Faculty Bibliography

BACKGROUND:F]FDG PET/CT. METHODS:in the corresponding tissue depot by simple linear regression. RESULTS: = 0.42, p = 0.009). CONCLUSION/CONCLUSIONS:F] FDG PET-based imaging for quantification of BAT activity. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov. NCT03189511 , registered on June 17, 2017, actual study start date was on May 31, 2017, retrospectively registered. NCT03269747 , registered on September 01, 2017.

PURPOSE/OBJECTIVE:F-FDG PET/MR for the TNM classification. METHOD/METHODS:F-FDG PET/MR for the TNM classification were evaluated. RESULTS:F-FDG PET/MRI without statistical significance (p = 0.3827). CONCLUSION/CONCLUSIONS:F-FDG-PET/MR in this setting is necessary to assess the true value of this modality.

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of the most recent scientific developments without having to resort to classical static meta-analyses that may become outdated in a short period of time.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.

OBJECTIVES:Non-Cartesian spiral magnetic resonance (MR) acquisition may enable higher scan speeds, as the spiral traverses the k-space more efficiently per given time than in Cartesian trajectories. Spiral MR imaging can be implemented in time-of-flight (TOF) MR angiography (MRA) sequences. In this study, we tested the performance of five 3-dimensional TOF MRA sequences for intracranial vessel imaging at 1.5 T with qualitative and quantitative image quality metrics based on in vitro and in vivo measurements. Specifically, 3 novel spiral TOF MRA sequences (spiral-TOFs) and a compressed sensing (CS) technology-accelerated TOF MRA sequence (CS 3.5) were compared with a conventional (criterion standard) parallel imaging-accelerated TOF MRA sequence (SENSE). MATERIALS AND METHODS:The SENSE sequence (5:08 minutes) was compared with the CS 3.5 sequence (3:06 minutes) and a spiral-TOF (spiral, 1:32 minutes), all with identical resolutions. In addition, 2 further isotropic spiral-TOFs (spiral 0.8, 2:12 minutes; spiral 0.6, 5:22 minutes) with higher resolution were compared with the SENSE. First, vessel tracking experiments were performed in vitro with a dedicated vascular phantom to determine possible differences in the depiction of cross-sectional areas of vessel segments. For the in vitro tests, an additional 3-dimensional proton density-weighted sequence was added for comparison reasons. Second, 3 readers blinded to sequence details assessed qualitative (16 features) and 2 readers assessed quantitative (contrast-to-noise ratio [CNR], contrast ratio [CR], vessel sharpness, and full width at half maximum edge criterion measurements) image quality based on images acquired from scanning 10 healthy volunteers with all 5 TOF sequences. Scores from quantitative image quality analysis were compared with Kruskal-Wallis, analysis of variance, or Welch's analysis of variance, followed by Dunnett's or Dunnett's T3 post hoc tests. Scores from qualitative image quality analysis were compared with exact binomial tests, and the level of interreader agreement was determined with Krippendorff's alpha. RESULTS:Concerning the in vitro tests, there were no significant differences between the 5 TOFs and the proton density-weighted sequence in measuring cross-sectional areas of vessel segments (P = 0.904). As for the in vivo tests, the CS 3.5 exhibited equal qualitative image quality as the SENSE, whereas the 3 spiral-TOFs outperformed the SENSE in several categories (P values from 0.002 to 0.031). Specifically, the spiral 0.8 and 0.6 sequences achieved significantly higher scores in 12 categories. Interreader agreement ranged from poor (alpha = -0.013, visualization of internal carotid artery segment C7) to substantial (alpha = 0.737, number of vessels visible, sagittal). As for the quantitative metrics, the CS 3.5 and all 3 spiral-TOFs presented with significantly worse CNR than the SENSE ([mean ± SD] SENSE 37.48 ± 7.13 vs CS 3.5 31.14 ± 5.97 vs spiral 19.77 ± 1.65 vs spiral 0.8 16.18 ± 2.14 vs spiral 0.6 10.37 ± 1.05). The CR values did not differ significantly between the SENSE and the other TOFs except for the spiral sequence that showed significantly improved CR (SENSE 0.53 ± 0.03 vs spiral 0.56 ± 0.03). As for vessel sharpness, the SENSE was outperformed by all spiral-TOFs (SENSE 0.37 ± 0.03 vs spiral 0.52 ± 0.07 vs spiral 0.8 0.53 ± 0.08 vs spiral 0.6 0.73 ± 0.09), whereas the CS 3.5 performed equally well (SENSE 0.37 ± 0.03 vs CS 3.5 0.37 ± 0.03). Full width at half maximum values did not differ significantly between any TOF. CONCLUSIONS:Spiral-TOFs may deliver high-quality intracranial vessel imaging thus matching the performance of conventional parallel imaging-accelerated TOFs (such as the SENSE). Specifically, imaging can be performed at unprecedented scan times as short as 1:32 minutes per sequence (70.12% scan time reduction compared with SENSE). Optionally, spiral imaging may also be used to increase spatial resolution while maintaining the scan time of a Cartesian-based acquisition schema. The CNR was decreased in spiral-TOF images.

