Faculty Bibliography

BACKGROUND/AIMS:Small intestinal bacterial overgrowth (SIBO) is a common condition in disorders of gut-brain interaction (DGBI). Recently, a combined scintigraphy-lactulose hydrogen breath test (ScLHBT) was described as an accurate tool diagnosing SIBO. We aim to analyze whether a lactulose nutrient challenge test (NCT), previously shown to separate DGBI from healthy volunteers, is equivalent to ScLHBT in diagnosing SIBO. METHODS:We studied data of 81 DGBI patients undergoing ScLHBT with 30 g lactulose and 300 mL water as well as NCT with 30 g lactulose and a 400 mL liquid test meal. Differences in proportion of positive SIBO diagnoses according to specified cecal load and time criteria for NCT and ScLHBT, respectively, were tested in an equivalence trial. An odds ratio (OR) range of 0.80-1.25 was considered equivalent. RESULTS:Diagnosis of SIBO during NCT was not equivalent to SIBO diagnosis in ScLHBT, considering a hydrogen increase before cecal load of 5.0%, 7.5%, or 10.0%, respectively ([OR, 3.76; 90% CI, 1.99-7.09], [OR, 1.87; 90% CI, 1.06-3.27], and [OR, 1.11; 90% CI, 0.65- 1.89]). Considering only time to hydrogen increase as criterion, the odds of a positive SIBO diagnosis in the NCT (0.65) was lower than in ScLHBT (1.70) (OR, 0.38; 90% CI, 0.23-0.65). CONCLUSIONS:This study could not show an equivalence of NCT and ScLHBT in diagnosing SIBO. A possible explanation might be the different transit times owing to unequal testing substances. The effect of this deviation in relation to consecutive therapy regimens should be tested in further prospective studies.

BACKGROUND:Brown adipose tissue (BAT) is a specialized form of adipose tissue, able to increase energy expenditure by heat generation in response to various stimuli. Recently, its pathological activation has been implicated in the pathogenesis of cancer cachexia. To establish a causal relationship, we retrospectively investigated the longitudinal changes in BAT and cancer in a large FDG-PET/CT cohort. METHODS:We retrospectively analyzed 13 461 FDG-PET/CT examinations of n = 8 409 patients at our institution from the winter months of 2007-2015. We graded the activation strength of BAT based on the anatomical location of the most caudally activated BAT depot into three tiers, and the stage of the cancer into five general grades. We validated the cancer grading by an interreader analysis and correlation with histopathological stage. Ambient temperature data (seven-day average before the examination) was obtained from a meteorological station close to the hospital. Changes of BAT, cancer, body mass index (BMI) and temperature between the different examinations were examined with Spearman's test and a mixed linear model for correlation, and with a causal inference algorithm for causality. RESULTS:We found n = 283 patients with at least two examinations and active BAT in at least one of them. There was no significant interaction between the changes in BAT activation, cancer burden or BMI. Temperature changes exhibited a strong negative correlation with BAT activity (ϱ = -0.57, p<0.00001). These results were confirmed with the mixed linear model. Causal inference revealed a link of Temperature ➜ BAT in all subjects and also of BMI ➜ BAT in subjects who had lost weight and increased cancer burden, but no role of cancer and no causal links of BAT ➜ BMI. CONCLUSIONS:Our data did not confirm the hypothesis that BAT plays a major role in cancer-mediated weight loss. Temperature changes are the main driver of incidental BAT activity on FDG-PET scans.

For clinically significant, locally confined prostate cancer, whole-gland radical prostatectomy and radiotherapy are established effective treatment strategies that, however, come at a cost of significant morbidity related to urinary and sexual side effects. The concept of risk stratification paired with a better understanding of prognostic factors has led to the development of alternative management options including active surveillance and focal therapy for appropriately selected patients with localized disease. High-intensity focused ultrasound (HIFU) is one such minimally invasive, image-guided treatment option for prostate cancer. Due to the relative novelty of HIFU and the increased use of magnetic resonance imaging in prostate cancer, many radiologists are not yet familiar with imaging findings related to HIFU, their temporal evolution as well as imaging appearance of recurrent disease after this type of focal therapy. HIFU induces sharply demarcated, localized coagulative necrosis of a tumor through thermal energy delivered via an endorectal or transurethral ultrasound transducer. In this pictorial review, we aim at providing relevant background information that will guide the reader through the general principles of HIFU in the prostate, as well as demonstrate the imaging appearance of expected post-HIFU changes versus recurrent tumor.

PURPOSE/OBJECTIVE:Prostate-specific membrane antigen positron emission tomography (PSMA-PET) has shown promise for detecting nodal and distant prostate cancer (PCa) metastases. However, its performance for local tumor staging is not as well established. The purpose of this study was to review the diagnostic performance of PSMA-PET for determining seminal vesical invasion (SVI) and extraprostatic extension (EPE). METHODS:Pubmed and Embase databases were searched until January 12, 2020. Studies assessing accuracy of PSMA-PET in determining SVI and EPE were included. Study quality was evaluated with the revised Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled sensitivity and specificity were calculated using hierarchical summary receiver operating characteristics modeling. Heterogeneity was explored using meta-regression analyses for anatomical imaging component (MRI vs CT) and by testing for a threshold effect. RESULTS:Twelve studies (615 patients) were included. Pooled sensitivity and specificity were 0.68 (95% CI 0.53-0.81) and 0.94 (95% CI 0.90-0.96) for SVI and 0.72 (95% CI 0.56-0.84) and 0.87 (95% CI 0.72-0.94) for EPE. Meta-regression analyses showed that for SVI, PET/MRI demonstrated greater sensitivity than PET/CT (0.87 [95% CI 0.75-0.98] vs 0.60 [95% CI 0.47-0.74]; p = 0.02 for joint model) while specificity was comparable (0.91 [95% CI 0.84-0.97] vs. 0.96 [95% CI 0.93-0.99]) but not for EPE (p = 0.08). A threshold effect was present for studies assessing EPE (correlation coefficient = 0.563 [95% CI, -0.234-0.908] between sensitivity and false-positive rate). CONCLUSION/CONCLUSIONS:PSMA-PET has moderate sensitivity and excellent specificity for assessing local tumor extent in patients with PCa. PET/MRI showed potential for greater sensitivity than PET/CT in assessing SVI.

