Utility of ADC Values for Differentiating Uterine Sarcomas From Leiomyomas: Systematic Review and Meta-Analysis.

Background: Uterine sarcomas are rare; however, they display imaging features that overlap those of leiomyomas. The potential for undetected uterine sarcomas is clinically relevant because minimally invasive treatment of leiomyomas may lead to cancer dissemination. ADC values have shown potential for differentiating benign and malignant uterine masses. Objective: The purpose of this study was to perform a systematic review of the diagnostic performance of ADC values in differentiating uterine sarcomas from leiomyomas. Evidence acquisition: We searched three electronic databases (MEDLINE, EMBASE, and Cochrane databases) for studies distinguishing uterine sarcomas from leiomyomas using MRI, including ADC, with pathologic tissue confirmation or imaging follow-up as the reference standard. Data extraction and QUADAS-2 quality assessment were performed. Sensitivity and specificity were pooled using hierarchic models, including bivariate and hierarchic summary ROC models. Metaregression was used to assess the impact of various factors on heterogeneity. Evidence synthesis: Twenty-one studies met study inclusion criteria. Pooled sensitivity and specificity were 89% (95% CI, 82-94%) and 86% (95% CI, 78-92%), respectively. Area under the summary ROC curve was 94% (95% CI, 92-96%). Context of ADC interpretation (i.e., standalone vs part of multiparametric MRI [mpMRI]) was the only factor found to account significantly for heterogeneity (p = .01). Higher specificity (95% [95% CI, 92-99%] vs 82% [95% CI, 75-89%]) and similar sensitivity (94% [95% CI, 89-99%] vs 88% [95% CI, 82-93%]) were observed when ADC was evaluated among mpMRI features as compared with standalone ADC assessment. ADC cutoff values ranged (0.87-1.29 × 10-3 mm2/s) but were not associated with statistically different performance (p = .37). Pooled mean ADC values in sarcomas and leiomyomas were 0.904 × 10-3 mm2/s and 1.287 × 10-3 mm2/s, respectively. Conclusion: As part of mpMRI evaluation of uterine masses, mass ADC value less than 0.904 × 10-3 mm2/s may be a useful test-positive threshold for uterine sarcoma, consistent with a prior expert consensus statement. Institutional protocols may influence locally selected ADC values. Clinical Impact: Using ADC as part of mpMRI assessment improves detection of uterine sarcoma, which could influence candidate selection for minimally invasive treatments.

Performance of O-RADS MRI Score in Differentiating Benign From Malignant Ovarian Teratomas: MR Feature Analysis for Differentiating O-RADS 4 From O-RADS 2.

OBJECTIVE: The aim of the study is to evaluate the performance of the ovarian-adnexal reporting and data system magnetic resonance imaging (O-RADS MRI) score and perform individual MRI feature analysis for differentiating between benign and malignant ovarian teratomas. METHODS: In this institutional review board-approved retrospective study, consecutive patients with a pathology-proven fat-containing ovarian mass imaged with contrast-enhanced MRI (1.5T or 3T) from 2013 to 2022 were included. Two blinded radiologists independently evaluated masses per the O-RADS MRI lexicon, including having a "characteristic" or "large" Rokitansky nodule (RN). Additional features analyzed included the following: nodule size/percentage volume relative to total teratoma volume, presence of bulk/intravoxel fat in the nodule, diffusion restriction in the nodule, angular interface, nodule extension through the teratoma border, presence/type of nodule enhancement pattern (solid versus peripheral), and evidence for metastatic disease. An overall O-RADS MRI score was assigned. Patient and lesion features associated with malignancy were evaluated and used to create a malignant teratoma score. χ2, Fisher's exact tests, receiver operating characteristic curve, and κ analysis was performed. RESULTS: One hundred thirty-seven women (median age 34, range 9-84 years) with 123 benign and 14 malignant lesions were included. Mean teratoma size was 7.3 cm (malignant: 14.4 cm, benign: 6.5 cm). 18/123 (14.6%) of benign teratomas were assigned an O-RADS 4 based on the presence of a "large" (11/18) or "noncharacteristic" (12/18) RN. 12/14 malignant nodules occupied >25% of the total teratoma volume (P = 0.09). Features associated with malignancy included the following: age <18 years, an enhancing noncharacteristic RN, teratoma size >12 cm, irregular cystic border, and extralesional extension; these were incorporated into a malignant teratoma score, with a score of 2 or more associated with area under the curve of 0.991 for reviewer 1 and 0.993 for reviewer 2. Peripheral enhancement in a RN was never seen with malignancy (64/123 benign, 0/14 malignant) and would have appropriated downgraded 9/18 overcalled O-RADS 4 benign teratomas. CONCLUSIONS: O-RADS MRI overcalled 15% (18/123) benign teratomas as O-RADS 4 but correctly captured all malignant teratomas. We propose defining a "characteristic" RN as an intravoxel or bulk fat-containing nodule. Observation of a peripheral rim of enhancement in a noncharacteristic RN allowed more accurate prediction of benignity and should be added to the MRI lexicon for improved O-RADS performance.

Accelerated Diffusion-Weighted Magnetic Resonance Imaging of the Liver at 1.5 T With Deep Learning-Based Image Reconstruction: Impact on Image Quality and Lesion Detection.

