MRI Markers of Degenerative Disc Disease in Young Patients With Multiple Sclerosis.

Background and Purpose: Evidence has emerged for an association between degenerative disc disease (DDD) and multiple sclerosis (MS). The purpose of the current study is to determine the presence and extent of cervical DDD in young patients (age <35) with MS, an age cohort that is less well studied for these changes. Methods: Retrospective chart review of consecutive patients aged <35 referred from the local MS clinic who were MRI scanned between May 2005 and November 2014. 80 patients (51 female and 29 male) with MS of any type ranging between 16 and 32 years of age (average 26) were included. Images were reviewed by 3 raters and assessed for presence and extent of DDD, as well as cord signal abnormalities. Interrater agreement was assessed using Kendall's W and Fleiss' Kappa statistics. Results: Substantial to very good interrater agreement was observed using our novel DDD grading scale. At least some degree of DDD was found in over 91% of patients. The majority scored mild (grade 1, 30-49%) to moderate (grade 2, 39-51%) degenerative changes. Cord signal abnormality was seen in 56-63%. Cord signal abnormality, when present, occurred exclusively at degenerative disc levels in only 10-15%, significantly lower than other distributions (P < .001 for all pairwise comparisons). Conclusions: MS patients demonstrate unexpected cervical DDD even at a young age. Future study is warranted to investigate the underlying etiology, such as altered biomechanics. Furthermore, cord lesions were found to occur independently of DDD.

MRI texture analysis of acetabular cancellous bone can discriminate between normal, cam positive, and cam-FAI hips.

OBJECTIVES: To compare the MRI texture profile of acetabular subchondral bone in normal, asymptomatic cam positive, and symptomatic cam-FAI hips and determine the accuracy of a machine learning model for discriminating between the three hip classes. METHODS: A case-control, retrospective study was performed including 68 subjects (19 normal, 26 asymptomatic cam, 23 symptomatic cam-FAI). Acetabular subchondral bone of unilateral hip was contoured on 1.5 T MR images. Nine first-order 3D histogram and 16 s-order texture features were evaluated using specialized texture analysis software. Between-group differences were assessed using Kruskal-Wallis and Mann-Whitney U tests, and differences in proportions compared using chi-square and Fisher's exact tests. Gradient-boosted ensemble methods of decision trees were created and trained to discriminate between the three groups of hips, with percent accuracy calculated. RESULTS: Sixty-eight subjects (median age 32 (28-40), 60 male) were evaluated. Significant differences among all three groups were identified with first-order (4 features, all p ≤ 0.002) and second-order (11 features, all p ≤ 0.002) texture analyses. First-order texture analysis could differentiate between control and cam positive hip groups (4 features, all p ≤ 0.002). Second-order texture analysis could additionally differentiate between asymptomatic cam and symptomatic cam-FAI groups (10 features, all p ≤ 0.02). Machine learning models demonstrated high classification accuracy of 79% (SD 16) for discriminating among all three groups. CONCLUSION: Normal, asymptomatic cam positive, and cam-FAI hips can be discriminated based on their MRI texture profile of subchondral bone using descriptive statistics and machine learning algorithms. CLINICAL RELEVANCE STATEMENT: Texture analysis can be performed on routine MR images of the hip and used to identify early changes in bone architecture, differentiating morphologically abnormal from normal hips, prior to onset of symptoms. KEY POINTS: • MRI texture analysis is a technique for extracting quantitative data from routine MRI images. • MRI texture analysis demonstrates that there are different bone profiles between normal hips and those with femoroacetabular impingement. • Machine learning models can be used in conjunction with MRI texture analysis to accurately differentiate between normal hips and those with femoroacetabular impingement.

Diagnostic Accuracy of Centrally Restricted Diffusion Sign in Cerebral Metastatic Disease: Differentiating Radiation Necrosis from Tumor Recurrence.

