Reduction of false positives using zone-specific prostate-specific antigen density for prostate MRI-based biopsy decision strategies.

OBJECTIVES: To develop and test zone-specific prostate-specific antigen density (sPSAD) combined with PI-RADS to guide prostate biopsy decision strategies (BDS). METHODS: This retrospective study included consecutive patients, who underwent prostate MRI and biopsy (01/2012-10/2018). The whole gland and transition zone (TZ) were segmented at MRI using a retrained deep learning system (DLS; nnU-Net) to calculate PSAD and sPSAD, respectively. Additionally, sPSAD and PI-RADS were combined in a BDS, and diagnostic performances to detect Grade Group ≥ 2 (GG ≥ 2) prostate cancer were compared. Patient-based cancer detection using sPSAD was assessed by bootstrapping with 1000 repetitions and reported as area under the curve (AUC). Clinical utility of the BDS was tested in the hold-out test set using decision curve analysis. Statistics included nonparametric DeLong test for AUCs and Fisher-Yates test for remaining performance metrics. RESULTS: A total of 1604 patients aged 67 (interquartile range, 61-73) with 48% GG ≥ 2 prevalence (774/1604) were evaluated. By employing DLS-based prostate and TZ volumes (DICE coefficients of 0.89 (95% confidence interval, 0.80-0.97) and 0.84 (0.70-0.99)), GG ≥ 2 detection using PSAD was inferior to sPSAD (AUC, 0.71 (0.68-0.74)/0.73 (0.70-0.76); p < 0.001). Combining PI-RADS with sPSAD, GG ≥ 2 detection specificity doubled from 18% (10-20%) to 43% (30-44%; p < 0.001) with similar sensitivity (93% (89-96%)/97% (94-99%); p = 0.052), when biopsies were taken in PI-RADS 4-5 and 3 only if sPSAD was ≥ 0.42 ng/mL/cc as compared to all PI-RADS 3-5 cases. Additionally, using the sPSAD-based BDS, false positives were reduced by 25% (123 (104-142)/165 (146-185); p < 0.001). CONCLUSION: Using sPSAD to guide biopsy decisions in PI-RADS 3 lesions can reduce false positives at MRI while maintaining high sensitivity for GG ≥ 2 cancers. CLINICAL RELEVANCE STATEMENT: Transition zone-specific prostate-specific antigen density can improve the accuracy of prostate cancer detection compared to MRI assessments alone, by lowering false-positive cases without significantly missing men with ISUP GG ≥ 2 cancers. KEY POINTS: • Prostate biopsy decision strategies using PI-RADS at MRI are limited by a substantial proportion of false positives, not yielding grade group ≥ 2 prostate cancer. • PI-RADS combined with transition zone (TZ)-specific prostate-specific antigen density (PSAD) decreased the number of unproductive biopsies by 25% compared to PI-RADS only. • TZ-specific PSAD also improved the specificity of MRI-directed biopsies by 9% compared to the whole gland PSAD, while showing identical sensitivity.

Metadata-independent classification of MRI sequences using convolutional neural networks: Successful application to prostate MRI.

PURPOSE: The ever-increasing volume of medical imaging data and interest in Big Data research brings challenges to data organization, categorization, and retrieval. Although the radiological value chain is almost entirely digital, data structuring has been widely performed pragmatically, but with insufficient naming and metadata standards for the stringent needs of image analysis. To enable automated data management independent of naming and metadata, this study focused on developing a convolutional neural network (CNN) that classifies medical images based solely on voxel data. METHOD: A 3D CNN (3D-ResNet18) was trained using a dataset of 31,602 prostate MRI volumes with 10 different sequence types of 1243 patients. A five-fold cross-validation approach with patient-based splits was chosen for training and testing. Training was repeated with a gradual reduction in training data assessing classification accuracies to determine the minimum training data required for sufficient performance. The trained model and developed method were tested on three external datasets. RESULTS: The model achieved an overall accuracy of 99.88 % ± 0.13 % in classifying typical prostate MRI sequence types. When being trained with approximately 10 % of the original cohort (112 patients), the CNN still achieved an accuracy of 97.43 % ± 2.10 %. In external testing the model achieved sensitivities of > 90 % for 10/15 tested sequence types. CONCLUSIONS: The herein developed CNN enabled automatic and reliable sequence identification in prostate MRI. Ultimately, such CNN models for voxel-based sequence identification could substantially enhance the management of medical imaging data, improve workflow efficiency and data quality, and allow for robust clinical AI workflows.

