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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

Comparison of Prostate Imaging and Reporting Data System V2.0 and V2.1 for Evaluation of Transition Zone Lesions: A 5-Reader 202-Patient Analysis

Kim, Nancy; Kim, Sooah; Prabhu, Vinay; Shanbhogue, Krishna; Smereka, Paul; Tong, Angela; Anthopolos, Rebecca; Taneja, Samir S; Rosenkrantz, Andrew B
OBJECTIVE:The aim of the study was to compare the distribution of Prostate Imaging and Reporting Data System (PI-RADS) scores, interreader agreement, and diagnostic performance of PI-RADS v2.0 and v2.1 for transition zone (TZ) lesions. METHODS:The study included 202 lesions in 202 patients who underwent 3T prostate magnetic resonance imaging showing a TZ lesion that was later biopsied with magnetic resonance imaging/ultrasound fusion. Five abdominal imaging faculty reviewed T2-weighted imaging and high b value/apparent diffusion coefficient images in 2 sessions. Cases were randomized using a crossover design whereby half in the first session were reviewed using v2.0 and the other half using v2.1, and vice versa for the 2nd session. Readers provided T2-weighted imaging and DWI scores, from which PI-RADS scores were derived. RESULTS:Interreader agreement for all PI-RADS scores had κ of 0.37 (v2.0) and 0.26 (v2.1). For 4 readers, the percentage of lesions retrospectively scored PI-RADS 1 increased greater than 5% and PI-RADS 2 score decreased greater than 5% from v2.0 to v2.1. For 2 readers, the percentage scored PI-RADS 3 decreased greater than 5% and, for 2 readers, increased greater than 5%. The percentage of PI-RADS 4 and 5 lesions changed less than 5% for all readers. For the 4 readers with increased frequency of PI-RADS 1 using v2.1, 4% to 16% were Gleason score ≥3 + 4 tumor. Frequency of Gleason score ≥3 + 4 in PI-RADS 3 lesions increased for 2 readers and decreased for 1 reader. Sensitivity of PI-RADS of 3 or greater for Gleason score ≥3 + 4 ranged 76% to 90% (v2.0) and 69% to 96% (v2.1). Specificity ranged 32% to 64% (v2.0) and 25% to 72% (v2.1). Positive predictive value ranged 43% to 55% (v2.0) and 41% to 58% (v2.1). Negative predictive value ranged 82% to 87% (v2.0) and 81% to 91% (v2.1). CONCLUSIONS:Poor interreader agreement and lack of improvement in diagnostic performance indicate an ongoing need to refine evaluation of TZ lesions.
PMID: 35405714
ISSN: 1532-3145
CID: 5218952

Safety of stereotactic body radiation therapy for localized prostate cancer without treatment planning MRI

Amarell, Katherine; Jaysing, Anna; Mendez, Christopher; Haas, Jonathan A; Blacksburg, Seth R; Katz, Aaron E; Sanchez, Astrid; Tong, Angela; Carpenter, Todd; Witten, Matthew; Collins, Sean P; Lischalk, Jonathan W
BACKGROUND:The use of treatment planning prostate MRI for Stereotactic Body Radiation Therapy (SBRT) is largely a standard, yet not all patients can receive MRI for a variety of clinical reasons. Thus, we aim to investigate the safety of patients who received CT alone based SBRT planning for the definitive treatment of localized prostate cancer. METHODS:Our study analyzed 3410 patients with localized prostate cancer who were treated with SBRT at a single academic institution between 2006 and 2020. Acute and late toxicity was evaluated using the Common Terminology Criteria for Adverse Events version 5.0. Expanded Prostate Cancer Index Composite (EPIC) questionnaires evaluated QOL and PSA nadir was evaluated to detect biochemical failures. RESULTS:A total of 162 patients (4.75%) received CT alone for treatment planning. The CT alone group was older relative to the MRI group (69.9 vs 67.2, p < 0.001) and had higher risk and grade disease (p < 0.001). Additionally, the CT group exhibited a trend in larger CTVs (82.56 cc vs 76.90 cc; p = 0.055), lower total radiation doses (p = 0.048), and more frequent pelvic nodal radiation versus the MRI group (p < 0.001). There were only two reported cases of Grade 3 + toxicity within the CT alone group. Quality of life data within the CT alone group revealed declines in urinary and bowel scores at one month with return to baseline at subsequent follow up. Early biochemical failure data at median time of 2.3 years revealed five failures by Phoenix definition. CONCLUSIONS:While clinical differences existed between the MRI and CT alone group, we observed tolerable toxicity profiles in the CT alone cohort, which was further supported by EPIC questionnaire data. The overall clinical outcomes appear comparable in patients unable to receive MRI for their SBRT treatment plan with early clinical follow up.
PMID: 35366926
ISSN: 1748-717x
CID: 5201512

Accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction: qualitative and quantitative comparison of image quality with conventional T2-weighted FS sequence

Shanbhogue, Krishna; Tong, Angela; Smereka, Paul; Nickel, Dominik; Arberet, Simon; Anthopolos, Rebecca; Chandarana, Hersh
OBJECTIVE:To compare the image quality of an accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction (DL HASTE-FS) with conventional T2-weighted FS sequence (conventional T2 FS) at 1.5 T. METHODS:One hundred consecutive patients who underwent clinical MRI of the liver at 1.5 T including the conventional T2-weighted fat-suppressed sequence (T2 FS) and accelerated single-shot T2-weighted MRI of the liver with deep learning-based image reconstruction (DL HASTE-FS) were included. Images were reviewed independently by three blinded observers who used a 5-point confidence scale for multiple measures regarding the artifacts and image quality. Descriptive statistics and McNemar's test were used to compare image quality scores and percentage of lesions detected by each sequence, respectively. Intra-class correlation coefficient (ICC) was used to assess consistency in reader scores. RESULTS:Acquisition time for DL HASTE-FS was 51.23 +/ 10.1 s, significantly (p < 0.001) shorter than conventional T2-FS (178.9 ± 85.3 s). DL HASTE-FS received significantly higher scores than conventional T2-FS for strength and homogeneity of fat suppression; sharpness of liver margin; sharpness of intra-hepatic vessel margin; in-plane and through-plane respiratory motion; other ghosting artefacts; liver-fat contrast; and overall image quality (all, p < 0.0001). DL HASTE-FS also received higher scores for lesion conspicuity and sharpness of lesion margin (all, p < .001), without significant difference for liver lesion contrast (p > 0.05). CONCLUSIONS:Accelerated single-shot T2-weighted MRI of the liver with deep learning-based image reconstruction showed superior image quality compared to the conventional T2-weighted fat-suppressed sequence despite a 4-fold reduction in acquisition time. KEY POINTS/CONCLUSIONS:• Conventional fat-suppressed T2-weighted sequence (conventional T2 FS) can take unacceptably long to acquire and is the most commonly repeated sequence in liver MRI due to motion. • DL HASTE-FS demonstrated superior image quality, improved respiratory motion and other ghosting artefacts, and increased lesion conspicuity with comparable liver-to-lesion contrast compared to conventional T2FS sequence. • DL HASTE- FS has the potential to replace conventional T2 FS sequence in routine clinical MRI of the liver, reducing the scan time, and improving the image quality.
PMID: 33961086
ISSN: 1432-1084
CID: 4866842

A Novel Deep Learning Based Computer-Aided Diagnosis System Improves the Accuracy and Efficiency of Radiologists in Reading Biparametric Magnetic Resonance Images of the Prostate: Results of a Multireader, Multicase Study