OBJECTIVE. Industry relationships drive technologic innovation in interventional radiology and offer opportunities for professional growth. Women are underrepresented in interventional radiology despite the growing recognition of the importance of diversity. This study characterized gender disparities in financial relationships between industry and academic interventional radiologists. MATERIALS AND METHODS. In this retrospective cross-sectional study, U.S. academic interventional radiology physicians and their academic ranks were identified by searching websites of practices with accredited interventional radiology fellowship programs. Publicly available databases were queried to collect each physician's gender, years since medical school graduation, h-index, academic rank, and industry payments in 2018. Wilcoxon and chi-square tests compared payments between genders. A general linear model assessed the impact of academic rank, years since graduation, gender, and h-index on payments. RESULTS. Of 842 academic interventional radiology physicians, 108 (13%) were women. A total $14,206,599.41 was received by 686 doctors (81%); only $147,975.28 (1%) was received by women. A lower percentage of women (74%) than men (83%) received payments (p = 0.04); median total payments were lower for women ($535) than men ($792) (p = 0.01). Academic rank, h-index, years since graduation, and male gender were independent predictors of higher payments. Industry payments supporting technologic advancement were made exclusively to men. CONCLUSION. Female interventional radiology physicians received fewer and lower industry payments, earning 1% of total payments despite constituting 13% of physicians. Gender independently predicted industry payments, regardless of h-index, academic rank, or years since graduation. Gender disparity in interventional radiology physician-industry relationships warrants further investigation and correction.

The aim of this study was to test an interactive up-to-date meta-analysis (iu-ma) of studies on MRI in the management of men with suspected prostate cancer. Based on the findings of recently published systematic reviews and meta-analyses, two freely accessible dynamic meta-analyses (https://iu-ma.org) were designed using the programming language R in combination with the package "shiny." The first iu-ma compares the performance of the MRI-stratified pathway and the systematic transrectal ultrasound-guided biopsy pathway for the detection of clinically significant prostate cancer, while the second iu-ma focuses on the use of biparametric versus multiparametric MRI for the diagnosis of prostate cancer. Our iu-mas allow for the effortless addition of new studies and data, thereby enabling physicians to keep track of the most recent scientific developments without having to resort to classical static meta-analyses that may become outdated in a short period of time. Furthermore, the iu-mas enable in-depth subgroup analyses by a wide variety of selectable parameters. Such an analysis is not only tailored to the needs of the reader but is also far more comprehensive than a classical meta-analysis. In that respect, following multiple subgroup analyses, we found that even for various subgroups, detection rates of prostate cancer are not different between biparametric and multiparametric MRI. Secondly, we could confirm the favorable influence of MRI biopsy stratification for multiple clinical scenarios. For the future, we envisage the use of this technology in addressing further clinical questions of other organ systems.

OBJECTIVE:High breast density is a risk factor for breast cancer. The aim of this study was to develop a deep convolutional neural network (dCNN) for the automatic classification of breast density based on the mammographic appearance of the tissue according to the American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) Atlas. METHODS:In this study, 20,578 mammography single views from 5221 different patients (58.3 ± 11.5 years) were downloaded from the picture archiving and communications system of our institution and automatically sorted according to the ACR density (a-d) provided by the corresponding radiological reports. A dCNN with 11 convolutional layers and 3 fully connected layers was trained and validated on an augmented dataset. The model was finally tested on two different datasets against: i) the radiological reports and ii) the consensus decision of two human readers. None of the test datasets was part of the dataset used for the training and validation of the algorithm. RESULTS:The optimal number of epochs was 91 for medio-lateral oblique (MLO) projections and 94 for cranio-caudal projections (CC), respectively. Accuracy for MLO projections obtained on the validation dataset was 90.9% (CC: 90.1%). Tested on the first test dataset of mammographies (850 MLO and 880 CC), the algorithm showed an accordance with the corresponding radiological reports of 71.7% for MLO and of 71.0% for CC. The agreement with the radiological reports improved in the differentiation between dense and fatty breast for both projections (MLO = 88.6% and CC = 89.9%). In the second test dataset of 200 mammographies, a good accordance was found between the consensus decision of the two readers on both, the MLO-model (92.2%) and the right craniocaudal-model (87.4%). In the differentiation between fatty (ACR A/B) and dense breasts (ACR C/D), the agreement reached 99% for the MLO and 96% for the CC projections, respectively. CONCLUSIONS:The dCNN allows for accurate classification of breast density based on the ACR BI-RADS system. The proposed technique may allow accurate, standardized, and observer independent breast density evaluation of mammographies. ADVANCES IN KNOWLEDGE/CONCLUSIONS:Standardized classification of mammographies by a dCNN could lead to a reduction of falsely classified breast densities, thereby allowing for a more accurate breast cancer risk assessment for the individual patient and a more reliable decision, whether additional ultrasound is recommended.