Treatment of right hepatic artery stump bleeding after pylorus-preserving pancreaticoduodenectomy by covered stent endoprosthesis placement.

Serious complications after pancreaticoduodenectomy include rupture of pseudoaneurysms arising from pancreatic fistula and pancreatojejunostomy leakage. We report a case of successful endovascular minimally invasive treatment using a covered stent endoprosthesis of a right hepatic artery stump bleeding following pylorus-preserving pancreaticoduodenectomy that was not suitable for coil or glue embolization due to an insufficiently short neck.

Tunneled hemodialysis catheter insertion: Above, within, or below the right atrium-Where is the tip?

Background: One major challenge when inserting a tunneled, cuffed central venous catheter (CVC) for hemodialysis under fluoroscopy is to accurately place the catheter tip by assessing its position in relation to the cardiac silhouette to approximate the right atrium (RA). Purpose: To investigate whether a weighted mean calculated from published results for two two-dimensional landmark reference distances may be useful in assessing CVC tip positions in relation to the RA. Material and Methods: Central venous catheter tip positions attained under fluoroscopic imaging during insertion using the cardiac silhouette as approximation were retrospectively related to two reference distances (carina to cranial RA border and craniocaudal RA extent), which were used to group catheter tip locations above (1), within (2), or below (3) the RA (henceforth referred to as landmark technique approximation, LTA). The LTA-derived catheter tip locations were validated by correlation with postinterventional computed tomography (CT) datasets acquired shortly after implantation (if available). Results: Based on LTA, 45 catheter tips (10.6%) were above, 179 (42.2%) within, and 200 (47.2%) below the RA. Postinterventional CT (n = 57; 13.4%) visualized 26.3% above, 66.7% within, and 7.0% below the RA. Conclusion: The LTA reference distances appear to lead to a rather low categorization of the CVC tips, or the tips have been placed rather low in the study population. Validation using postinterventional CT indicated an underestimation of the RA in the LTA. Patient characteristics with a higher risk of false estimation through LTA have been defined.

Clinical utility of combined T2-weighted imaging and T2-mapping in the detection of prostate cancer: a multi-observer study.

BACKGROUND: To evaluate the clinical utility of combined T2-weighted imaging and T2-mapping for the detection of prostate cancer. METHODS: Forty patients underwent multiparametric magnetic resonance imaging (mpMRI) and T2-mapping of the prostate. Three readers each reviewed two sets of images: T2-weighted fast spin-echo (FSE) sequence (standard T2), and standard T2 in combination with T2-mapping. Each reader assigned probability scores for malignancy to each zone [peripheral zone (PZ) or transition zone (TZ)]. Inter-observer variability for standard T2 and combined standard T2 with T2-mapping were assessed. Diagnostic accuracy was compared between standard T2 and combined standard T2 with T2-mapping. RESULTS: There was fair agreement between all three readers for standard T2 [intraclass correlation coefficient (ICC) =0.56] and combined standard T2 with T2-mapping (ICC =0.58). There was no significant difference in the area under the receiver operator characteristics curve for standard T2 compared to combined standard T2 with T2-mapping (0.89 vs. 0.82, P=0.31). Sensitivity (Sn) for combined standard T2 with T2-mapping was significantly higher compared to standard T2 alone (73.0% vs. 49.2%, P=0.006). Specificity (Sp) for combined standard T2 with T2-mapping was borderline significantly lower compared to standard T2 alone (89.3% vs. 94.9%, P=0.05). There was no significant differences between the negative predictive values (NPVs) and positive predictive values (PPVs) (P=0.07, P=0.45). CONCLUSIONS: Combination of T2-weighted imaging and T2-mapping could potentially increase Sn for prostate malignancy compared to T2-weighted imaging alone.