OBJECTIVES/OBJECTIVE:To compare interreader agreement and diagnostic accuracy of LI-RADS v2018 categorization using quantitative versus qualitative MRI assessment of arterial phase hyperenhancement (APHE) and washout (WO) of focal liver lesions. METHODS:Sixty patients (19 female; mean age, 56 years) at risk for HCC with 71 liver lesions (28 HCCs, 43 benign) who underwent contrast-enhanced MRI were included in this retrospective study. Four blinded radiologists independently assigned a qualitative LI-RADS score per lesion. Two other radiologists placed ROIs within the lesion, adjacent liver parenchyma, and paraspinal musculature on pre- and post-contrast MR images. The percentage of arterial enhancement and the liver-to-lesion contrast ratio were calculated for quantification of APHE and WO. Using these quantitative parameters, a quantitative LI-RADS score was assigned. Interreader agreement and AUCs were calculated. RESULTS:Interreader agreement was similar for qualitative and quantitative LI-RADS (κ = 0.38 vs. 0.40-0.47) with a tendency towards improved agreement for quantitatively assessed APHE (κ = 0.65 vs. 0.81) and WO (κ = 0.53 vs. 0.78). Qualitative LI-RADS showed an AUC of 0.86, 0.94, 0.94, and 0.91 for readers 1, 2, 3, and 4, respectively. The quantitative LI-RADS score where APHE/WO/or both were replaced showed an AUC of 0.89/0.84/0.89, 0.95/0.92/0.92, 0.93/0.91/0.89, and 0.91/0.86/0.88 for readers 1, 2, 3, and 4, respectively. Sensitivity of LR-4/5 slightly increased, while specificity slightly decreased using quantitative APHE. CONCLUSION/CONCLUSIONS:Qualitative and quantitative LI-RADS showed similar performance. Quantitatively assessed APHE showed the potential to increase interreader agreement and sensitivity of HCC diagnosis, whereas quantitatively assessed WO had the opposite effect and needs to be redefined. KEY POINTS/CONCLUSIONS:• Quantitative assessment of arterial phase hyperenhancement shows the potential to increase interreader agreement and sensitivity to diagnose hepatocellular carcinoma. • Adding quantitative measurements of major LI-RADS features does not improve accuracy over qualitative assessment alone according to the LI-RADS v2018 algorithm.

PURPOSE/OBJECTIVE:To evaluate a deep learning based image analysis software for the detection and localization of distal radius fractures. METHOD/METHODS:A deep learning system (DLS) was trained on 524 wrist radiographs (166 showing fractures). Performance was tested on internal (100 radiographs, 42 showing fractures) and external test sets (200 radiographs, 100 showing fractures). Single and combined views of the radiographs were shown to DLS and three readers. Readers were asked to indicate fracture location with regions of interest (ROI). The DLS yielded scores (range 0-1) and a heatmap. Detection performance was expressed as AUC, sensitivity and specificity at the optimal threshold and compared to radiologists' performance. Heatmaps were compared to radiologists' ROIs. RESULTS:The DLS showed excellent performance on the internal test set (AUC 0.93 (95% confidence interval (CI) 0.82-0.98) - 0.96 (0.87-1.00), sensitivity 0.81 (0.58-0.95) - 0.90 (0.70-0.99), specificity 0.86 (0.68-0.96) - 1.0 (0.88-1.0)). DLS performance decreased on the external test set (AUC 0.80 (0.71-0.88) - 0.89 (0.81-0.94), sensitivity 0.64 (0.49-0.77) - 0.92 (0.81-0.98), specificity 0.60 (0.45-0.74) - 0.90 (0.78-0.97)). Radiologists' performance was comparable on internal data (sensitivity 0.71 (0.48-0.89) - 0.95 (0.76-1.0), specificity 0.52 (0.32-0.71) - 0.97 (0.82-1.0)) and better on external data (sensitivity 0.88 (0.76-0.96) - 0.98 (0.89-1.0), specificities 0.66 (0.51-0.79) - 1.0 (0.93-1.0), p < 0.05). In over 90%, the areas of peak activation aligned with radiologists' annotations. CONCLUSIONS:The DLS was able to detect and localize wrist fractures with a performance comparable to radiologists, using only a small dataset for training.

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.