OBJECTIVE: To perform image quality comparison between deep learning-based multiband diffusion-weighted sequence (DL-mb-DWI), accelerated multiband diffusion-weighted sequence (accelerated mb-DWI), and conventional multiband diffusion-weighted sequence (conventional mb-DWI) in patients undergoing clinical liver magnetic resonance imaging (MRI). METHODS: Fifty consecutive patients who underwent clinical MRI of the liver at a 1.5-T scanner, between September 1, 2021, and January 31, 2022, were included in this study. Three radiologists independently reviewed images using a 5-point Likert scale for artifacts and image quality factors, in addition to assessing the presence of liver lesions and lesion conspicuity. RESULTS: DL-mb-DWI acquisition time was 65.0 ± 2.4 seconds, significantly (P < 0.001) shorter than conventional mb-DWI (147.5 ± 19.2 seconds) and accelerated mb-DWI (94.3 ± 1.8 seconds). DL-mb-DWI received significantly higher scores than conventional mb-DWI for conspicuity of the left lobe (P < 0.001), sharpness of intrahepatic vessel margin (P < 0.001), sharpness of the pancreatic contour (P < 0.001), in-plane motion artifact (P = 0.002), and overall image quality (P = 0.005) by reader 2. DL-mb-DWI received significantly higher scores for conspicuity of the left lobe (P = 0.006), sharpness of the pancreatic contour (P = 0.020), and in-plane motion artifact (P = 0.042) by reader 3. DL-mb-DWI received significantly higher scores for strength of fat suppression (P = 0.004) and sharpness of the pancreatic contour (P = 0.038) by reader 1. The remaining quality parameters did not reach statistical significance for reader 1. CONCLUSIONS: Novel diffusion-weighted MRI sequence with deep learning-based image reconstruction demonstrated significantly decreased acquisition times compared with conventional and accelerated mb-DWI sequences, while maintaining or improving image quality for routine abdominal MRI. DL-mb-DWI offers a potential alternative to conventional mb-DWI in routine clinical liver MRI.

Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate.

BACKGROUND: Demand for prostate MRI is increasing, but scan times remain long even in abbreviated biparametric MRIs (bpMRI). Deep learning can be leveraged to accelerate T2-weighted imaging (T2WI). PURPOSE: To compare conventional bpMRIs (CL-bpMRI) with bpMRIs including a deep learning-accelerated T2WI (DL-bpMRI) in diagnosing prostate cancer. STUDY TYPE: Retrospective. POPULATION: Eighty consecutive men, mean age 66 years (47-84) with suspected prostate cancer or prostate cancer on active surveillance who had a prostate MRI from December 28, 2020 to April 28, 2021 were included. Follow-up included prostate biopsy or stability of prostate-specific antigen (PSA) for 1 year. FIELD STRENGTH AND SEQUENCES: A 3 T MRI. Conventional axial and coronal T2 turbo spin echo (CL-T2), 3-fold deep learning-accelerated axial and coronal T2-weighted sequence (DL-T2), diffusion weighted imaging (DWI) with b = 50 sec/mm2 , 1000 sec/mm2 , calculated b = 1500 sec/mm2 . ASSESSMENT: CL-bpMRI and DL-bpMRI including the same conventional diffusion-weighted imaging (DWI) were presented to three radiologists (blinded to acquisition method) and to a deep learning computer-assisted detection algorithm (DL-CAD). The readers evaluated image quality using a 4-point Likert scale (1 = nondiagnostic, 4 = excellent) and graded lesions using Prostate Imaging Reporting and Data System (PI-RADS) v2.1. DL-CAD identified and assigned lesions of PI-RADS 3 or greater. STATISTICAL TESTS: Quality metrics were compared using Wilcoxon signed rank test, and area under the receiver operating characteristic curve (AUC) were compared using Delong's test. SIGNIFICANCE: P = 0.05. RESULTS: Eighty men were included (age: 66 ± 9 years; 17/80 clinically significant prostate cancer). Overall image quality results by the three readers (CL-T2, DL-T2) are reader 1: 3.72 ± 0.53, 3.89 ± 0.39 (P = 0.99); reader 2: 3.33 ± 0.82, 3.31 ± 0.74 (P = 0.49); reader 3: 3.67 ± 0.63, 3.51 ± 0.62. In the patient-based analysis, the reader results of AUC are (CL-bpMRI, DL-bpMRI): reader 1: 0.77, 0.78 (P = 0.98), reader 2: 0.65, 0.66 (P = 0.99), reader 3: 0.57, 0.60 (P = 0.52). Diagnostic statistics from DL-CAD (CL-bpMRI, DL-bpMRI) are sensitivity (0.71, 0.71, P = 1.00), specificity (0.59, 0.44, P = 0.05), positive predictive value (0.23, 0.24, P = 0.25), negative predictive value (0.88, 0.88, P = 0.48). CONCLUSION: Deep learning-accelerated T2-weighted imaging may potentially be used to decrease acquisition time for bpMRI. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

A concurrent, deep learning-based computer-aided detection system for prostate multiparametric MRI: a performance study involving experienced and less-experienced radiologists.

