Faculty Bibliography

OBJECTIVES/OBJECTIVE:Despite its high negative predictive value (NPV) for clinically significant prostate cancer (csPCa), MRI suffers from a substantial number of false positives, especially for intermediate-risk cases. In this work, we determine whether a deep learning model trained with PI-RADS-guided representation learning can disambiguate the PI-RADS 3 classification, detect csPCa from bi-parametric prostate MR images, and avoid unnecessary benign biopsies. MATERIALS AND METHODS/METHODS:This study included 28,263 MR examinations and radiology reports from 21,938 men imaged for known or suspected prostate cancer between 2015 and 2023 at our institution (21 imaging locations with 34 readers), with 6352 subsequent biopsies. We trained a deep learning model, a representation learner (RL), to learn how radiologists interpret conventionally acquired T2-weighted and diffusion-weighted MR images, using exams in which the radiologists are confident in their risk assessments (PI-RADS 1 and 2 for the absence of csPCa vs. PI-RADS 4 and 5 for the presence of csPCa, n=21,465). We then trained biopsy-decision models to detect csPCa (Gleason score ≥7) using these learned image representations, and compared them to the performance of radiologists, and of models trained on other clinical variables (age, prostate volume, PSA, and PSA density) for treatment-naïve test cohorts consisting of only PI-RADS 3 (n=253, csPCa=103) and all PI-RADS (n=531, csPCa=300) cases. RESULTS:On the 2 test cohorts (PI-RADS-3-only, all-PI-RADS), RL-based biopsy-decision models consistently yielded higher AUCs in detecting csPCa (AUC=0.73 [0.66, 0.79], 0.88 [0.85, 0.91]) compared with radiologists (equivocal, AUC=0.79 [0.75, 0.83]) and the clinical model (AUCs=0.69 [0.62, 0.75], 0.78 [0.74, 0.82]). In the PIRADS-3-only cohort, all of whom would be biopsied using our institution's standard of care, the RL decision model avoided 41% (62/150) of benign biopsies compared with the clinical model (26%, P<0.001), and improved biopsy yield by 10% compared with the PI-RADS ≥3 decision strategy (0.50 vs. 0.40). Furthermore, on the all-PI-RADS cohort, RL decision model avoided 27% of additional benign biopsies (138/231) compared to radiologists (33%, P<0.001) with comparable sensitivity (93% vs. 92%), higher NPV (0.87 vs. 0.77), and biopsy yield (0.75 vs. 0.64). The combination of clinical and RL decision models further avoided benign biopsies (46% in PI-RADS-3-only and 62% in all-PI-RADS) while improving NPV (0.82, 0.88) and biopsy yields (0.52, 0.76) across the 2 test cohorts. CONCLUSIONS:Our PI-RADS-guided deep learning RL model learns summary representations from bi-parametric prostate MR images that can provide additional information to disambiguate intermediate-risk PI-RADS 3 assessments. The resulting RL-based biopsy decision models also outperformed radiologists in avoiding benign biopsies while maintaining comparable sensitivity to csPCa for the all-PI-RADS cohort. Such AI models can easily be integrated into clinical practice to supplement radiologists' reads in general and improve biopsy yield for any equivocal decisions.

Endometriosis is a common condition primarily impacting women of childbearing age. Despite increasing awareness that endometriosis can be diagnosed non-invasively with the correct imaging techniques, there exists a significant delay in diagnosis, to the tune of 5-10 years. This gap can be narrowed by understanding that this is a disease that lends itself to pattern recognition, and learning to recognize the characteristic patterns on any imaging study will allow earlier diagnosis and prevent long-term complications that can occur with progressive, untreated endometriosis. The disease is often multifocal and thus can present with a wide array of nonspecific symptoms. When clinical findings do not suggest endometriosis, patients often undergo non-targeted imaging, such as chest, abdominal, or pelvic computed tomography (CT); Magnetic Resonance imaging (MRI) studies optimized for neurologic or musculoskeletal indications; or ultrasound (US) exams performed for palpable masses or nonspecific abdominal pain. Familiarity with endometriosis's characteristic patterns across organ systems and how it can masquerade as other diseases helps radiologists broaden their differential to include endometriosis, even on studies not originally aimed at its detection. This review article will describe those imaging findings of endometriosis affecting various organ systems that mimic other pathologies and will enable the reader to pause and question whether endometriosis should be included in the differential.

