Faculty Bibliography

The visceral vasculature is inextricably intertwined with abdominopelvic disease staging, spread, and management in routine and emergent cases. Comprehensive evaluation requires specialized imaging techniques for abnormality detection and characterization. Vascular pathology is often encountered on nondedicated routine imaging examinations, which may obscure, mimic, or confound many vascular diagnoses. This review highlights normal arterial, portal venous, and systemic venous anatomy and clinically relevant variants; diagnostic pitfalls related to image-acquisition technique and disease mimics; and characteristics of common and rare vascular diseases to empower radiologists to confidently interpret the vascular findings and avoid misdiagnosis.

PURPOSE/OBJECTIVE:This study aimed to compare the image quality of portal venous phase-derived virtual noncontrast (VNC) images from photon-counting computed tomography (PCCT) with energy-integrating dual-energy computed tomography (EI-DECT) in the same patient using quantitative and qualitative analyses. METHODS:Consecutive patients retrospectively identified with available portal venous phase-derived VNC images from both PCCT and EI-DECT were included. Patients without available VNC in picture archiving and communication system in PCCT or prior EI-DECT and non-portal venous phase acquisitions were excluded. Three fellowship-trained radiologists blinded to VNC source qualitatively assessed VNC images on a 5-point scale for overall image quality, image noise, small structure delineation, noise texture, artifacts, and degree of iodine removal. Quantitative assessment used region-of-interest measurements within the aorta at 4 standard locations, both psoas muscles, both renal cortices, spleen, retroperitoneal fat, and inferior vena cava. Attenuation (Hounsfield unit), quantitative noise (Hounsfield unit SD), contrast-to-noise ratio (CNR) (CNRvascular, CNRkidney, CNRspleen, CNRfat), signal-to-noise ratio (SNR) (SNRvascular, SNRkidney, SNRspleen, SNRfat), and radiation dose were compared between PCCT and EI-DECT with the Wilcoxon signed rank test. A P < 0.05 indicated statistical significance. RESULTS:A total of 74 patients (27 men; mean ± SD age, 63 ± 13 years) were included. Computed tomography dose index volumes for PCCT and EI-DECT were 9.2 ± 3.5 mGy and 9.4 ± 9.0 mGy, respectively (P = 0.06). Qualitatively, PCCT VNC images had better overall image quality, image noise, small structure delineation, noise texture, and fewer artifacts (all P < 0.00001). Virtual noncontrast images from PCCT had lower attenuation (all P < 0.05), noise (P = 0.006), and higher CNR (P < 0.0001-0.04). Contrast-enhanced structures had lower SNR on PCCT (P = 0.001, 0.002), reflecting greater contrast removal. The SNRfat (nonenhancing) was higher for PCCT than EI-DECT (P < 0.00001). CONCLUSIONS:Virtual noncontrast images from PCCT had improved image quality, lower noise, improved CNR and SNR compared with those derived from EI-DECT.

BACKGROUND:Chronic kidney disease (CKD) is highly prevalent, affecting approximately 11% of U.S. adults. Multiple studies have evaluated a potential association between CKD and urinary tract malignancies. Summary estimates of urinary tract malignancy risk in CKD patients with and without common co-existing conditions may guide clinical practice recommendations. METHODS:Four electronic databases were searched for original cohort studies evaluating the association between CKD and urinary tract cancers (kidney cancer and urothelial carcinoma) through May 25, 2023, in persons with at least moderate CKD and no dialysis or kidney transplantation. Quality assessment was performed for studies meeting inclusion criteria using the Newcastle-Ottawa Scale. Meta-analysis with a random-effects model was performed for unadjusted incidence rate ratios (IRR) as well as adjusted hazard ratios (aHR) for confounding conditions (diabetes, hypertension, and/or tobacco use), shown to have association with kidney cancer and urothelial carcinoma. Sub-analysis was conducted for estimates associated with CKD stages separately. RESULTS:Six cohort studies with 8 617 563 persons were included. Overall, methodological quality of the studies was good. CKD was associated with both higher unadjusted incidence and adjusted hazard of kidney cancer (IRR, 3.36; 95% confidence interval [CI], 2.32-4.88; aHR, 2.04; 95% CI, 1.77-2.36) and urothelial cancer (IRR, 3.96; 95% CI, 2.44-6.40; aHR, 1.40; 95% CI, 1.22-1.68) compared with persons without CKD. Examining incident urinary tract cancers by CKD severity, risks were elevated in stage 3 CKD (kidney aHR, 1.89; 95% CI, 1.56-2.30; urothelial carcinoma aHR, 1.40; 95% CI, 1.18-1.65) as well as in stages 4/5 CKD (kidney cancer aHR, 2.30; 95% CI, 2.00-2.66, UC aHR, 1.24; 95% CI, 1.04-1.49). CONCLUSIONS:Even moderate CKD is associated with elevated risk of kidney cancer and UC. Providers should consider these elevated risks when managing individuals with CKD, particularly when considering evaluation for the presence and etiology of hematuria.