OBJECTIVES: To evaluate the effect of a deep learning-based computer-aided diagnosis (DL-CAD) system on experienced and less-experienced radiologists in reading prostate mpMRI. METHODS: In this retrospective, multi-reader multi-case study, a consecutive set of 184 patients examined between 01/2018 and 08/2019 were enrolled. Ground truth was combined targeted and 12-core systematic transrectal ultrasound-guided biopsy. Four radiologists, two experienced and two less-experienced, evaluated each case twice, once without (DL-CAD-) and once assisted by DL-CAD (DL-CAD+). ROC analysis, sensitivities, specificities, PPV and NPV were calculated to compare the diagnostic accuracy for the diagnosis of prostate cancer (PCa) between the two groups (DL-CAD- vs. DL-CAD+). Spearman's correlation coefficients were evaluated to assess the relationship between PI-RADS category and Gleason score (GS). Also, the median reading times were compared for the two reading groups. RESULTS: In total, 172 patients were included in the final analysis. With DL-CAD assistance, the overall AUC of the less-experienced radiologists increased significantly from 0.66 to 0.80 (p = 0.001; cutoff ISUP GG ≥ 1) and from 0.68 to 0.80 (p = 0.002; cutoff ISUP GG ≥ 2). Experienced radiologists showed an AUC increase from 0.81 to 0.86 (p = 0.146; cutoff ISUP GG ≥ 1) and from 0.81 to 0.84 (p = 0.433; cutoff ISUP GG ≥ 2). Furthermore, the correlation between PI-RADS category and GS improved significantly in the DL-CAD + group (0.45 vs. 0.57; p = 0.03), while the median reading time was reduced from 157 to 150 s (p = 0.023). CONCLUSIONS: DL-CAD assistance increased the mean detection performance, with the most significant benefit for the less-experienced radiologist; with the help of DL-CAD less-experienced radiologists reached performances comparable to that of experienced radiologists. KEY POINTS: • DL-CAD used as a concurrent reading aid helps radiologists to distinguish between benign and cancerous lesions in prostate MRI. • With the help of DL-CAD, less-experienced radiologists may achieve detection performances comparable to that of experienced radiologists. • DL-CAD assistance increases the correlation between PI-RADS category and cancer grade.

Characterization of Psychotropic PRN Medications in a Canadian Psychiatric Intensive Care Unit.

BACKGROUND: Pro re nata (PRN) antipsychotics and benzodiazepines are routinely used for the rapid stabilization of acutely agitated patients. Despite the popular use of PRN medications in mental health units, primary literature supporting efficacy and safety is poor, and there is no single universally accepted practice guideline. PRN psychotropic medications have the potential to cause adverse effects when used inappropriately. AIMS: Our objective was to characterize the prescribing, administration, and documentation practices of PRN psychotropic medications in a psychiatric intensive care unit. METHODS: We conducted a retrospective chart review of patients admitted to a 12-bed psychiatric intensive care unit between June and September 2018. All PRN antipsychotic and benzodiazepine orders, administrations, documentation practices, and attempted nonpharmacological strategies were assessed for each order and patient. Descriptive statistics were used to analyze data. RESULTS: Thirty-two patients with a total of 123 physicians' orders and 1,179 PRN administrations of antipsychotics and benzodiazepines were reviewed. Of the total administrations, 720 (61%) were combinations with at least two psychotropic agents. Forty-one (33%) physicians' orders had a prescribed indication, and 559 (47%) administrations had an attempted nonpharmacological method prior to PRN administration. Eight patients (25%) had antipsychotic PRN orders, which exceeded the total daily maximum dose. Three adverse drug effects were attributed to PRN administration. CONCLUSIONS: Areas of improvement that we identified included documentation practices of effectiveness of administered PRNs, prescriptions to include clear indications and dosage within the 24-hour maximum limits, and documentation of nonpharmacological methods utilized.

Risk of Cardiovascular Outcomes in Patients With Type 2 Diabetes After Addition of SGLT2 Inhibitors Versus Sulfonylureas to Baseline GLP-1RA Therapy.

BACKGROUND: Several glucagon-like peptide receptor agonists (GLP-1RA) and sodium-glucose cotransporter-2 inhibitors (SGLT2i) have demonstrated cardiovascular benefit in type 2 diabetes in large randomized controlled trials in patients with established cardiovascular disease or multiple risk factors. However, few trial participants were on both agents, and it remains unknown whether the addition of SGLT2i to GLP-1RA therapy has further cardiovascular benefits. METHODS: Patients adding either SGLT2i or sulfonylureas to baseline GLP-1RA were identified within 3 US claims datasets (2013-2018) and were 1:1 propensity score-matched, adjusting for >95 baseline covariates. The primary outcomes were a composite cardiovascular end point (comprising myocardial infarction, stroke, and all-cause mortality) and heart failure hospitalization. Adjusted hazard ratios (HRs) and 95% CIs were estimated in each dataset and pooled through fixed-effects meta-analysis. RESULTS: Among 12 584 propensity score-matched pairs (mean [SD] age, 58.3 [10.9] years; 48.2% male) across the 3 datasets, there were 107 composite cardiovascular end point events (incidence rate per 1000 person-years, 9.9 [95% CI, 8.1-11.9]) among SGLT2i initiators compared with 129 events (incidence rate, 13.0 [95% CI, 10.9-15.3]) among sulfonylurea initiators, corresponding to an adjusted pooled HR of 0.76 (95% CI, 0.59-0.98); this decrease in composite cardiovascular end point was driven by numeric decreases in the risk of myocardial infarction (HR, 0.71 [95% CI, 0.51-1.003]) and all-cause mortality (HR, 0.68 [95% CI, 0.40-1.14]) but not stroke (HR, 1.05 [95% CI, 0.62-1.79]). For the outcome of heart failure hospitalization, there were 141 events (incidence rate, 13.0 [95% CI, 11.0-15.2]) among SGLT2i initiators versus 206 events (incidence rate, 20.8 [95% CI, 18.1-23.8]) among sulfonylurea initiators, corresponding to an adjusted pooled HR of 0.65 (95% CI, 0.50-0.82). CONCLUSIONS: Risk of residual confounding cannot be fully excluded. Individual therapeutic agents within each class may have different magnitudes of effect. In this large real-world cohort of patients with diabetes already on GLP-1RA, addition of SGLT2i conferred greater cardiovascular benefit compared with addition of sulfonylurea. The magnitude of the cardiovascular risk reduction was comparable with the benefit seen in cardiovascular outcome trials of SGLT2i versus placebo, where baseline GLP-1RA use was minimal.