Purpose: The centrally restricted diffusion sign of diffusion-weighted imaging (DWI) is associated with radiation necrosis (RN) in treated gliomas. Our goal was to evaluate its diagnostic accuracy to distinguish RN from tumor recurrence (TR) in treated brain metastases. Methods: Retrospective study of consecutive patients with brain metastases who developed a newly centrally necrotic lesion after radiotherapy (RT). One reader placed regions of interest (ROI) in the enhancing solid lesion and the non-enhancing central necrosis on the apparent diffusion coefficient (ADC) map. Two readers qualitatively assessed the presence of the centrally restricted diffusion sign. The final diagnosis was made by histopathology (n = 39) or imaging follow-up (n = 2). Differences between groups were assessed by Fisher's exact or Mann-Whitney U tests. Diagnostic accuracy and inter-reader agreement were evaluated using receiver operating characteristic (ROC) curve analysis and kappa scores. Results: Forty-one lesions (32 predominant RN; 9 predominant TR) were analyzed. An ADC value ≤ 1220 × 10-6 mm2/s (sensitivity 74%, specificity 89%, area under the curve [AUC] .85 [95% confidence interval {CI}, .70-.94] P < .0001) from the necrosis and an ADC necrosis/enhancement ratio ≤1.37 (sensitivity 74%, specificity 89%, AUC .82 [95% CI, .67-.93] P < .0001) provided the highest performance for RN diagnosis. The qualitative centrally restricted diffusion sign had a sensitivity of 69% (95% CI, .50-.83), specificity of 77% (95% CI, .40-.96), and a moderate (k = .49) inter-reader agreement for RN diagnosis. Conclusions: Radiation necrosis is associated with lower ADC values in the central necrosis than TR. A moderate interobserver agreement might limit the qualitative assessment of the centrally restricted diffusion sign.

Rule-based natural language processing for automation of stroke data extraction: a validation study.

PURPOSE: Data extraction from radiology free-text reports is time consuming when performed manually. Recently, more automated extraction methods using natural language processing (NLP) are proposed. A previously developed rule-based NLP algorithm showed promise in its ability to extract stroke-related data from radiology reports. We aimed to externally validate the accuracy of CHARTextract, a rule-based NLP algorithm, to extract stroke-related data from free-text radiology reports. METHODS: Free-text reports of CT angiography (CTA) and perfusion (CTP) studies of consecutive patients with acute ischemic stroke admitted to a regional stroke center for endovascular thrombectomy were analyzed from January 2015 to 2021. Stroke-related variables were manually extracted as reference standard from clinical reports, including proximal and distal anterior circulation occlusion, posterior circulation occlusion, presence of ischemia or hemorrhage, Alberta stroke program early CT score (ASPECTS), and collateral status. These variables were simultaneously extracted using a rule-based NLP algorithm. The NLP algorithm's accuracy, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) were assessed. RESULTS: The NLP algorithm's accuracy was > 90% for identifying distal anterior occlusion, posterior circulation occlusion, hemorrhage, and ASPECTS. Accuracy was 85%, 74%, and 79% for proximal anterior circulation occlusion, presence of ischemia, and collateral status respectively. The algorithm confirmed the absence of variables from radiology reports with an 87-100% accuracy. CONCLUSIONS: Rule-based NLP has a moderate to good performance for stroke-related data extraction from free-text imaging reports. The algorithm's accuracy was affected by inconsistent report styles and lexicon among reporting radiologists.

Preoperative Determination of Isocitrate Dehydrogenase Mutation in Gliomas Using Spectral Editing MRS: A Prospective Study.

BACKGROUND: The edited magnetic resonance spectroscopy (MRS) technique has not yet been formally evaluated for the in vivo detection of 2-hydroxyglutarate (2-HG) in patients with gliomas of various grades. PURPOSE: To evaluate the diagnostic accuracy of edited MRS in the preoperative identification of the isocitrate dehydrogenase (IDH) mutation status in patients with gliomas. STUDY TYPE: Prospective. POPULATION: Fifty-eight subjects (31 glioblastomas, 27 grade II and III gliomas). FIELD STRENGTH/SEQUENCE: Mescher-Garwood (MEGA)-PRESS and routine clinical brain tumor MR sequences were used at 3T. ASSESSMENT: Data were analyzed using an advanced method for accurate, robust, and efficient spectral fitting (AMARES) from jMRUI software. The amplitudes of the 2-HG, N-acetyl-aspartate (NAA), choline (Cho), and creatine/phosphocreatine (Cr) resonances were calculated with their associated Cramer-Rao lower bound (CRLB). The IDH1 R132H mutation status was assessed by immunohistochemistry for all patients. Patients with grades II and III gliomas with negative immunohistochemistry underwent DNA sequencing to further interrogate IDH mutation status. STATISTICAL TEST: The differences in 2-HG amplitudes, 2-HG/NAA, 2-HG/Cho, and 2-HG/Cr between IDH-mutant and IDH-wildtype gliomas were assessed using Mann-Whitney U-tests. Receiver operating characteristic curve analysis was performed to evaluate the diagnostic accuracy of each parameter. RESULTS: The 2-HG amplitudes, 2-HG/NAA, and 2-HG/Cho were higher for IDH-mutant gliomas than IDH-wildtype gliomas (P < 0.007). Using a CRLB threshold <30%, a 2-HG cutoff greater than 0 had a sensitivity of 80% (95% confidence interval [CI]: 52-96%) and a specificity of 81% (95% CI: 54-96%) in identifying IDH-mutant gliomas. In the subset of patients with grades II and III gliomas, the sensitivity was 80% (95% CI: 52-96%) and specificity was 100% (95% CI: 40-100%). Among 2-HG ratios, the highest AUC for the identification of IDH mutant status was achieved using the 2-HG/NAA (AUC = 0.8, 95% CI 0.67-.89). DATA CONCLUSION: Preoperative edited MRS appears to be able to help identify IDH-mutant gliomas with high specificity. Level of Evidence 1 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2021;53:416-426.