Winkel, David J; Tong, Angela; Lou, Bin; Kamen, Ali; Comaniciu, Dorin; Disselhorst, Jonathan A; Rodríguez-Ruiz, Alejandro; Huisman, Henkjan; Szolar, Dieter; Shabunin, Ivan; Choi, Moon Hyung; Xing, Pengyi; Penzkofer, Tobias; Grimm, Robert; von Busch, Heinrich; Boll, Daniel T
OBJECTIVE:The aim of this study was to evaluate the effect of a deep learning based computer-aided diagnosis (DL-CAD) system on radiologists' interpretation accuracy and efficiency in reading biparametric prostate magnetic resonance imaging scans. MATERIALS AND METHODS/METHODS:We selected 100 consecutive prostate magnetic resonance imaging cases from a publicly available data set (PROSTATEx Challenge) with and without histopathologically confirmed prostate cancer. Seven board-certified radiologists were tasked to read each case twice in 2 reading blocks (with and without the assistance of a DL-CAD), with a separation between the 2 reading sessions of at least 2 weeks. Reading tasks were to localize and classify lesions according to Prostate Imaging Reporting and Data System (PI-RADS) v2.0 and to assign a radiologist's level of suspicion score (scale from 1-5 in 0.5 increments; 1, benign; 5, malignant). Ground truth was established by consensus readings of 3 experienced radiologists. The detection performance (receiver operating characteristic curves), variability (Fleiss κ), and average reading time without DL-CAD assistance were evaluated. RESULTS:The average accuracy of radiologists in terms of area under the curve in detecting clinically significant cases (PI-RADS ≥4) was 0.84 (95% confidence interval [CI], 0.79-0.89), whereas the same using DL-CAD was 0.88 (95% CI, 0.83-0.94) with an improvement of 4.4% (95% CI, 1.1%-7.7%; P = 0.010). Interreader concordance (in terms of Fleiss κ) increased from 0.22 to 0.36 (P = 0.003). Accuracy of radiologists in detecting cases with PI-RADS ≥3 was improved by 2.9% (P = 0.10). The median reading time in the unaided/aided scenario was reduced by 21% from 103 to 81 seconds (P < 0.001). CONCLUSIONS:Using a DL-CAD system increased the diagnostic accuracy in detecting highly suspicious prostate lesions and reduced both the interreader variability and the reading time.
PMID: 33787537
ISSN: 1536-0210
CID: 4858422

Assessment of Renal Cell Carcinoma by Texture Analysis in Clinical Practice: A Six-Site, Six-Platform Analysis of Reliability

Doshi, Ankur M; Tong, Angela; Davenport, Matthew S; Khalaf, Ahmed; Mresh, Rafah; Rusinek, Henry; Schieda, Nicola; Shinagare, Atul; Smith, Andrew D; Thornhill, Rebecca; Vikram, Raghunandan; Chandarana, Hersh
Background: Multiple commercial and open-source software applications are available for texture analysis. Nonstandard techniques can cause undesirable variability that impedes result reproducibility and limits clinical utility. Objective: The purpose of this study is to measure agreement of texture metrics extracted by 6 software packages. Methods: This retrospective study included 40 renal cell carcinomas with contrast-enhanced CT from The Cancer Genome Atlas and Imaging Archive. Images were analyzed by 7 readers at 6 sites. Each reader used 1 of 6 software packages to extract commonly studied texture features. Inter and intra-reader agreement for segmentation was assessed with intra-class correlation coefficients. First-order (available in 6 packages) and second-order (available in 3 packages) texture features were compared between software pairs using Pearson correlation. Results: Inter- and intra-reader agreement was excellent (ICC 0.93-1). First-order feature correlations were strong (r>0.8, p<0.001) between 75% (21/28) of software pairs for mean and standard deviation, 48% (10/21) for entropy, 29% (8/28) for skewness, and 25% (7/28) for kurtosis. Of 15 second-order features, only co-occurrence matrix correlation, grey-level non-uniformity, and run-length non-uniformity showed strong correlation between software packages (0.90-1, p<0.001). Conclusion: Variability in first and second order texture features was common across software configurations and produced inconsistent results. Standardized algorithms and reporting methods are needed before texture data can be reliably used for clinical applications. Clinical Impact: It is important to be aware of variability related to texture software processing and configuration when reporting and comparing outputs.
PMID: 33852355
ISSN: 1546-3141
CID: 4846082