Deep Learning Reconstruction Enables Highly Accelerated Biparametric MR Imaging of the Prostate.

BACKGROUND: Early diagnosis and treatment of prostate cancer (PCa) can be curative; however, prostate-specific antigen is a suboptimal screening test for clinically significant PCa. While prostate magnetic resonance imaging (MRI) has demonstrated value for the diagnosis of PCa, the acquisition time is too long for a first-line screening modality. PURPOSE: To accelerate prostate MRI exams, utilizing a variational network (VN) for image reconstruction. STUDY TYPE: Retrospective. SUBJECTS: One hundred and thirteen subjects (train/val/test: 70/13/30) undergoing prostate MRI. FIELD STRENGTH/SEQUENCE: 3.0 T; a T2 turbo spin echo (TSE) T2-weighted image (T2WI) sequence in axial and coronal planes, and axial echo-planar diffusion-weighted imaging (DWI). ASSESSMENT: Four abdominal radiologists evaluated the image quality of VN reconstructions of retrospectively under-sampled biparametric MRIs (bp-MRI), and standard bp-MRI reconstructions for 20 test subjects (studies). The studies included axial and coronal T2WI, DWI B50 seconds/mm2 and B1000 seconds/mm (4-fold T2WI, 3-fold DWI), all of which were evaluated separately for image quality on a Likert scale (1: non-diagnostic to 5: excellent quality). In another 10 test subjects, three readers graded lesions on bp-MRI-which additionally included calculated B1500 seconds/mm2 , and apparent diffusion coefficient map-according to the Prostate Imaging Reporting and Data System (PI-RADS v2.1), for both VN and standard reconstructions. Accuracy of PI-RADS ≥3 for clinically significant cancer was computed. Projected scan time of the retrospectively under-sampled biparametric exam was also computed. STATISTICAL TESTS: One-sided Wilcoxon signed-rank test was used for comparison of image quality. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for lesion detection and grading. Generalized estimating equation with cluster effect was used to compare differences between standard and VN bp-MRI. A P-value of <0.05 was considered statistically significant. RESULTS: Three of four readers rated no significant difference for overall quality between the standard and VN axial T2WI (Reader 1: 4.00 ± 0.56 (Standard), 3.90 ± 0.64 (VN) P = 0.33; Reader 2: 4.35 ± 0.74 (Standard), 3.80 ± 0.89 (VN) P = 0.003; Reader 3: 4.60 ± 0.50 (Standard), 4.55 ± 0.60 (VN) P = 0.39; Reader 4: 3.65 ± 0.99 (Standard), 3.60 ± 1.00 (VN) P = 0.38). All four readers rated no significant difference for overall quality between standard and VN DWI B1000 seconds/mm2 (Reader 1: 2.25 ± 0.62 (Standard), 2.45 ± 0.75 (VN) P = 0.96; Reader 2: 3.60 ± 0.92 (Standard), 3.55 ± 0.82 (VN) P = 0.40; Reader 3: 3.85 ± 0.72 (Standard), 3.55 ± 0.89 (VN) P = 0.07; Reader 4: 4.70 ± 0.76 (Standard); 4.60 ± 0.73 (VN) P = 0.17) and three of four readers rated no significant difference for overall quality between standard and VN DWI B50 seconds/mm2 (Reader 1: 3.20 ± 0.70 (Standard), 3.40 ± 0.75 (VN) P = 0.98; Reader 2: 2.85 ± 0.81 (Standard), 3.00 ± 0.79 (VN) P = 0.93; Reader 3: 4.45 ± 0.72 (Standard), 4.05 ± 0.69 (VN) P = 0.02; Reader 4: 4.50 ± 0.69 (Standard), 4.45 ± 0.76 (VN) P = 0.50). In the lesion evaluation study, there was no significant difference in the number of PI-RADS ≥3 lesions identified on standard vs. VN bp-MRI (P = 0.92, 0.59, 0.87) with similar sensitivity and specificity for clinically significant cancer. The average scan time of the standard clinical biparametric exam was 11.8 minutes, and this was projected to be 3.2 minutes for the accelerated exam. DATA CONCLUSION: Diagnostic accelerated biparametric prostate MRI exams can be performed using deep learning methods in <4 minutes, potentially enabling rapid screening prostate MRI. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 5.

Axumin (18F-Fluciclovine) PET imaging in men exhibiting no clinically significant cancer on initial negative biopsy of PI-RADS 4 and 5 regions of interest.