Current disparities in the access to diagnostic imaging for Black patients and the underrepresentation of Black physicians in radiology, relative to their representation in the general U.S. population, reflect contemporary consequences of historical anti-Black discrimination. These disparities have existed within the field of radiology and professional medical organizations since their inception. Explicit and implicit racism against Black patients and physicians was institutional policy in the early 20th century when radiology was being developed as a clinical medical field. Early radiology organizations also embraced this structural discrimination, creating strong barriers to professional Black radiologist involvement. Nevertheless, there were numerous pioneering Black radiologists who advanced scholarship, patient care, and diversity within medicine and radiology during the early 20th century. This work remains important in the present day, as race-based health care disparities persist and continue to decrease the quality of radiology-delivered patient care. There are also structural barriers within radiology affecting workforce diversity that negatively impact marginalized groups. Multiple opportunities exist today for antiracism work to improve quality of care and to apply standards of social justice and health equity to the field of radiology. An initial step is to expand education on the disparities in access to imaging and health care among Black patients. Institutional interventions include implementing community-based outreach and applying antibias methodology in artificial intelligence algorithms, while systemic interventions include identifying national race-based quality measures and ensuring imaging guidelines properly address the unique cancer risks in the Black patient population. These approaches reflect some of the strategies that may mutually serve to address health care disparities in radiology. ^© RSNA, 2023 See the invited commentary by Scott in this issue. Quiz questions for this article are available in the supplemental material.

PURPOSE/OBJECTIVE:Fat-suppressed T2-weighted imaging (T2-FS) requires a long scan time and can be wrought with motion artifacts, urging the development of a shorter and more motion robust sequence. We compare the image quality of a single-shot T2-weighted MRI prototype with deep-learning-based image reconstruction (DL HASTE-FS) with a standard T2-FS sequence for 3 T liver MRI. METHODS:41 consecutive patients with 3 T abdominal MRI examinations including standard T2-FS and DL HASTE-FS, between 5/6/2020 and 11/23/2020, comprised the study cohort. Three radiologists independently reviewed images using a 5-point Likert scale for artifact and image quality measures, while also assessing for liver lesions. RESULTS:DL HASTE-FS acquisition time was 54.93 ± 16.69, significantly (p < .001) shorter than standard T2-FS (114.00 ± 32.98 s). DL HASTE-FS received significantly higher scores for sharpness of liver margin (4.3 vs 3.3; p < .001), hepatic vessel margin (4.2 vs 3.3; p < .001), pancreatic duct margin (4.0 vs 1.9; p < .001); in-plane (4.0 vs 3.2; p < .001) and through-plane (3.9 vs 3.4; p < .001) motion artifacts; other ghosting artifacts (4.3 vs 2.9; p < .001); and overall image quality (4.0 vs 2.9; p < .001), in addition to receiving a higher score for homogeneity of fat suppression (3.7 vs 3.4; p = .04) and liver-fat contrast (p = .03). For liver lesions, DL HASTE-FS received significantly higher scores for sharpness of lesion margin (4.4 vs 3.7; p = .03). CONCLUSION/CONCLUSIONS:Novel single-shot T2-weighted MRI with deep-learning-based image reconstruction demonstrated superior image quality compared with the standard T2-FS sequence for 3 T liver MRI, while being acquired in less than half the time.

