ± 0.70 (Standard), 3.40 ± 0.75 (VN) P = 0.98; Reader 2: 2.85 ± 0.81 (Standard), 3.00 ± 0.79 (VN) P = 0.93; Reader 3: 4.45 ± 0.72 (Standard), 4.05 ± 0.69 (VN) P = 0.02; Reader 4: 4.50 ± 0.69 (Standard), 4.45 ± 0.76 (VN) P = 0.50). In the lesion evaluation study, there was no significant difference in the number of PI-RADS ≥3 lesions identified on standard vs. VN bp-MRI (P = 0.92, 0.59, 0.87) with similar sensitivity and specificity for clinically significant cancer. The average scan time of the standard clinical biparametric exam was 11.8 minutes, and this was projected to be 3.2 minutes for the accelerated exam. DATA CONCLUSION/UNASSIGNED:Diagnostic accelerated biparametric prostate MRI exams can be performed using deep learning methods in <4 minutes, potentially enabling rapid screening prostate MRI. LEVEL OF EVIDENCE/METHODS:3 TECHNICAL EFFICACY: Stage 5.
PMID: 34877735
ISSN: 1522-2586
CID: 5110242

Diagnostic abdominal MR imaging on a prototype low-field 0.55 T scanner operating at two different gradient strengths

Chandarana, Hersh; Bagga, Barun; Huang, Chenchan; Dane, Bari; Petrocelli, Robert; Bruno, Mary; Keerthivasan, Mahesh; Grodzki, David; Block, Kai Tobias; Stoffel, David; Sodickson, Daniel K
PURPOSE:To develop a protocol for abdominal imaging on a prototype 0.55 T scanner and to benchmark the image quality against conventional 1.5 T exam. METHODS:In this prospective IRB-approved HIPAA-compliant study, 10 healthy volunteers were recruited and imaged. A commercial MRI system was modified to operate at 0.55 T (LF) with two different gradient performance levels. Each subject underwent non-contrast abdominal examinations on the 0.55 T scanner utilizing higher gradients (LF-High), lower adjusted gradients (LF-Adjusted), and a conventional 1.5 T scanner. The following pulse sequences were optimized: fat-saturated T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and Dixon T1-weighted imaging (T1WI). Three readers independently evaluated image quality in a blinded fashion on a 5-point Likert scale, with a score of 1 being non-diagnostic and 5 being excellent. An exact paired sample Wilcoxon signed-rank test was used to compare the image quality. RESULTS:Diagnostic image quality (overall image quality score ≥ 3) was achieved at LF in all subjects for T2WI, DWI, and T1WI with no more than one unit lower score than 1.5 T. The mean difference in overall image quality score was not significantly different between LF-High and LF-Adjusted for T2WI (95% CI - 0.44 to 0.44; p = 0.98), DWI (95% CI - 0.43 to 0.36; p = 0.92), and for T1 in- and out-of-phase imaging (95%C I - 0.36 to 0.27; p = 0.91) or T1 fat-sat (water only) images (95% CI - 0.24 to 0.18; p = 1.0). CONCLUSION:Diagnostic abdominal MRI can be performed on a prototype 0.55 T scanner, either with conventional or with reduced gradient performance, within an acquisition time of 10 min or less.
PMID: 34415411
ISSN: 2366-0058
CID: 5048652

Computed Tomography Enterography

Petrocelli, Robert; Dane, Bari
Computed tomography enterography (CTE) is an abdominopelvic computed tomography (CT) tailored for evaluation of the small bowel. This multidetector CT examination uses neutral oral contrast to optimally distend small bowel. Patients are scanned after the rapid injection of intravenous contrast during peak bowel wall enhancement. CTE is excellent for the evaluation of many small bowel disorders, particularly Crohn's disease. The purpose of this article is to review CTE indications, contraindications, technique, safety considerations, and imaging findings of common small bowel diseases.
SCOPUS:85114739334
ISSN: 1546-0843
CID: 5009252