PURPOSE: The objective of the study was to determine whether Axumin (18F-Fluciclovine) PET/MRI informs the decision to perform an early repeat biopsy of PI-RADS 4/5 region of interest (ROI) exhibiting no clinically significant prostate cancer (csPCa) on initial biopsy. METHODS: This prospective study enrolled men with at least one PI-RADS 4/5 ROI on multi-parametric MRI and no csPCa on prior biopsy defined as Gleason grade group (GGG) > 1. All men underwent an Axumin PET/MRI and only-persistent PI-RADS > 2 ROI were advised to undergo a repeat biopsy. A PET cancer suspicion score (PETCSS) was internally developed to stratify PET avid lesions according to their suspicion of harboring csPCa. The sensitivity, specificity, positive (PPV) and negative predictive value (NPV) of the PETCSS for predicting csPCa were assessed. Relative risk was calculated to analyze the association of baseline variables with csPCa on repeat biopsy. RESULTS: Thirty-eight ROI on 36 enrolled men were analyzed. Fourteen (36.8%) were downgraded to PI-RADS 1/2 and were not subjected to repeat biopsy. Thirteen (92.9%) of these downgraded scans also exhibited low-risk PETCSS. Overall, 18/22 (81.2%) subjects underwent a repeat per protocol biopsy. Of the 20 ROI subjected to repeat biopsy, eight (40%) were found to harbour csPCa. The sensitivity, specificity, PPV and NPV of the PETCSS were 50, 50, 40, and 60%, respectively. No predictor of csPCa was found in the risk analysis. CONCLUSION: Our pilot study showed that both MRI and PET sequences have limited performance for identifying those persistently suspicious PI-RADS 4/5 ROI that are found to harbor csPCa on repeat biopsy.

Comparison of Prostate Imaging and Reporting Data System V2.0 and V2.1 for Evaluation of Transition Zone Lesions: A 5-Reader 202-Patient Analysis.

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.

MRI predicts prostatic urethral involvement in men undergoing radical prostatectomy: implications for cryo-ablation of localized prostate cancer.

PURPOSE: To determine whether multi-parametric magnetic resonance imaging (mpMRI) can reliably predict proximity of prostate cancer to the prostatic urethra in a contemporary series of men undergoing radical prostatectomy (RP) at two academic centers. METHODS: Clinical characteristics of consecutive men undergoing pre-operative mpMRI prior to RP and whole-mount axial serial step-sectioned pathology examination at two academic centers between Jun 2016 and Oct 2018 were analyzed retrospectively. Every tumor was characterized by its pathologic minimum distance to the prostatic urethral lumen (pMDUL). Only the cancer closest to the urethra represented the prostatic urethral index lesion. The radiologic minimum distance of the index lesion to the prostatic urethral lumen was measured and noted as ≤ 5 mm versus > 5 mm. The sensitivity, specificity, positive and negative predicting values (PPV and NPV) and area under the receivers operating characteristics curve (AUC) were calculated for performance of mpMRI for predicting pMDUL ≤ 5 mm. RESULTS: Of the 163 surgical specimens examined, 112 (69%) exhibited a pMDUL ≤ 5 mm. These men had significantly higher grade group (GG) and advanced pathological and clinical stage. The rates of high PI-RADS score and presence of gross extracapsular extension were also significantly greater for the group with pMDUL ≤ 5 mm. The AUC, sensitivity, specificity, PPV, and NPV were 0.641, 51.8, 76.5, 82.9, and 42.4%, respectively, for mpMRI to predict pMDUL < 5 mm. CONCLUSIONS: Nearly 70% of men undergoing RP present with tumor within 5 mm of the prostatic urethra. These tumors present higher risk characteristics, and mpMRI exhibited moderate performance and high PPV in their pre-operative detection. Physicians performing partial gland ablation should take these results into consideration during treatment selection and planning.

Accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction: qualitative and quantitative comparison of image quality with conventional T2-weighted FS sequence.

OBJECTIVE: To compare the image quality of an accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction (DL HASTE-FS) with conventional T2-weighted FS sequence (conventional T2 FS) at 1.5 T. METHODS: One hundred consecutive patients who underwent clinical MRI of the liver at 1.5 T including the conventional T2-weighted fat-suppressed sequence (T2 FS) and accelerated single-shot T2-weighted MRI of the liver with deep learning-based image reconstruction (DL HASTE-FS) were included. Images were reviewed independently by three blinded observers who used a 5-point confidence scale for multiple measures regarding the artifacts and image quality. Descriptive statistics and McNemar's test were used to compare image quality scores and percentage of lesions detected by each sequence, respectively. Intra-class correlation coefficient (ICC) was used to assess consistency in reader scores. RESULTS: Acquisition time for DL HASTE-FS was 51.23 +/ 10.1 s, significantly (p < 0.001) shorter than conventional T2-FS (178.9 ± 85.3 s). DL HASTE-FS received significantly higher scores than conventional T2-FS for strength and homogeneity of fat suppression; sharpness of liver margin; sharpness of intra-hepatic vessel margin; in-plane and through-plane respiratory motion; other ghosting artefacts; liver-fat contrast; and overall image quality (all, p < 0.0001). DL HASTE-FS also received higher scores for lesion conspicuity and sharpness of lesion margin (all, p < .001), without significant difference for liver lesion contrast (p > 0.05). CONCLUSIONS: Accelerated single-shot T2-weighted MRI of the liver with deep learning-based image reconstruction showed superior image quality compared to the conventional T2-weighted fat-suppressed sequence despite a 4-fold reduction in acquisition time. KEY POINTS: • Conventional fat-suppressed T2-weighted sequence (conventional T2 FS) can take unacceptably long to acquire and is the most commonly repeated sequence in liver MRI due to motion. • DL HASTE-FS demonstrated superior image quality, improved respiratory motion and other ghosting artefacts, and increased lesion conspicuity with comparable liver-to-lesion contrast compared to conventional T2FS sequence. • DL HASTE- FS has the potential to replace conventional T2 FS sequence in routine clinical MRI of the liver, reducing the scan time, and improving the image quality.