Effect of phase of enhancement on texture analysis in renal masses evaluated with non-contrast-enhanced, corticomedullary, and nephrographic phase-enhanced CT images.

OBJECTIVE: To compare texture analysis (TA) features of solid renal masses on renal protocol (non-contrast enhanced [NECT], corticomedullary [CM], nephrographic [NG]) CT. MATERIALS AND METHODS: A total of 177 consecutive solid renal masses (116 renal cell carcinoma [RCC]; 51 clear cell [cc], 40 papillary, 25 chromophobe, and 61 benign masses; 49 oncocytomas, 12 fat-poor angiomyolipomas) with three-phase CT between 2012 and 2017 were studied. Two blinded radiologists independently assessed tumor heterogeneity (5-point Likert scale) and segmented tumors. TA features (N = 25) were compared between groups and between phases. Accuracy (area under the curve [AUC]) for RCC versus benign and cc-RCC versus other masses was compared. RESULTS: Subjectively, tumor heterogeneity differed between phases (p < 0.01) and between tumors within the same phase (p = 0.03 [NECT] and p < 0.01 [CM, NG]). Inter-observer agreement was moderate to substantial (intraclass correlation coefficient = 0.55-0.73). TA differed in 92.0% (23/25) features between phases (p < 0.05) except for GLNU and f6. More TA features differed significantly on CM (80.0% [20/25]) compared with NG (40.0% [10/25]) and NECT (16.0% [4/25]) (p < 0.01). For RCC versus benign, AUCs of texture features did not differ comparing CM and NG (p > 0.05), but were higher for 20% (5/25) and 28% (7/25) of features comparing CM and NG with NECT (p < 0.05). For cc-RCC versus other, 36% (9/25) and 40% (10/25) features on CM had higher AUCs compared with NECT and NG images (p < 0.05). CONCLUSION: Texture analysis of renal masses differs, when evaluated subjectively and quantitatively, by phase of CT enhancement. The corticomedullary phase had the highest discriminatory value when comparing masses and for differentiating cc-RCC from other masses. KEY POINTS: • Subjectively evaluated renal tumor heterogeneity on CT differs by phase of enhancement. • Quantitative CT texture analysis features in renal tumors differ by phases of enhancement with the corticomedullary phase showing the highest number and most significant differences compared with non-contrast-enhanced and nephrographic phase images. • For diagnosis of clear cell RCC, corticomedullary phase texture analysis features had improved accuracy of classification in approximately 40% of features studied compared with non-contrast-enhanced and nephrographic phase images.

Left atrial vortex size and velocity distributions by 4D flow MRI in patients with paroxysmal atrial fibrillation: Associations with age and CHA2 DS2 -VASc risk score.

BACKGROUND: Characterization of left atrial (LA) hemodynamics in paroxysmal atrial fibrillation (PAF) may provide valuable insights for thromboembolic risk. PURPOSE: To evaluate LA vortex formation and velocity distributions by 4D flow MRI and identify associations with age, LA/LV (left ventricle) function, and established risk scores. STUDY TYPE: Prospective clinical. POPULATION: Patients with PAF (n = 45, 46 ± 14 years) and healthy controls (n = 15, 54 ± 9 years) were enrolled. MRI SEQUENCES: 3T standardized cardiac MRI protocol inclusive of 4D flow MRI. ASSESSMENT: Flow analysis planes were prescribed at each pulmonary vein. Velocity distribution analysis and vortex size quantification by the Lambda2 (λ2 ) method were performed in the LA. STATISTICS: Pearson or Spearman's correlation coefficients, r, were calculated to identify relationships between 4D flow-derived LA parameters and age, LA/LV function, and CHA2 DS2 -VASc stroke risk score. Univariate and multivariate determinants of stroke risk were assessed using linear regressions. To compare parameters within multiple groups, one-way analysis of variance or Kruskal-Wallis was used. RESULTS: LA vortice sizes were observed in all subjects using λ2 showing inverse correlations with peak pulmonary vein inflow velocities (P < 0.05), and positive correlations with LA volume (P < 0.05). Vortex size was elevated in PAF at all phases of the cardiac cycle, being most prominent at end early diastole (3.98 ± 1.84 cm3 vs. 6.93 ± 3.11 cm3 , P = 0.001). Velocity distribution analysis showed a greater incidence of flow stasis among patients with PAF (P < 0.05). In univariate regression, vortex size was associated with the CHA2 DS2 -VASc risk score at peak systole (0.457 ± 0.038, P ≤ 0.001). However, in multivariate regression age was the dominant determinant of stroke risk (0.348 ± 0.012, P = 0.006). DATA CONCLUSION: This study demonstrated that LA vortex size is increased among low-risk patients with PAF and is associated with the CHA2 DS2 -VASc risk score. Age remained the dominant determinant of stroke risk. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:871-884.