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.

OBJECTIVE:Texture features are proposed for classification and prognostication, with lacking information about variability. We assessed 3 T liver MRI feature variability. METHODS:Five volunteers underwent standard 3 T MRI, and repeated with identical and altered parameters. Two readers placed regions of interest using 3DSlicer. Repeatability (between standard and repeat scan), robustness (between standard and parameter changed scan), and reproducibility (two reader variation) were computed using coefficient of variation (CV). RESULTS:67%, 49%, and 61% of features had good-to-excellent (CV ≤ 10%) repeatability on ADC, T1, and T2, respectively, least frequently for first order (19-35%). 22%, 19%, and 21% of features had good-to-excellent robustness on ADC, T1, and T2, respectively. 52%, 35%, and 25% of feature measurements had good-to-excellent inter-reader reproducibility on ADC, T1, and T2, respectively, with highest good-to-excellent reproducibility for first order features on ADC/T1. CONCLUSION/CONCLUSIONS:We demonstrated large variations in texture features on 3 T liver MRI. Further study should evaluate methods to reduce variability.

RATIONALE AND OBJECTIVES/OBJECTIVE:Radiology social media research has focused on Twitter, Facebook, and YouTube, with minimal attention to Instagram, which may be a natural platform for engagement. We evaluated features of public radiology-related Instagram accounts. MATERIALS AND METHODS/METHODS:Instagram accounts were searched using the term "radiology." Two independent raters used a coding system developed through initial content review to categorize account user types and post aims over the study month (October 2019). Multivariate linear regressions were performed. RESULTS:49 Instagram accounts and their 459 posts were retrieved. Users had median 117 total posts (interquartile range 43-203), 9 posts during the study month (1-16), 3079 followers (695-19,600), and 106 followed users (50-351). Most users were radiologists (41%, most commonly academic), radiology practices (12%, most commonly academic) and 10% radiology professional societies. The 459 posts had median 178 likes (interquartile range 51-353) and 2 comments (0-5); single videos had median 4693 views (2183-6080). 75% of posts were radiology images or videos (of these, 29% MRI, 28% CT). 65% of posts were clinical imaging cases (most commonly neuroradiology). Seven posts violated HIPAA regulations, all originating outside the U.S. When controlling for number of account followers, posts by radiology society (β = -130.6, p = 0.017) and practice accounts (β = -90.6, p = 0.049) had fewer post likes. An artwork post was the only significant predictor of greater post likes (β = +866.2, p < 0.001) and comments (β = +14.3, p < 0.001). CONCLUSION/CONCLUSIONS:Instagram is commonly used by academic radiologists to present clinical imaging cases. Radiologists should consider opportunities for greater application of this unique image-based social media platform.

Despite benefits of safety event reporting, few are trainee initiated. A comprehensive intervention was created to increase trainee reporting, partnering a trainee safety council with high-level faculty. Data were collected for 12 months pre intervention and 30 months post intervention, including short-term (1-12 mo) and long-term (13-30 mo) follow-up. A total of 2337 trainee events were submitted over the study period, primarily communication-related (40%) and on the medicine service (39%). Monthly submissions increased from 29.3 pre intervention to 66.2, 77.7, and 58.6 events/mo at post intervention, short-term follow-up, and long-term follow-up, respectively (P < 0.001). Proportion of hospital events submitted by trainees increased from 2.3% pre intervention to 4.1%, 4.9%, and 3.6% at post intervention, short-term, and long-term follow-up, respectively (P < 0.001). Trainee monthly submissions (P = 0.015) and proportion of hospital events (P < 0.001) declined from short- to long-term follow-up. Low- and intermediate-level harm events significantly increased post intervention (P < 0.001) while high-level events did not (P = 0.15-1.0). Our comprehensive intervention increased trainee event submissions at long-term follow-up.