MRI predicts prostatic urethral involvement in men undergoing radical prostatectomy: implications for cryo-ablation of localized prostate cancer

Becher, Ezequiel; Sali, Akash; Abreu, Andre; Iwata, Tsuyoshi; Tong, Angela; Deng, Fang-Ming; Iwata, Atsuko; Gupta, Chhavi; Gill, Inderbir; Aron, Manju; Palmer, Suzanne; Lepor, Herbert
PURPOSE/OBJECTIVE:To determine whether multi-parametric magnetic resonance imaging (mpMRI) can reliably predict proximity of prostate cancer to the prostatic urethra in a contemporary series of men undergoing radical prostatectomy (RP) at two academic centers. METHODS:Clinical characteristics of consecutive men undergoing pre-operative mpMRI prior to RP and whole-mount axial serial step-sectioned pathology examination at two academic centers between Jun 2016 and Oct 2018 were analyzed retrospectively. Every tumor was characterized by its pathologic minimum distance to the prostatic urethral lumen (pMDUL). Only the cancer closest to the urethra represented the prostatic urethral index lesion. The radiologic minimum distance of the index lesion to the prostatic urethral lumen was measured and noted as ≤ 5 mm versus  > 5 mm. The sensitivity, specificity, positive and negative predicting values (PPV and NPV) and area under the receivers operating characteristics curve (AUC) were calculated for performance of mpMRI for predicting pMDUL ≤ 5 mm. RESULTS:Of the 163 surgical specimens examined, 112 (69%) exhibited a pMDUL ≤ 5 mm. These men had significantly higher grade group (GG) and advanced pathological and clinical stage. The rates of high PI-RADS score and presence of gross extracapsular extension were also significantly greater for the group with pMDUL ≤ 5 mm. The AUC, sensitivity, specificity, PPV, and NPV were 0.641, 51.8, 76.5, 82.9, and 42.4%, respectively, for mpMRI to predict pMDUL < 5 mm. CONCLUSIONS:Nearly 70% of men undergoing RP present with tumor within 5 mm of the prostatic urethra. These tumors present higher risk characteristics, and mpMRI exhibited moderate performance and high PPV in their pre-operative detection. Physicians performing partial gland ablation should take these results into consideration during treatment selection and planning.
PMID: 33616707
ISSN: 1433-8726
CID: 4794232

Impact on Participants of Family Connect, a Novel Program Linking COVID-19 Inpatients' Families With the Frontline Providers

Taffel, Myles T; Hochman, Katherine A; Chhor, Chloe M; Alaia, Erin F; Borja, Maria J; Sondhi, Jaya; Lala, Shailee V; Tong, Angela
PURPOSE/OBJECTIVE:With clinical volumes decreased, radiologists volunteered to participate virtually in daily clinical rounds and provide communication between frontline physicians and patients with coronavirus disease 2019 (COVID-19) and their families affected by restrictive hospital visitation policies. The purpose of this survey-based assessment was to demonstrate the beneficial effects of radiologist engagement during this pandemic and potentially in future crises if needed. METHODS:After the program's completion, a survey consisting of 13 multiple-choice and open-ended questions was distributed to the 69 radiologists who volunteered for a minimum of 7 days. The survey focused on how the experience would change future practice, the nature of interaction with medical students, and the motivation for volunteering. The electronic medical record system identified the patients who tested positive for or were suspected of having COVID-19 and the number of notes documenting family communication. RESULTS:In all, 69 radiologists signed or cosigned 7,027 notes. Of the 69 radiologists, 60 (87.0%) responded to the survey. All found the experience increased their understanding of COVID-19 and its effect on the health care system. Overall, 59.6% agreed that participation would result in future change in communication with patients and their families. Nearly all (98.1%) who worked with medical students agreed that their experience with medical students was rewarding. A majority (82.7%) chose to participate as a way to provide service to the patient population. CONCLUSION/CONCLUSIONS:This program provided support to frontline inpatient teams while also positively affecting the radiologist participants. If a similar situation arises in the future, this communication tool could be redeployed, especially with the collaboration of medical students.
PMID: 33091384
ISSN: 1558-349x
CID: 4663492