CT texture analysis of acetabular subchondral bone can discriminate between normal and cam-positive hips.

OBJECTIVES: The purpose of this study was to determine if the CT texture profile of acetabular subchondral bone differs between normal, asymptomatic cam-positive, and symptomatic cam-FAI hips. In addition, the utility of texture analysis to discriminate between the three hip statuses was explored using a machine learning approach. METHODS: IRB-approved, case-control study analyzing CT images in subjects with and without cam morphology from August 2010 to December 2013. Sixty-eight subjects were included: 19 normal controls, 26 asymptomatic cam, and 23 symptomatic cam-FAI. Acetabular subchondral bone was contoured on the sagittal oblique CT images using ImageJ ®. 3D histogram texture features (mean, variance, skewness, kurtosis, and percentiles) were evaluated using MaZda software. Groupwise differences were investigated using Kruskal-Wallis tests and Mann-Whitney U tests. Gradient-boosted decision trees were created and trained to discriminate between control and cam-positive hips. RESULTS: Both asymptomatic and symptomatic cam-FAI hips demonstrated significantly higher values of texture variance (p = 0.0007, p < 0.0001), 90th percentile (p = 0.007, p = 0.006), and 99th percentile (p = 0.009, p = 0.009), but significantly lower values of skewness (p = 0.0001, p = 0.0013) and kurtosis (p = 0.0001, p = 0.0001) compared to normal controls. There were no differences in texture profile between asymptomatic cam and symptomatic cam-FAI hips. Machine learning models demonstrated high classification accuracy for discriminating control hips from asymptomatic cam-positive (82%) and symptomatic cam-FAI (86%) hips. CONCLUSIONS: Texture analysis can discriminate between normal and cam-positive hips using conventional descriptive statistics, regression modeling, and machine learning algorithms. It has the potential to become an important tool in compositional analysis of hip subchondral trabecular bone in the context of FAI, and possibly serve as a biomarker of joint degeneration. KEY POINTS: • The CT texture profile of acetabular subchondral bone is significantly different between normal and cam-positive hips. • Texture analysis can detect changes in subchondral bone in asymptomatic cam-positive hips that are equal to that of symptomatic cam-FAI hips. • Texture analysis has the potential to become an important tool in compositional analysis of hip subchondral bone in the context of FAI and may serve as a biomarker in the study of joint physiology and biomechanics.

Shape Analysis of Peripheral Zone Observations on Prostate DWI: Correlation to Histopathology Outcomes After Radical Prostatectomy.

OBJECTIVE. The objective of our study was to subjectively and quantitatively assess shape features of peripheral zone (PZ) tumors at DWI compared with pathologic outcomes. MATERIALS AND METHODS. During the study period, 241 consecutive men with PZ dominant prostate tumors underwent 3-T MRI including DWI before undergoing radical prostatectomy. DW images of these patients were retrospectively assessed by two blinded radiologists. The reviewers assigned Prostate Imaging Reporting and Data System (PI-RADS) shape categories (round or oval, crescentic [i.e., conforming to PZ], linear or wedge-shaped) and segmented tumors for quantitative shape analysis. Discrepancies were resolved by consensus. Comparisons were performed with Gleason score (GS) and pathologic stage. RESULTS. Consensus review results were as follows: 63.9% (154/241) of tumors were round or oval; 22.8% (55/241), crescentic; and 13.3% (32/241), linear or wedge-shaped. Agreement for shape assessment was moderate (κ = 0.41). Round or oval tumors were higher grade (GS 6 = 1.3%, GS 7 = 78.0%, GS ≥ 8 = 20.7%) than crescentic tumors (GS 6 = 9.1%, GS 7 = 74.6%, GS ≥ 8 = 16.3%) and linear or wedge-shaped tumors (GS 6 = 6.3%, GS 7 = 78.1%, GS ≥ 8 = 15.6%) (p = 0.011). In addition, round or oval tumors had higher rates of extraprostatic extension (EPE) and seminal vesicle invasion (SVI) (EPE and SVI: 70.1% and 26.0%) than crescentic tumors (67.3% and 9.1%; p = 0.003) and linear or wedge-shaped tumors (40.6% and 9.4%; p = 0.008). Quantitatively, the shape features termed "circularity" and "roundness" were associated with EPE (p < 0.001 and p = 0.003), SVI (p < 0.001 and p = 0.029), and increasing GS (p = 0.009 and p = 0.021), but there was overlap between groups. CONCLUSION. In this study, approximately 10% of resected PZ tumors were linear or wedge-shaped on DWI. PZ tumors that were judged subjectively and evaluated quantitatively to be round or oval were associated with increased prostate cancer aggressiveness.