BACKGROUND:Minimally invasive focal therapy of low- to intermediate-risk prostate cancer is becoming more common and has demonstrated lower morbidity compared to other treatments. Multiparametric prostate magnetic resonance imaging (mpMRI) has the potential to be an effective posttreatment evaluation method for residual/recurrent neoplasm. OBJECTIVE:This study aimed to evaluate the ability of mpMRI to detect residual/recurrent neoplasm after focal therapy treatment of prostate cancer using a 3-point Likert scale. METHODS:This retrospective study included patients who underwent focal therapy utilizing cryoablation, high-frequency ultrasound, and radiofrequency ablation for low- to intermediate-risk prostate cancer with baseline mpMRI and biopsy and a 6- to 12-month follow-up mpMRI and biopsy. Three abdominal fellowship-trained readers were asked to evaluate the follow-up mpMRI utilizing a 3-point Likert scale based on the level of suspicion as "nonviable," "equivocal," or "viable." Diagnostic statistics and Light's κ for interreader variability were calculated. RESULTS:A total of 142 patients were included (mean age, 65 ± 7 years). When considering "equivocal" or "viable" as positive, the overall sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC) for detecting recurrent grade group (GG) 2 or greater disease for Reader 1 were 0.47, 0.83, 0.24, 0.93, and 0.65; for Reader 2, 0.73, 0.75, 0.26, 0.96, and 0.74; and for Reader 3, 0.73, 0.57, 0.17, 0.95, and 0.65. When considering "viable" as positive, the overall sensitivity, specificity, PPV, NPV, and AUC for Reader 1 were 0.47, 0.92, 0.41, 0.94, and 0.69; for Reader 2, 0.33, 0.97, 0.56, 0.93, and 0.65; and for Reader 3, 0.53, 0.84, 0.29, 0.94, and 0.69. κ was 0.39. CONCLUSIONS:This study suggests that DCE and DWI are the most important sequences in mpMRI and demonstrates the efficacy of utilizing a 3-point grading system in detecting and diagnosing prostate cancer after focal therapy. CLINICAL IMPACT/CONCLUSIONS:mpMRI can be used to monitor for residual/recurrent disease after focal therapy.

Endometriosis, a chronic condition that often starts in adolescence, can have a significant impact on quality of life due to symptoms of dysmenorrhea and pelvic pain. Although laparoscopy with direct visualization and pathologic correlation is the reference standard for the diagnosis of endometriosis, some authors have called for a greater emphasis on clinical diagnosis - including imaging. Magnetic resonance imaging (MRI) provides highly reproducible, large field of view, multiplanar, and multiparametric imaging of pelvic endometriosis and is well tolerated in adolescent patients. As such, pediatric radiologists need to be familiar with the manifestations of endometriosis on MRI and how these findings may differ from those seen in adult populations.

OBJECTIVES/UNASSIGNED:To evaluate the incidence and degree of rectal wall infiltration (RWI) of spacer gel used during prostate radiotherapy among two practitioners experienced in using rectal spacers. MATERIALS AND METHODS/UNASSIGNED:Consecutive patients with prostate cancer who received prostate radiotherapy after hydrogel rectal spacer insertion in August 2023-August 2024 by two experienced practitioners were retrospectively included. Post-implant magnetic resonance imaging examinations were evaluated by two radiologists for RWI: 0 (no abnormality), 1 (rectal wall edema), 2 (superficial RWI), and 3 (deep RWI). Scores 2-3 were considered positive for RWI and their location and degree of RWI (radial, longitudinal, and circumferential) were also categorized. Inter-reader agreement was assessed with Cohen's Kappa. RESULTS/UNASSIGNED:215 men were included. Agreement was substantial between the radiologists for RWI scores (Kappa, 0.697; 95% confidence interval, 0.594-0.800). RWI scores were 0 in 80.5% (173/215), 1 in 7.9% (17/215), 2 in 10.7% (23/215), and, 3 in 0.9% (2/215) of the men. Altogether, RWI was present (scores 2-3) in 11.6% (25/215), most commonly in the mid-gland and apex with median radial, longitudinal, and circumferential involvement of 3.2 mm, 8.6 mm, and 11.5%. None of these patients demonstrated any significant rectal toxicity. CONCLUSION/UNASSIGNED:RWI was very uncommon for experienced practitioners. The degree of RWI was focal and not associated with increased complications.

Endometriosis is a common yet morbid disease. Imaging plays an important role in diagnosis and treatment planning. Both ultrasound (US) and MRI are used to detect disease. We performed a literature review to assess whether one is superior. A total of 33 studies from the 4482 identified in the initial search were found to assess the efficacy of US and/or MRI in detecting pelvic endometriosis. Most studies were performed at centers with extensive experience with endometriosis, using dedicated US and MRI protocols. A wide range of sensitivities and specificities was reported, but overall weighted means of diagnostic statistics between US and MRI were similar. The choice of dedicated US versus MRI in evaluation of endometriosis should therefore be based on the expertise in the region. The data also showed US had better accuracy for identifying depth of wall invasion in bowel wall disease, whereas MRI better visualized pelvic wall and extraperitoneal disease. Routine US and MRI protocols performed worse than dedicated US and MRI protocols, which may account for delays in diagnoses. Clinical and research efforts directed at improving the sensitivity of routine imaging for diagnosing deep endometriosis could improve patient access to appropriate care.

