Faculty Bibliography

BACKGROUND:F-FDG dose for a 10-min time-of-flight (TOF) PET/MR acquisition that would still allow accurate quantification of supraclavicular BAT volume and activity. METHODS:Twenty datasets from 13 volunteers were retrospectively included from a prospective clinical study. PET emission datasets were modified to simulate step-wise reductions of the original 75 MBq injected dose. The resulting PET images were visually and quantitatively assessed and compared to a 4-min reference scan. For the visual assessment, the image quality and artifacts were scored using a 5-point and a 3-point Likert scale. For the quantitative analysis, image noise and artifacts, BAT metabolic activity, BAT metabolic volume (BMV), and total BAT glycolysis (TBG) were investigated. RESULTS:The visual assessment showed still good image quality for the 35%, 30%, and 25% activity reconstructions with no artifacts. Quantitatively, the background noise was similar to the reference for the 35% and 30% activity reconstructions and the artifacts started to increase significantly in the 25% and lower activity reconstructions. There was no significant difference in supraclavicular BAT metabolic activity, BMV, and TBG between the reference and the 35% to 20% activity reconstructions. CONCLUSIONS:F-FDG tracer dose can be reduced to approximately 19 MBq (25%) while maintaining image quality and accurate supraclavicular BAT quantification. This could decrease the effective dose from 1.4 mSv to 0.36 mSv.

OBJECTIVES:Non-Cartesian Spiral readout can be implemented in 3D Time-of-flight (TOF) MR angiography (MRA) with short acquisition times. In this intra-individual comparison study we evaluated the clinical feasibility of Spiral TOF MRA in comparison with compressed sensing accelerated TOF MRA at 1.5T for intracranial vessel imaging as it has yet to be determined. MATERIALS AND METHODS:Forty-four consecutive patients with suspected intracranial vascular disease were imaged with two Spiral 3D TOFs (Spiral, 0.82x0.82x1.2 mm3, 01:32 min; Spiral 0.8, 0.8x0.8x0.8 mm3, 02:12 min) and a Compressed SENSE accelerated 3D TOF (CS 3.5, 0.82x0.82x1.2 mm3, 03:06 min) at 1.5T. Two neuroradiologists assessed qualitative (visualization of central and peripheral vessels) and quantitative image quality (Contrast Ratio, CR) and performed lesion and variation assessment for all three TOFs in each patient. After the rating process, the readers were questioned and representative cases were reinspected in a non-blinded fashion. For statistical analysis, the Friedman and Nemenyi post-hoc test, Kendall W tests, repeated measure ANOVA and weighted Cohen's Kappa tests were used. RESULTS:The Spiral and Spiral 0.8 outperformed the CS 3.5 in terms of peripheral image quality (p<0.001) and performed equally well in terms of central image quality (p>0.05). The readers noted slight differences in the appearance of maximum intensity projection images. A good to high degree of interstudy agreement between the three TOFs was observed for lesion and variation assessment (W = 0.638, p<0.001 -W = 1, p<0.001). CR values did not differ significantly between the three TOFs (p = 0.534). Interreader agreement ranged from good (K = 0.638) to excellent (K = 1). CONCLUSIONS:Compared to the CS 3.5, both the Spiral and Spiral 0.8 exhibited comparable or better image quality and comparable diagnostic performance at much shorter acquisition times.

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.

Quantitative assessment of functional perfusion capacity and vessel architecture is critical when validating biomaterials for regenerative medicine purposes and requires high-tech analytical methods. Here, combining two clinically relevant imaging techniques, (magnetic resonance imaging; MRI and microcomputed tomography; MicroCT) and using the chorioallantoic membrane (CAM) assay, we present and validate a novel functional and morphological three-dimensional (3D) analysis strategy to study neovascularization in biomaterials relevant for bone regeneration. Using our new pump-assisted approach, the two scaffolds, Optimaix (laminar structure mimicking entities of the diaphysis) and DegraPol (highly porous resembling spongy bone), were shown to directly affect the architecture of the ingrowing neovasculature. Perfusion capacity (MRI) and total vessel volume (MicroCT) strongly correlated for both biomaterials, suggesting that our approach allows for a comprehensive evaluation of the vascularization pattern and efficiency of biomaterials. Being compliant with the 3R-principles (replacement, reduction and refinement), the well-established and easy-to-handle CAM model offers many advantages such as low costs, immune-incompetence and short experimental times with high-grade read-outs when compared to conventional animal models. Therefore, combined with our imaging-guided approach it represents a powerful tool to study angiogenesis in biomaterials.