Assessment of Renal Cell Carcinoma by Texture Analysis in Clinical Practice: A Six-Site, Six-Platform Analysis of Reliability.

BACKGROUND. Multiple commercial and open-source software applications are available for texture analysis. Nonstandard techniques can cause undesirable variability that impedes result reproducibility and limits clinical utility. OBJECTIVE. The purpose of this study is to measure agreement of texture metrics extracted by six software packages. METHODS. This retrospective study included 40 renal cell carcinomas with contrast-enhanced CT from The Cancer Genome Atlas and Imaging Archive. Images were analyzed by seven readers at six sites. Each reader used one of six software packages to extract commonly studied texture features. Inter- and intrareader agreement for segmentation was assessed with intraclass correlation coefficients (ICCs). First-order (available in six packages) and second-order (available in three packages) texture features were compared between software pairs using Pearson correlation. RESULTS. Inter- and intrareader agreement was excellent (ICC, 0.93-1). First-order feature correlations were strong (r ≥ 0.8, p < .001) between 75% (21/28) of software pairs for mean intensity and SD, 48% (10/21) for entropy, 29% (8/28) for skewness, and 25% (7/28) for kurtosis. Of 15 second-order features, only cooccurrence matrix correlation, gray-level nonuniformity, and run-length nonuniformity showed strong correlation between software packages (r = 0.90-1, p < .001). CONCLUSION. Variability in first- and second-order texture features was common across software configurations and produced inconsistent results. Standardized algorithms and reporting methods are needed before texture data can be reliably used for clinical applications. CLINICAL IMPACT. It is important to be aware of variability related to texture software processing and configuration when reporting and comparing outputs.

Validation of claims-based algorithms to identify patients with psoriasis.

PURPOSE: Accurately identifying patients with psoriasis (PsO) is crucial for generating real-world evidence on PsO disease course and treatment utilization. METHODS: We developed nine claims-based algorithms for PsO using a combination of the International Classification of Diseases (ICD)-9 codes, specialist visit, and medication dispensing using Medicare linked to electronic health records data (2013-2014) in two healthcare provider networks in Boston, Massachusetts. We calculated positive predictive value (PPV) and 95% confidence interval (CI) for each algorithm using the treating physician's diagnosis of PsO via chart review as the gold standard. Among the confirmed PsO cases, we assessed their PsO disease activity. RESULTS: The nine claims-based algorithms identified 990 unique patient records. Of those, 918 (92.7%) with adequate information were reviewed. The PPV of the algorithms ranged from 65.1 to 82.9%. An algorithm defined as ≥1 ICD-9 diagnosis code for PsO and ≥1 prescription claim for topical vitamin D agents showed the highest PPV (82.9%). The PPV of the algorithm requiring ≥2 ICD-9 diagnosis codes and ≥1 prescription claim for PsO treatment excluding topical steroids was 81.1% but higher (82.5%) when ≥1 diagnosis was from a dermatologist. Among 411 PsO patients with adequate information on PsO disease activity in EHRs, 1.5-5.8% had no disease activity, 31.3-36.8% mild, and 26.9-35.1% moderate-to-severe across the algorithms. CONCLUSIONS: Claims-based algorithms based on a combination of PsO diagnosis codes and dispensing for PsO-specific treatments had a moderate-to-high PPV. These algorithms can serve as a useful tool to identify patients with PsO in future real-world data pharmacoepidemiologic studies.

GRASP-Pro: imProving GRASP DCE-MRI through self-calibrating subspace-modeling and contrast phase automation.

PURPOSE: To propose a highly accelerated, high-resolution dynamic contrast-enhanced MRI (DCE-MRI) technique called GRASP-Pro (golden-angle radial sparse parallel imaging with imProved performance) through a joint sparsity and self-calibrating subspace constraint with automated selection of contrast phases. METHODS: GRASP-Pro reconstruction enforces a combination of an explicit low-rank subspace-constraint and a temporal sparsity constraint. The temporal basis used to construct the subspace is learned from an intermediate reconstruction step using the low-resolution portion of radial k-space, which eliminates the need for generating the basis using auxiliary data or a physical signal model. A convolutional neural network was trained to generate the contrast enhancement curve in the artery, from which clinically relevant contrast phases are automatically selected for evaluation. The performance of GRASP-Pro was demonstrated for high spatiotemporal resolution DCE-MRI of the prostate and was compared against standard GRASP in terms of overall image quality, image sharpness, and residual streaks and/or noise level. RESULTS: Compared to GRASP, GRASP-Pro reconstructed dynamic images with enhanced sharpness, less residual streaks and/or noise, and finer delineation of the prostate without prolonging reconstruction time. The image quality improvement reached statistical significance (P < 0.05) in all the assessment categories. The neural network successfully generated contrast enhancement curves in the artery, and corresponding peak enhancement indexes correlated well with that from the manual selection. CONCLUSION: GRASP-Pro is a promising method for rapid and continuous DCE-MRI. It enables superior reconstruction performance over standard GRASP and allows reliable generation of artery enhancement curve to guide the selection of desired contrast phases for improving the efficiency of GRASP MRI workflow.

