Faculty Bibliography

OBJECTIVES/OBJECTIVE:Prostate-specific membrane antigen (PSMA)-PET/CT has become integral to management of prostate cancer; however, PSMA-avid rib lesions pose a diagnostic challenge. This study investigated clinicopathological and imaging findings that predict metastatic etiology of PSMA-avid rib lesions. MATERIALS AND METHODS/METHODS:), miPSMA score), CT features (sclerotic, lucent, fracture, no correlate), other sites of metastases, and primary tumor findings. A composite reference standard for rib lesion etiology (metastatic vs non-metastatic) based on histopathology, serial imaging, and clinical assessment was used. RESULTS:, miPSMA), more commonly involved multiple ribs, and were more often sclerotic (p < 0.01); lucency/fractures were only seen in benign lesions. CONCLUSION/CONCLUSIONS:Several imaging and clinicopathological factors differed between PSMA-avid metastatic and benign lesions. Isolated rib lesions without other sites of metastasis are almost always benign. Careful assessment of CT features can help diagnose benign lesions. KEY POINTS/CONCLUSIONS:Question While prostate-specific membrane antigen (PSMA)-PET/CT has become integral to the management of prostate cancer, PSMA-avid rib lesions pose a diagnostic challenge. Findings Approximately a quarter of patients who had PSMA-avid rib lesions were metastatic. However, only 2.1% of them had isolated rib metastasis (without PSMA-avid metastases elsewhere). Clinical relevance Isolated PSMA-avid rib lesions are almost always benign when there is no evidence of metastatic disease elsewhere. Scrutinizing CT features can help diagnose benign PSMA-avid lesions with greater certainty.

OBJECTIVES/OBJECTIVE:An increasing number of patients with prostate cancer (PCa) undergo assessment with magnetic resonance imaging (MRI) and prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA-PET/CT). This offers comprehensive multimodality staging but can lead to discrepancies. The objective was to assess the rates and types of discordance between MRI and PSMA-PET/CT for primary PCa assessment. MATERIALS AND METHODS/METHODS:Consecutive men diagnosed with intermediate and high-risk PCa who underwent MRI and PSMA-PET/CT in 2021-2023 were retrospectively included. MRI and PSMA-PET/CT were interpreted using PI-RADS v2.1 and PRIMARY scores. Discordances between the two imaging modalities were categorized as "minor" (larger or additional lesion seen on one modality) or "major" (positive on only one modality or different index lesions between MRI and PSMA-PET/CT) and reconciled using radical prostatectomy or biopsy specimens. RESULTS:Three hundred and nine men (median age 69 years, interquartile range (IQR) 64-75) were included. Most had Gleason Grade Group ≥ 3 PCa (70.9% (219/309)). Median PSA was 9.0 ng/mL (IQR 5.6-13.6). MRI and PSMA-PET/CT were concordant in 157/309 (50.8%) and discordant in 152/309 (49.1%) patients; with 39/152 (25.7%) major and 113/152 (74.3%) minor discordances. Of 27 patients with lesions only seen on MRI, 85.2% (23/27) were clinically significant PCa (csPCa). Of 23 patients with lesions only seen on PSMA-PET/CT, 78.3% (18/23) were csPCa. Altogether, lesions seen on only one modality were csPCa in 80.0% (36/45). CONCLUSION/CONCLUSIONS:MRI and PSMA-PET/CT were discordant in half of patients for primary PCa evaluation, with major discrepancies seen in roughly one out of eight patients. KEY POINTS/CONCLUSIONS:Question While both MRI and PSMA-PET/CT can be used for primary tumor assessment, the discordances between them are not well established. Findings MRI and PSMA-PET/CT were discordant in about half of the patients. Most prostate lesions seen on only one modality were significant cancer. Clinical relevance MRI and PSMA-PET/CT are often discordant for assessing the primary prostate tumor. Using both modalities for primary prostate tumor evaluation can provide complementary information that may substantially impact treatment planning.

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.

BACKGROUND:Risk of early-stage lung adenocarcinoma (LUAD) recurrence after surgical resection is significant, and post-recurrence median survival is approximately two years. Currently there are no commercially available biomarkers that predict recurrence. Here, we investigated whether microbial and host genomic signatures in the lung can predict recurrence. METHODS:In 91 early-stage (Stage IA/IB) LUAD-patients with extensive follow-up, we used 16s rRNA gene sequencing and host RNA-sequencing to map the microbial and host transcriptomic landscape in tumor and adjacent unaffected lung samples. RESULTS:23 out of 91 subjects had tumor recurrence over 5-year period. In tumor samples, LUAD recurrence was associated with enrichment with Dialister, Prevotella, while in unaffected lung, recurrence was associated with enrichment with Sphyngomonas and Alloiococcus. The strengths of the associations between microbial and host genomic signatures with LUAD recurrence were greater in adjacent unaffected lung samples than in the primary tumor. Among microbial-host features in the unaffected lung samples associated with recurrence, enrichment with Stenotrophomonas geniculata and Chryseobacterium were positively correlated with upregulation of IL-2, IL-3, IL-17, EGFR, HIF-1 signaling pathways among the host transcriptome. In tumor samples, enrichment with Veillonellaceae Dialister, Ruminococcacea, Haemophilus Influenza, and Neisseria were positively correlated with upregulation of IL-1, IL-6, IL17, IFN, and Tryptophan metabolism pathways. CONCLUSIONS:Overall, modeling suggested that a combined microbial/transcriptome approach using unaffected lung samples had the best biomarker performance (AUC=0.83). IMPACT/CONCLUSIONS:This study suggests that LUAD recurrence is associated with distinct pathophysiological mechanisms of microbial-host interactions in the unaffected lung rather than those present in the resected tumor.