PURPOSE/OBJECTIVE:To evaluate the interreader variability in prostate and seminal vesicle (SV) segmentation on T2w MRI. METHODS:Six readers segmented the peripheral zone (PZ), transitional zone (TZ) and SV slice-wise on axial T2w prostate MRI examinations of n = 80 patients. Twenty different similarity scores, including dice score (DS), Hausdorff distance (HD) and volumetric similarity coefficient (VS), were computed with the VISCERAL EvaluateSegmentation software for all structures combined and separately for the whole gland (WG = PZ + TZ), TZ and SV. Differences between base, midgland and apex were evaluated with DS slice-wise. Descriptive statistics for similarity scores were computed. Wilcoxon testing to evaluate differences of DS, HD and VS was performed. RESULTS:Overall segmentation variability was good with a mean DS of 0.859 (±SD = 0.0542), HD of 36.6 (±34.9 voxels) and VS of 0.926 (±0.065). The WG showed a DS, HD and VS of 0.738 (±0.144), 36.2 (±35.6 vx) and 0.853 (±0.143), respectively. The TZ showed generally lower variability with a DS of 0.738 (±0.144), HD of 24.8 (±16 vx) and VS of 0.908 (±0.126). The lowest variability was found for the SV with DS of 0.884 (±0.0407), HD of 17 (±10.9 vx) and VS of 0.936 (±0.0509). We found a markedly lower DS of the segmentations in the apex (0.85 ± 0.12) compared to the base (0.87 ± 0.10, p < 0.01) and the midgland (0.89 ± 0.10, p < 0.001). CONCLUSIONS:We report baseline values for interreader variability of prostate and SV segmentation on T2w MRI. Variability was highest in the apex, lower in the base, and lowest in the midgland.

BACKGROUND:Our aims were to determine if features derived from texture analysis (TA) can distinguish normal, benign, and malignant tissue on automated breast ultrasound (ABUS); to evaluate whether machine learning (ML) applied to TA can categorise ABUS findings; and to compare ML to the analysis of single texture features for lesion classification. METHODS:This ethically approved retrospective pilot study included 54 women with benign (n = 38) and malignant (n = 32) solid breast lesions who underwent ABUS. After manual region of interest placement along the lesions' margin as well as the surrounding fat and glandular breast tissue, 47 texture features (TFs) were calculated for each category. Statistical analysis (ANOVA) and a support vector machine (SVM) algorithm were applied to the texture feature to evaluate the accuracy in distinguishing (i) lesions versus normal tissue and (ii) benign versus malignant lesions. RESULTS:Skewness and kurtosis were the only TF significantly different among all the four categories (p < 0.000001). In subsets (i) and (ii), a maximum area under the curve of 0.86 (95% confidence interval [CI] 0.82-0.88) for energy and 0.86 (95% CI 0.82-0.89) for entropy were obtained. Using the SVM algorithm, a maximum area under the curve of 0.98 for both subsets was obtained with a maximum accuracy of 94.4% in subset (i) and 90.7% in subset (ii). CONCLUSIONS:TA in combination with ML might represent a useful diagnostic tool in the evaluation of breast imaging findings in ABUS. Applying ML techniques to TFs might be superior compared to the analysis of single TF.