Interreader Concordance of the TI-RADS: Impact of Radiologist Experience.

OBJECTIVE. The objective of this article is to assess radiologist concordance in characterizing thyroid nodules using the American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS), focusing on the effect of radiologist experience on reader concordance. MATERIALS AND METHODS. Three experienced and three less experienced radiologists assessed 150 thyroid nodules using the TI-RADS lexicon. Percent concordance was determined for various endpoints. RESULTS. Interreader concordance for the five TI-RADS categories was 87.2% for shape, 81.2% for composition, 76.1% for echogenicity, 72.9% for margins, and 69.8% for echogenic foci. Concordance for individual features was 96.3% for rim calcifications, 90.8% for macrocalcifications, 90.1% for spongiform, 83.5% for comet tail artifact, and 77.7% for punctate echogenic foci. Concordance for the TI-RADS level and recommendation for fine-needle aspiration (FNA) were 50.4% and 78.9%, respectively. Concordance was significantly (p < 0.05) higher for less experienced readers in identifying margins (84.3% vs 67.4%), echogenic foci (76.9% vs 69.3%), comet tail artifact (89.6% vs 79.2%), and punctate echogenic foci (85.3% vs 75.5%), and lower for peripheral rim calcifications (95.0% vs 97.8 %), but was not different (p > 0.05) for the remaining categories and features. CONCLUSION. A range of TI-RADS categories, features, and recommendations for FNA had generally moderate interreader agreement among six radiologists. Our results show that concordance for numerous characteristics was significantly higher for the less experienced versus the more experienced readers. These results suggest that less experienced readers relied more on the explicit TI-RADS criteria, whereas the experienced radiologists partially relied on their accumulated experience when forming impressions. However, the overall TI-RADS level and recommendation for FNA were unaffected, supporting the robustness of the TI-RADS lexicon and its continued use in practice.

Validation of claims-based algorithms for psoriatic arthritis.

PURPOSE: An increasing number of new medications are being developed and approved for psoriatic arthritis (PsA). To generate real-world evidence on comparative safety and effectiveness of these drugs, a claims-based algorithm that can accurately identify PsA is greatly needed. METHODS: To identify patients with PsA, we developed seven claims-based algorithms based on a combination of diagnosis codes and medication dispensing using the claims data from Medicare parts A/B/D linked to electronic medical records (2012-2014). Two physicians independently conducted a chart review using the treating physician's diagnosis of PsA as the gold standard. We calculated the positive predictive value (PPV) and 95% confidence intervals of each algorithm. RESULTS: Of the total 2157 records identified by the seven algorithms, 45% of the records had relevant clinical data to determine the presence of PsA. The PPV of the algorithms ranged from 75.2% (algorithm 1: ≥2 diagnosis codes for PsA and ≥1 diagnosis code for psoriasis) to 88.6% (algorithm 7: ≥2 diagnosis codes for PsA with ≥1 code by rheumatologist and ≥1 dispensing for PsA medication). Having ≥2 diagnosis codes and ≥1 dispensing for PsA medications (algorithm 6) also had PPV of 82.4%. CONCLUSIONS: All seven claims-based algorithms demonstrated a moderately high PPV of 75% to 89% in identifying PsA. The use of ≥2 diagnosis codes plus ≥1 prescription claim for PsA appears to be a valid and efficient tool in identifying PsA patients in the claims data, while broader algorithms based on diagnoses without a prescription claim also have reasonably good PPVs.

Sodium-Glucose Cotransporter-2 Inhibitors and the Risk for Severe Urinary Tract Infections: A Population-Based Cohort Study.

Background: Prior studies evaluating risk for severe urinary tract infections (UTIs) with sodium-glucose cotransporter-2 (SGLT-2) inhibitors have reported conflicting findings. Objective: To assess whether patients initiating use of SGLT-2 inhibitors were at increased risk for severe UTI events compared with those initiating use of dipeptidyl peptidase-4 (DPP-4) inhibitors or glucagon-like peptide-1 receptor (GLP-1) agonists. Design: Population-based cohort study. Setting: 2 large, U.S.-based databases of commercial claims (March 2013 to September 2015). Participants: Within each database, 2 cohorts were created and matched 1:1 on propensity score. Patients were aged 18 years or older, had type 2 diabetes mellitus, and were initiating use of SGLT-2 inhibitors versus DPP-4 inhibitors (cohort 1) or GLP-1 agonists (cohort 2). Measurements: The primary outcome was a severe UTI event, defined as a hospitalization for primary UTI, sepsis with UTI, or pyelonephritis; the secondary outcome was outpatient UTI treated with antibiotics. Hazard ratios (HRs) were estimated in each propensity score-matched cohort, with adjustment for more than 90 baseline characteristics. Results: After 1:1 matching on propensity score, 123 752 patients were identified in cohort 1 and 111 978 in cohort 2 in the 2 databases. In cohort 1, persons newly receiving SGLT-2 inhibitors had 61 severe UTI events (incidence rate [IR] per 1000 person-years, 1.76), compared with 57 events in the DPP-4 inhibitor group (IR, 1.77) (HR, 0.98 [95% CI, 0.68 to 1.41]). In cohort 2, those receiving SGLT-2 inhibitors had 73 events (IR, 2.15), compared with 87 events in the GLP-1 agonist group (IR, 2.96) (HR, 0.72 [CI, 0.53 to 0.99]). Findings were robust across sensitivity analyses; within several subgroups of age, sex, and frailty; and for canagliflozin and dapagliflozin individually. In addition, SGLT-2 inhibitors were not associated with increased risk for outpatient UTIs (cohort 1: HR, 0.96 [CI, 0.89 to 1.04]; cohort 2: HR, 0.91 [CI, 0.84 to 0.99]). Limitation: Generalizability of the study findings may be limited to patients with commercial insurance. Conclusion: In a large cohort of patients seen in routine clinical practice, risk for severe and nonsevere UTI events among those initiating SGLT-2 inhibitor therapy was similar to that among patients initiating treatment with other second-line antidiabetic medications. Primary Funding Source: Brigham and Women's Hospital, Division of Pharmacoepidemiology and Pharmacoeconomics.