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.

The standard method for identifying active Brown Adipose Tissue (BAT) is [¹⁸F]-Fluorodeoxyglucose ([¹⁸F]-FDG) PET/CT imaging, which is costly and exposes patients to radiation, making it impractical for population studies. These issues can be addressed with computational methods that predict [¹⁸F]-FDG uptake by BAT from CT; earlier population studies pave the way for developing such methods by showing some correlation between the Hounsfield Unit (HU) of BAT in CT and the corresponding [¹⁸F]-FDG uptake in PET. In this study, we propose training convolutional neural networks (CNNs) to predict [¹⁸F]-FDG uptake by BAT from unenhanced CT scans in the restricted regions that are likely to contain BAT. Using the Attention U-Net architecture, we perform experiments on datasets from four different cohorts, the largest study to date. We segment BAT regions using predicted [¹⁸F]-FDG uptake values, achieving 23% to 40% better accuracy than conventional CT thresholding. Additionally, BAT volumes computed from the segmentations distinguish the subjects with and without active BAT with an AUC of 0.8, compared to 0.6 for CT thresholding. These findings suggest CNNs can facilitate large-scale imaging studies more efficiently and cost-effectively using only CT.

Purpose To investigate the accuracy and robustness of prostate segmentation using deep learning across various training data sizes, MRI vendors, prostate zones, and testing methods relative to fellowship-trained diagnostic radiologists. Materials and Methods In this systematic review, Embase, PubMed, Scopus, and Web of Science databases were queried for English-language articles using keywords and related terms for prostate MRI segmentation and deep learning algorithms dated to July 31, 2022. A total of 691 articles from the search query were collected and subsequently filtered to 48 on the basis of predefined inclusion and exclusion criteria. Multiple characteristics were extracted from selected studies, such as deep learning algorithm performance, MRI vendor, and training dataset features. The primary outcome was comparison of mean Dice similarity coefficient (DSC) for prostate segmentation for deep learning algorithms versus diagnostic radiologists. Results Forty-eight studies were included. Most published deep learning algorithms for whole prostate gland segmentation (39 of 42 [93%]) had a DSC at or above expert level (DSC ≥ 0.86). The mean DSC was 0.79 ± 0.06 (SD) for peripheral zone, 0.87 ± 0.05 for transition zone, and 0.90 ± 0.04 for whole prostate gland segmentation. For selected studies that used one major MRI vendor, the mean DSCs of each were as follows: General Electric (three of 48 studies), 0.92 ± 0.03; Philips (four of 48 studies), 0.92 ± 0.02; and Siemens (six of 48 studies), 0.91 ± 0.03. Conclusion Deep learning algorithms for prostate MRI segmentation demonstrated accuracy similar to that of expert radiologists despite varying parameters; therefore, future research should shift toward evaluating segmentation robustness and patient outcomes across diverse clinical settings. Keywords: MRI, Genital/Reproductive, Prostate Segmentation, Deep Learning Systematic review registration link: osf.io/nxaev © RSNA, 2024.

Microservices are a software development approach where an application is structured as a collection of loosely coupled, independently deployable services, each focusing on executing a specific purpose. The development of microservices could have a significant impact on radiology workflows, allowing routine tasks to be automated and improving the efficiency and accuracy of radiologic tasks. This technical report describes the development of several microservices that have been successfully deployed in a tertiary cancer center, resulting in substantial time savings for radiologists and other staff involved in radiology workflows. These microservices include the automatic generation of shift emails, notifying administrative staff and faculty about fellows on rotation, notifying referring physicians about outside examinations, and populating report templates with information from PACS and RIS. The report outlines the common thought process behind developing these microservices, including identifying a problem, connecting various APIs, collecting data in a database, writing a prototype and deploying it, gathering feedback and refining the service, putting it in production, and identifying staff who are in charge of maintaining the service. The report concludes by discussing the benefits and challenges of microservices in radiology workflows, highlighting the importance of multidisciplinary collaboration, interoperability, security, and privacy.

PURPOSE/OBJECTIVE:To describe the structure of a dedicated body oncologic imaging fellowship program. To summarize the numbers and types of cross-sectional imaging examinations reported by fellows. METHODS:The curriculum, training methods, and assessment measures utilized in the program were reviewed and described. An educational retrospective analysis was conducted. Data on the number of examinations interpreted by fellows, breakdown of modalities, and examinations by disease management team (DMT) were collected. RESULTS:A total of 38 fellows completed the fellowship program during the study period. The median number of examinations reported per fellow was 2296 [interquartile range: 2148 - 2534], encompassing all oncology-relevant imaging modalities: CT 721 [646-786], MRI 1158 [1016-1309], ultrasound 256 [209-320] and PET/CT 176 [130-202]. The breakdown of examinations by DMT revealed variations in imaging patterns, with MRIs most frequently interpreted for genitourinary, musculoskeletal, and hepatobiliary cancers, and CTs most commonly for general staging or assessment of nonspecific symptoms. CONCLUSION/CONCLUSIONS:This descriptive analysis may serve as a foundation for the development of similar fellowship programs and the advancement of body oncologic imaging. The volume and diversity of examinations reported by fellows highlights the comprehensive nature of body oncologic imaging.