CONTEXT:Recent studies suggested that magnetic resonance imaging (MRI) followed by targeted biopsy ("MRI-stratified pathway") detects more clinically significant prostate cancers (csPCa) than the systematic transrectal ultrasound-guided prostate biopsy (TRUS-Bx) pathway, but controversy persists. Several randomized clinical trials (RCTs) were recently published, enabling generation of higher-level evidence to evaluate this hypothesis. OBJECTIVE:To perform a systematic review and meta-analysis of RCTs comparing the detection rates of csPCa in the MRI-stratified pathway and the systematic TRUS-Bx pathway in patients with a suspicion of prostate cancer (PCa). EVIDENCE ACQUISITION:PubMed, EMBASE, and Cochrane databases were searched up to March 18, 2019. RCTs reporting csPCa detection rates of both pathways in patients with a clinical suspicion of prostate cancer were included. Relative csPCa detection rates of the MRI-stratified pathway were pooled using random-effect model. Study quality was assessed using the Cochrane risk of bias tool for randomized trials. A comparison of detection rates of clinically insignificant PCa (cisPCa) and any PCa was also performed. EVIDENCE SYNTHESIS:Nine RCTs (2908 patients) were included. The MRI-stratified pathway detected more csPCa than the TRUS-Bx pathway (relative detection rate 1.45 [95% confidence interval {CI} 1.09-1.92] for all patients, and 1.42 [95% CI 1.02-1.97] and 1.60 [95% CI 1.01-2.54] for biopsy-naïve and prior negative biopsy patients, respectively). Detection rates were not significantly different between pathways for cisPCa (0.89 [95% CI 0.49-1.62]), but higher in the MRI-stratified pathway for the detection of any PCa (1.39 [95% CI 1.05-1.84]). CONCLUSIONS:The MRI-stratified pathway detected more csPCa than the systematic TRUS-guided biopsy pathway in men with a clinical suspicion of PCa, for both biopsy-naïve patients and those with prior negative biopsy. The detection rate of any PCa was higher in the MRI-stratified pathway, but not significantly different from that of cisPCa. PATIENT SUMMARY:Our meta-analysis of clinical trials shows that the magnetic resonance imaging-stratified pathway detects more clinically significant prostate cancers than the transrectal ultrasound-guided prostate biopsy pathway in men with a suspicion of prostate cancer.

Background Recent studies have reported the additive value of combined gallium 68 (⁶⁸Ga)-labeled Glu-urea-Lys (Ahx)-HBED-CC ligand targeting the prostate-specific membrane antigen (PSMA) (hereafter called ⁶⁸Ga-PSMA-11) PET/MRI for the detection and localization of primary prostate cancer compared with multiparametric MRI. Purpose To compare the diagnostic accuracy and interrater agreement of multiparametric MRI and ⁶⁸Ga-PSMA-11 PET/MRI for the detection of extracapsular extension (ECE) and seminal vesicle infiltration (SVI) in patients with prostate cancer. Materials and Methods Retrospective analysis of 40 consecutive men who underwent multiparametric MRI and ⁶⁸Ga-PSMA-11 PET/MRI within 6 months for suspected prostate cancer followed by radical prostatectomy between April 2016 and July 2018. Four readers blinded to clinical and histopathologic findings rated the probability of ECE and SVI at multiparametric MRI and PET/MRI by using a five-point Likert-type scale. The prostatectomy specimen served as the reference standard. Accuracy was assessed with a multireader multicase analysis and by calculating reader-average areas under the receiver operating characteristics curve (AUCs), sensitivity, and specificity for ordinal and dichotomized data in a region-specific and patient-specific approach. Interrater agreement was assessed with the Fleiss multirater κ. Results For multiparametric MRI versus PET/MRI in ECE detection, respectively, AUC, sensitivity, and specificity in the region-specific analysis were 0.67 and 0.75 (P = .07), 28% (21 of 76) and 47% (36 of 76) (P = .09), and 94% (529 of 564) and 90% (509 of 564) (P = .007). For the patient-specific analysis, AUC, sensitivity, and specificity were 0.66 and 0.73 (P = .19), 46% (22 of 48) and 69% (33 of 48) (P = .04), and 75% (84 of 112) and 67% (75 of 112) (P = .19), respectively. For multiparametric MRI versus PET/MRI in SVI detection, respectively, AUC, sensitivity, and specificity of the region-specific analysis were 0.66 and 0.74 (P = .21), 35% (seven of 20) and 50% (10 of 20) (P = .25), and 98% (295 of 300) and 94% (282 of 300) (P < .001). For the patient-specific analysis, AUC, sensitivity, and specificity were 0.65 and 0.79 (P = .25), 35% (seven of 20) and 55% (11 of 20) (P = .20), and 98% (137 of 140) and 94% (131 of 140) (P = .07), respectively. Interrater reliability for multiparametric MRI versus PET/MRI did not differ for ECE (κ, 0.46 vs 0.40; P = .24) and SVI (κ, 0.23 vs 0.33; P = .39). Conclusion Our results suggest that gallium 68 (⁶⁸Ga)-labeled Glu-urea-Lys (Ahx)-HBED-CC ligand targeting the prostate-specific membrane antigen (PSMA) (⁶⁸Ga-PSMA-11) PET/MRI and multiparametric MRI perform similarly for local staging of prostate cancer in patients with intermediate-to-high-risk prostate cancer. The increased sensitivity of ⁶⁸Ga-PSMA-11 PET/MRI for the detection of extracapsular disease comes at the cost of a slightly reduced specificity. © RSNA, 2019.