Optimizing size thresholds for detection of clinically significant prostate cancer on MRI: Peripheral zone cancers are smaller and more predictable than transition zone tumors.

PURPOSE: To evaluate if size-based cut-offs based on MR imaging can successfully assess clinically significant prostate cancer (csPCA). The goal was to improve the currently applied size-based differentiation criterion in PI-RADS. METHODS AND MATERIALS: MRIs of 293 patients who had undergone 3 T MR imaging with subsequent confirmation of prostate cancer on systematic and targeted MRI/TRUS-fusion biopsy were re-read by three radiologists. All identifiable tumors were measured on T2WI for lesions originating in the transition zone (TZ) and on DWI for lesions from the peripheral zone (PZ) and tabulated against their Gleason grade. RESULTS: 309 lesions were analyzed, 213 (68.9 %) in the PZ and 96 (31.1 %) in the TZ. ROC-Analysis showed a stronger correlation between lesion size and clinically significant (defined as Gleason Grade Group ≥ 2) prostate cancer (PCa) for the PZ (AUC = 0.73) compared to the TZ (AUC = 0.63). The calculated Youden index resulted in size cut-offs of 14 mm for PZ and 21 mm for TZ tumors. CONCLUSION: Size cut-offs can be used to stratify prostate cancer with different optimal size thresholds in the peripheral zone and transition zone. There was a clearer separation of clinically significant tumors in peripheral zone cancers compared to transition zone cancers. Future iterations of PI-RADS could therefore take different size-based cut-offs for peripheral zone and transition zone cancers into account.

In Vivo Quantification of Water Diffusion, Stiffness, and Tissue Fluidity in Benign Prostatic Hyperplasia and Prostate Cancer.

OBJECTIVES: Water diffusion, tissue stiffness, and viscosity characterize the biophysical behavior of tumors. However, little is known about how these parameters correlate in prostate cancer (PCa). Therefore, we paired tomoelastography of the prostate with diffusion-sensitive magnetic resonance imaging for the quantitative mapping of biophysical parameters in benign prostatic hyperplasia (BPH) and PCa. MATERIALS AND METHODS: Multifrequency magnetic resonance imaging elastography with tomoelastography processing was performed at 60, 70, and 80 Hz using externally placed compressed-air drivers. Shear-wave speed (SWS) and loss angle (φ) were analyzed as surrogate markers of stiffness and viscosity-related fluidity in the normal peripheral zone (PZ), hyperplastic transition zone (TZ), which is consistent with BPH, and PCa lesions. The SWS and φ were correlated with the normalized apparent diffusion coefficient (nADC). RESULTS: Thirty-nine men (median age/range, 67/49-88 years), 25 with BPH and 14 with biopsy-proven PCa, were prospectively enrolled in this institutional review board-approved study. The SWS in PCa (3.1 ± 0.6 m/s) was higher than in TZ (2.8 ± 0.3 m/s, P = 0.004) or tended to be higher than in PZ (2.8 ± 0.4 m/s, P = 0.025). Similarly, φ in PCa (1.1 ± 0.1 rad) was higher than in TZ (0.9 ± 0.2 m/s, P < 0.001) and PZ (0.9 ± 0.1 rad, P < 0.001), whereas nADC in PCa (1.3 ± 0.3) was lower than in TZ (2.2 ± 0.4, P < 0.001) and PZ (3.1 ± 0.7, P < 0.001). Pooled nADC was inversely correlated with φ (R = -0.6, P < 0.001) but not with SWS. TZ and PZ only differed in nADC (P < 0.001) but not in viscoelastic properties. Diagnostic differentiation of PCa from normal prostate tissues, as assessed by area under the curve greater than 0.9, was feasible using nADC and φ but not SWS. CONCLUSIONS: Tomoelastography provides quantitative maps of tissue mechanical parameters of the prostate. Prostate cancer is characterized by stiff tissue properties and reduced water diffusion, whereas, at the same time, tissue fluidity is increased, suggesting greater mechanical friction inside the lesion. This biophysical signature correlates with known histopathological features including increased cell density and fibrous protein accumulation.