Exploratory study of geometric distortion correction of prostate diffusion-weighted imaging using B0 map acquisition.

BACKGROUND: Evaluation of prostate MRI relies on diffusion-weighted imaging (DWI), commonly distorted by susceptibility artifacts, thereby creating a need for approaches to correct such distortion. PURPOSE: To compare geometric distortion on prostate MRI between standard DWI and a geometric distortion correction method for DWI described as static distortion correction DWI (SDC DWI). STUDY TYPE: Retrospective case study. POPULATION: Thirty patients (ages 31-81 years) undergoing prostate MRI. SEQUENCE: Geometric distortions from echo planar imaging were corrected with the SDC DWI protocol, which first acquires a B0 -field map to estimate geometric distortions. ASSESSMENT: Contours of the prostate were placed on axial T2 -weighted imaging (T2 WI) as an anatomic standard. Pixel shifts and apparent diffusion coefficient (ADC) values were compared between prostate contours applied to the SDC DWI and standard DWI sequences. Detailed characterization of the impact of SDC DWI was performed in three representative patients. STATISTICAL TESTS: One-way analysis of variance (ANOVA) test, Spearman correlation test, and Bland-Altman plots were calculated. RESULTS: There was significantly greater overlap of the SDC DWI prostate region of interest (ROI) with T2 WI than standard DWI with T2 WI (10.56 cm2 ± 3.14, P < 0.05). R2 of ADC values from standard DWI vs. SDC DWI in the 30 patients ranged from 0.02-0.94 (mean 0.60). A patient without susceptibility artifact demonstrated minimal pixel shift ranging from 0.6-1.3 mm and high correlation of ADC values (R2 = 0.89) between SDC DWI and standard DWI. A patient with rectal gas showed greater pixel shift (range: -2.5 to -0.5 mm) and less ADC value correlation (R2 = 0.69). A patient with a pelvic phlebolith adjacent to the prostate showed an even greater pixel shift (range: 10-16 mm) and decreased ADC correlation (R2 = 0.21). DATA CONCLUSION: SDC DWI appears to correct for susceptibility-related pixel shifts in the prostate compared with standard DWI, which may have value for assessing prostate lesions obscured by geometric warping. Level of Evidence 4 Technical Efficacy Stage 1 J. Magn. Reson. Imaging 2019;50:1614-1619.

MRI screening for uterine leiomyosarcoma.

BACKGROUND: Uterine fibroids are a common benign tumor and can be symptomatic, necessitating resection. Surgical myomectomy is an effective treatment option with a risk of disseminating occult uterine leiomyosarcoma (LMS), creating a need for an effective presurgical screening protocol. Clinical collaboration with contrast-enhanced MRI including T2 and diffusion-weighted imaging (DWI) can be utilized as a screening exam. PURPOSE: To review the accuracy and feasibility of an interdisciplinary prospective contrast-enhanced MRI pelvis with DWI screening system for LMS prior to fibroid resection. STUDY TYPE: Retrospective cohort study. POPULATION: In all, 1960 adult female patients aged 18-87 undergoing screening MRI pelvis prior to uterine fibroid resection. FIELD STRENGTH/SEQUENCE: T1 and T2 -weighted imaging, DWI, and contrast-enhanced images were acquired at 1.5 T and 3.0 T. ASSESSMENT: Each radiologist at the time of clinical study prospectively designated a confidence level of presence of LMS in the impression, which was reviewed retrospectively. A separate retrospective evaluation of the histologically proven LMS and the false positives was performed for the presence of five MRI features of LMS including low ADC values, intermediate/high T2 signal intensity, irregular margins, hemorrhage, and necrosis. A preliminary cost-effectiveness analysis was performed, comparing the costs of treatment of uterine fibroids with vs. without a collaborative screening protocol using MRI. STATISTICAL TESTS: Sensitivity, specificity, positive predictive value, and negative predictive value were obtained from the prospective evaluations. Student's t-tests were used to compare demographics and apparent diffusion coefficient values between LMS and false-positive results. RESULTS: We prospectively identified LMS patients with 100% sensitivity and 97% specificity. Preliminary cost analysis demonstrated that the MR screening protocol increased life expectancy by 0.04 years at a cost of $12,937 per life-year gained. DATA CONCLUSION: MRI is an effective and potentially economic screening test, especially with standardized reporting and coordination with clinicians. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019.