A first analysis of simultaneous ⁶⁸Ga-prostate-specific membrane antigen (PSMA)-11 PET/MRI showed some improvement in the detection of recurrent disease at low serum prostate specific antigen (PSA) values below 0.5 ng/mL compared with the already high detection rate of ⁶⁸Ga-PSMA-11 PET/CT. We therefore focused on all patients with biochemical recurrence and PSA values no higher than 0.5 ng/mL to assess the detection rate for ⁶⁸Ga-PSMA-11 PET/MRI. Methods: We retrospectively analyzed a cohort of 66 consecutive patients who underwent ⁶⁸Ga-PSMA-11 PET/MRI for biochemical recurrence with a PSA value no higher than 0.5 ng/mL at our institution. Median PSA level was 0.23 ng/mL (range, 0.03-0.5 ng/mL). Detection of PSMA-positive lesions within the prostate fossa, local and distant lymph nodes, bones, or visceral organs was recorded. In addition, all scans with ⁶⁸Ga-PSMA-11 PET/MRI-positive lesions were retrospectively assessed to analyze if lesions were detected inside or outside a standard salvage radiotherapy volume. Results: Overall, in 36 of 66 patients (54.5%) PSMA-positive lesions were detected; in 26 of 40 (65%) patients with a PSA level between 0.2 and 0.5 ng/mL and in 10 of 26 (38.5%) patients with a PSA level less than 0.2 ng/mL. Even at those low PSA values, only 8 of 66 (12.1%) patients had exclusive local recurrence. Lymph nodes were detected in 23 patients and bone metastases in 5 on ⁶⁸Ga-PSMA-11 PET/MRI. In 26 of 66 patients (39.4%), PSMA-positive lesions were located outside a standard salvage radiotherapy volume. Conclusion: Our data confirm that ⁶⁸Ga-PSMA-11 PET/MRI has a high detection rate for recurrent prostate cancer, even at low PSA levels no higher than 0.5 ng/mL. In addition, we show that ⁶⁸Ga-PSMA-11 PET/MRI detected PSMA-positive lesions outside a standard salvage radiotherapy volume in 39.4% of all patients.

In this prospective study, we quantified the fast pseudo-diffusion contamination by blood perfusion or cerebrospinal fluid (CSF) intravoxel incoherent movements on the measurement of the diffusion tensor metrics in healthy brain tissue. Diffusion-weighted imaging (TR/TE = 4100 ms/90 ms; b-values: 0, 5, 10, 20, 35, 55, 80, 110, 150, 200, 300, 500, 750, 1000, 1300 s/mm², 20 diffusion-encoding directions) was performed on a cohort of five healthy volunteers at 3 Tesla. The projections of the diffusion tensor along each diffusion-encoding direction were computed using a two b-value approach (2b), by fitting the signal to a monoexponential curve (mono), and by correcting for fast pseudo-diffusion compartments using the biexponential intravoxel incoherent motion model (IVIM) (bi). Fractional anisotropy (FA) and mean diffusivity (MD) of the diffusion tensor were quantified in regions of interest drawn over white matter areas, gray matter areas, and the ventricles. A significant dependence of the MD from the evaluation method was found in all selected regions. A lower MD was computed when accounting for the fast-diffusion compartments. A larger dependence was found in the nucleus caudatus (bi: median 0.86 10^-3 mm²/s, Δ2b: -11.2%, Δmono: -14.4%; p = 0.007), in the anterior horn (bi: median 2.04 10^-3 mm²/s, Δ2b: -9.4%, Δmono: -11.5%, p = 0.007) and in the posterior horn of the lateral ventricles (bi: median 2.47 10^-3 mm²/s, Δ2b: -5.5%, Δmono: -11.7%; p = 0.007). Also for the FA, the signal modeling affected the computation of the anisotropy metrics. The deviation depended on the evaluated region with significant differences mainly in the nucleus caudatus (bi: median 0.15, Δ2b: +39.3%, Δmono: +14.7%; p = 0.022) and putamen (bi: median 0.19, Δ2b: +3.1%, Δmono: +17.3%; p = 0.015). Fast pseudo-diffusive regimes locally affect diffusion tensor imaging (DTI) metrics in the brain. Here, we propose the use of an IVIM-based method for correction of signal contaminations through CSF or perfusion.

OBJECTIVE:data from cervical cancer patients. MATERIALS AND METHODS:data. RESULTS:data showed that the optimal threshold was 40 s/mm² for patients with squamous cell carcinoma and a subsampled acquisition of six b-values (scan time, 198 seconds) estimated parameters were not significantly different from reference parameters (individual parameter error rates of less than 5%). In patients with adenocarcinoma, the optimal threshold was 100 s/mm², but an optimal subsample could not be identified. Irrespective of the histological subtype, only three b-values were needed for simplified IVIM, but these parameters did not retain their discriminative ability. CONCLUSION:Subsampling of six b-values halved the IVIM scan time without significant losses in accuracy and discriminative ability. Simplified IVIM is possible with only three b-values, at the risk of losing diagnostic information.