Reducing the dose of CT of the paranasal sinuses: potential of an iterative reconstruction algorithm.

OBJECTIVE: To evaluate the feasibility and image quality of low-dose CT of the paranasal sinuses using iterative reconstruction with adaptive-iterative dose reduction in three dimensions (AIDR 3D) in comparison with conventional image protocols of older scanner generations. METHODS: Sinus CT scans of 136 patients were assessed retrospectively. Patients underwent CT either with low-dose settings (Protocol A: 80 kV, 30 mA s; Protocol B: 120 kV, 15 mA s or C: 80 kV, 90 mA s) reconstructed using AIDR 3D (Protocols A and B) or filtered back projection (FBP) (Protocol C) or with standard dose (Protocol D: 120 kV, 80 mA s) and FBP. Image quality was assessed in consensus by two blinded readers scoring the diagnostic image quality (from 1 = excellent to 5 = non-diagnostic) and conspicuity of important anatomic landmarks (from 0 = not visible to 2 = completely visible; maximum score of 16 points) as well as osseous structures (maximum score of 12 points). Dose-length product, effective dose (ED), CT dose index and scan length were retrieved for each scan and compared. RESULTS: Mean ED could be lowered by 82% when using Protocol A. The best image quality was found using Protocol B (mean score = 2.1 ± 0.51). Conspicuity of relevant anatomic landmarks was best with Protocol A (mean score = 11.97 ± 1.88). Protocol B provided the highest conspicuity of osseous structures (mean score = 8.27 ± 1.58). Image noise was highest in images obtained using Protocol A. CONCLUSIONS: AIDR 3D allows a significant dose reduction while maintaining a good diagnostic image quality and conspicuity of relevant anatomic structures.

Estimating fat mass in heart failure patients.

INTRODUCTION: Body composition (BC) assessments in heart failure (HF) patients are mainly based on body weight, body mass index and waist-to-hip ratio. The present study compares BC assessments by basic anthropometry, dual energy X-ray absorptiometry (DXA), bioelectrical impedance spectroscopy (BIS), and air displacement plethysmography (ADP) for the estimation of fat (FM) and fat-free mass (FFM) in a HF population. MATERIAL AND METHODS: In this single-centre, observational pilot study we enrolled 52 patients with HF (33 HF with reduced ejection fraction (HFrEF), 19 HF with preserved ejection fraction (HFpEF); mean age was 67.7 ±9.9 years, 41 male) and 20 healthy controls. DXA was used as a reference standard for the measurement of FM and FFM. RESULTS: In the HF population, linear regression for DXA-FM and waist-to-hip ratio (r = -0.05, 95% CI: (-0.32)-0.23), body mass index (r = 0.47, 95% CI: 0.23-0.669), and body density (r = -0.87, 95% CI: (-0.93)-(-0.87)) was obtained. In HF, Lin's concordance correlation coefficient of DXA-FM (%) with ADP-FM (%) was 0.76 (95% CI: 0.64-0.85) and DXA-FFM [kg] with DXA-ADP [kg] was 0.93 (95% CI: 0.88-0.96). DXA-FM (%) for BIS-FM (%) was 0.69 (95% CI: 0.54-0.80) and 0.73 (95% CI: 0.60-0.82) for DXA-FFM [kg] and BIS-FFM [kg]. CONCLUSIONS: Body density is a useful surrogate for FM. ADP was found suitable for estimating FM (%) and FFM [kg] in HF patients. BIS showed acceptable results for the estimation of FM (%) in HFrEF and for FFM [kg] in HFpEF patients. We encourage selecting a suitable method for BC assessment according to the compartment of interest in the HF population.