PURPOSE/OBJECTIVE:To train a CycleGAN on downscaled versions of mammographic data to artificially inject or remove suspicious features, and to determine whether these AI-mediated attacks can be detected by radiologists. MATERIAL AND METHODS/METHODS:From two publicly available datasets, BCDR and INbreast, we selected 680 images with and without lesions as training data. An internal dataset (n = 302 cancers, n = 590 controls) served as test data. We ran two experiments (256 × 256 px and 512 × 408 px) and applied the trained model to the test data. Three radiologists read a set of images (modified and originals) and rated the presence of suspicious lesions on a scale from 1 to 5 and the likelihood of the image being manipulated. The readout was evaluated by multiple reader multiple case receiver operating characteristics (MRMC-ROC) analysis using the area under the curve (AUC). RESULTS:At the lower resolution, the overall performance was not affected by the CycleGAN modifications (AUC 0.70 vs. 0.76, p = 0.67). However, one radiologist exhibited lower detection of cancer (0.85 vs 0.63, p = 0.06). The radiologists could not discriminate between original and modified images (0.55, p = 0.45). At the higher resolution, all radiologists showed significantly lower detection rate of cancer in the modified images (0.80 vs. 0.37, p < 0.001), however, they were able to detect modified images due to better visibility of artifacts (0.94, p < 0.0001). CONCLUSION/CONCLUSIONS:Our proof-of-concept study shows that CycleGAN can implicitly learn suspicious features and artificially inject or remove them in existing images. The applicability of the method is currently limited by the small image size and introduction of artifacts.

PURPOSE/OBJECTIVE:To compare the correlation of transition zone prostate-specific antigen density (TZPSAD) versus whole gland (WG) density (PSAD) with Gleason score. METHODS:In this single-center, retrospective cohort study, men undergoing MRI of the prostate in 2015 and 2016 who had a transperineal template saturation biopsy within 6 months of MRI were included (n = 178; median age 64 y, interquartile range [IQR] 58-68 y; PSA 6.6 ng/ml, 4.6-9.7 ng/ml). The WG and TZ were segmented voxel-wise on T2-weighted transverse planes. The volumes and corresponding PSA-densities were calculated. Correlations with the Gleason score were assessed with Spearman's rho. Optimal thresholds of the PSA densities were computed using the Youden Index of the receiver-operating-characteristics curve. A p-value of ≤ 0.05 was considered statistically significant. RESULTS:) for discrimination between Gleason 3 + 4 and 4 + 3. CONCLUSION/CONCLUSIONS:may help in risk stratification of men with suspected PCa.