Response assessment of hepatocellular carcinoma treated with yttrium-90 radioembolization: inter-reader variability, comparison with 3D quantitative approach, and role in the prediction of clinical outcomes

King, Michael J; Tong, Angela; Dane, Bari; Huang, Chenchan; Zhan, Chenyang; Shanbhogue, Krishna
OBJECTIVES/OBJECTIVE:To assess the inter-reader variability in response assessment for HCC treated with radioembolization (TARE) compared with 3D quantitative criteria (qEASL); and to evaluate their role in prediction of pathological necrosis and clinical outcomes. MATERIALS AND METHODS/METHODS:57 patients with 77 HCCs who underwent TARE were included. Five radiologists recorded multiple imaging features and assigned mRECIST/LIRADS Treatment Response (TR) categories on post-treatment MRI at 4-6 weeks and 6-9 months after TARE. qEASL categories were assigned by a separate reader. Inter-reader variability between LIRADS TR/mRECIST/qEASL were evaluated and hazards regression was used in predicting clinical outcomes. RESULTS:Inter-reader agreement was fair for mRECIST (K = 0.43 and 0.34 at first and second follow-up respectively); moderate for LIRADS TR (K = 0.48 and 0.53 at first and second follow-up respectively). Inter-criterion agreement was moderate to substantial (r = 0.41-0.65 and r = 0.54-0.60 at first and second follow-up) for mRECIST-qEASL. LIRADS TR correlated well with qEASL for all readers at both follow-ups (K = 0.45-0.78; K = 0.39-0.77 for first and second follow-up). qEASL was the most accurate in predicting Tumor-Free Survival (TFS) on first (HR 2.23 [1.44-3.46], p < 0.001) and second (HR 1.69 [1.15-2.48], p = 0.008) follow-up. LIRADS TR was the most accurate in predicting histopathological necrosis (8 patients underwent liver transplantation and 1 patient underwent tumor resection during the period of the study). CONCLUSIONS:HCC response assessment following TARE is challenging, resulting in poor to moderate inter-reader agreement for mRECIST, and moderate inter-reader agreement for LIRADS TR response assessment criteria. qEASL outperformed mRECIST criteria for early identification of responders and predicting TFS, suggesting an advantage in volumetric tumor response assessment. LIRADS TR outperformed other criteria in predicting pathological necrosis.
PMID: 33096408
ISSN: 1872-7727
CID: 4642632

Endometriosis MRI lexicon: consensus statement from the society of abdominal radiology endometriosis disease-focused panel

Jha, Priyanka; Sakala, Michelle; Chamie, Luciana Pardini; Feldman, Myra; Hindman, Nicole; Huang, Chenchan; Kilcoyne, Aoife; Laifer-Narin, Sherelle; Nicola, Refky; Poder, Liina; Shenoy-Bhangle, Anuradha; Tong, Angela; VanBuren, Wendy; Taffel, Myles T
Endometriosis is a common gynecologic disorder characterized by the presence of ectopic endometrial tissue outside the endometrial cavity. Magnetic Resonance Imaging (MRI) has become a mainstay for diagnosis and staging of this disease. In the literature, significant heterogeneity exists in the descriptions of imaging findings and anatomic sites of involvement. The Society of Abdominal Radiology's Endometriosis Disease-Focused Panel presents this consensus document to establish an MRI lexicon for endometriosis MRI evaluation and anatomic localization.
PMID: 31728612
ISSN: 2366-0058
CID: 4187042