OBJECTIVE:To perform image quality comparison between deep learning-based multiband diffusion-weighted sequence (DL-mb-DWI), accelerated multiband diffusion-weighted sequence (accelerated mb-DWI), and conventional multiband diffusion-weighted sequence (conventional mb-DWI) in patients undergoing clinical liver magnetic resonance imaging (MRI). METHODS:Fifty consecutive patients who underwent clinical MRI of the liver at a 1.5-T scanner, between September 1, 2021, and January 31, 2022, were included in this study. Three radiologists independently reviewed images using a 5-point Likert scale for artifacts and image quality factors, in addition to assessing the presence of liver lesions and lesion conspicuity. RESULTS:DL-mb-DWI acquisition time was 65.0 ± 2.4 seconds, significantly (P < 0.001) shorter than conventional mb-DWI (147.5 ± 19.2 seconds) and accelerated mb-DWI (94.3 ± 1.8 seconds). DL-mb-DWI received significantly higher scores than conventional mb-DWI for conspicuity of the left lobe (P < 0.001), sharpness of intrahepatic vessel margin (P < 0.001), sharpness of the pancreatic contour (P < 0.001), in-plane motion artifact (P = 0.002), and overall image quality (P = 0.005) by reader 2. DL-mb-DWI received significantly higher scores for conspicuity of the left lobe (P = 0.006), sharpness of the pancreatic contour (P = 0.020), and in-plane motion artifact (P = 0.042) by reader 3. DL-mb-DWI received significantly higher scores for strength of fat suppression (P = 0.004) and sharpness of the pancreatic contour (P = 0.038) by reader 1. The remaining quality parameters did not reach statistical significance for reader 1. CONCLUSIONS:Novel diffusion-weighted MRI sequence with deep learning-based image reconstruction demonstrated significantly decreased acquisition times compared with conventional and accelerated mb-DWI sequences, while maintaining or improving image quality for routine abdominal MRI. DL-mb-DWI offers a potential alternative to conventional mb-DWI in routine clinical liver MRI.

INTRODUCTION/BACKGROUND:Local disease recurrence following focal therapy (FT) for prostate cancer may be due to failure to eradicate focal disease or development of disease in the untreated prostate (in- and out-of-field recurrences). Several studies suggest in-field contrast enhancement (CE) on post-treatment multi-parametric (mp) MRI between 6-12 months following FT indicates residual disease. The present study assesses the incidence and oncologic implications of early CE observed following primary partial gland cryoablation (PPGCA). MATERIAL AND METHODS/METHODS:The surveillance protocol for men enrolled in our prospective outcomes study following PPGCA included mpMRI at 6-12 months, 2 years, 3.5 years, and 5 years. All cases of in-field early CE were re-reviewed retrospectively and graded using the previously described Prostate Imaging after Focal Ablation scoring system. All patients exhibiting early CE were re-evaluated by a single radiologist at 2-year mpMRI Results: A total of 320 men enrolled in our PPGCA outcomes study had at least 6 months of follow up. Three hundred fifteen (98%) of these men had undergone post-PPGCA mpMRI at 6-12 months. Of these men, 9 were found to have early in-field CE and 8 underwent repeat MRI at 2 years. In all 8 cases, the CE resolved on the 2-year mpMRI. Of these 8 patients, seven underwent repeat protocol biopsy at 2 years and in-field significant disease was detected in only 1 case. CONCLUSIONS:The most compelling evidence that early CE is not indicative of prostate cancer recurrence is that all lesions resolved within 24 months. While incidence of early CE is low, its consistent resolution calls into question the clinical significance of this finding after PPGCA.

AIM/OBJECTIVE:To investigate the associations between the hour of the day and Prostate Imaging-Reporting and Data System (PI-RADS) scores assigned by radiologists in prostate MRI reports. MATERIALS AND METHODS/METHODS:Retrospective single-center collection of prostate MRI reports over an 8-year period. Mean PI-RADS scores assigned between 0800 and 1800 h were examined with a regression model. RESULTS: = 0.005, p < 0.001), with malignant scores more frequently assigned later in the day. CONCLUSION/CONCLUSIONS:These findings suggest chronobiological factors may contribute to variability in radiological assessments. Though the magnitude of the effect is small, this may potentially add variability and impact diagnostic accuracy.