Transition zone prostate cancer: Logistic regression and machine-learning models of quantitative ADC, shape and texture features are highly accurate for diagnosis.

BACKGROUND: The limitation of diagnosis of transition zone (TZ) prostate cancer (PCa) using subjective assessment of multiparametric (mp) MRI with PI-RADS v2 is related to overlapping features between cancers and stromal benign prostatic hyperplasia (BPH) nodules, particularly in small lesions. PURPOSE: To evaluate modeling of quantitative apparent diffusion coefficient (ADC), texture, and shape features using logistic regression (LR) and support vector machine (SVM) models for the diagnosis of transition zone PCa. STUDY TYPE: Retrospective. POPULATION: Ninety patients; 44 consecutive TZ PCa were compared with 61 consecutive BPH nodules (26 glandular/35 stromal). FIELD STRENGTH/SEQUENCE: 3 T/T2 -weighted (T2 W) fast spin-echo, diffusion weighted imaging. ASSESSMENT: A radiologist manually segmented lesions on axial images for quantitative ADC (mean, 10th , 25th -centile-ADC), T2 W-shape (circularity, convexity) and T2 W-texture (kurtosis, skewness, entropy, run-length nonuniformity [RLNU], gray-level nonuniformity [GLNU]) analysis. A second radiologist segmented one-fifth of randomly selected lesions to determine the reproducibility of measurements. The reference standard was histopathology for all lesions. STATISTICAL TESTS: Quantitative features were selected a priori and were compared using univariate and multivariate analysis. LR and SVM models of statistically significant features were constructed and evaluated using receiver operator characteristic (ROC) analysis. Subgroup analysis of TZ PCa vs. only stromal BPH and in lesions measuring <15 mm was performed. Agreement in measurements was assessed using the Dice similarity coefficient (DSC). RESULTS: Mean, 25th and 10th -centile ADC, circularity, and texture (entropy, RLNU, GLNU) features differed between groups (P < 0.0001-0.0058); however, at multivariate analysis only circularity and ADC metrics (P < 0.001) remained significant. LR and SVM models were highly accurate for the diagnosis of TZ PCa (sensitivity/specificity/AUC): 93.2%/98.4%/0.989 and 93.2%/96.7%/0.949, respectively, with no significance difference between the LR and SVM models (P = 0.2271). Reproducibility of segmentation was excellent (DSC 0.84 tumors and 0.87 BPH). Subgroup analyses of TZ PCa vs. stromal BPH (AUC = 0.976) and in <15 mm lesions (AUC = 0.990) remained highly accurate. DATA CONCLUSION: LR and SVM models incorporating previously described quantitative ADC, shape and texture analysis features are highly accurate for the diagnosis of TZ PCa and remained accurate when comparing TZ PCa with stromal BPH and in smaller lesions. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:940-950.

Prospective comparative diagnostic accuracy evaluation of dynamic contrast-enhanced (DCE) vs. dynamic susceptibility contrast (DSC) MR perfusion in differentiating tumor recurrence from radiation necrosis in treated high-grade gliomas.

BACKGROUND: The appearance of a new enhancing lesion after surgery and chemoradiation for high-grade glioma (HGG) presents a common diagnostic dilemma. Histopathological analysis remains the reference standard in this situation. PURPOSE: To prospectively compare the diagnostic accuracy of dynamic contrast-enhanced (DCE) vs. dynamic susceptibility contrast (DSC) in differentiating tumor recurrence (TR) from radiation necrosis (RN). STUDY TYPE: Prospective diagnostic accuracy study. POPULATION: In all, 98 consecutive treated HGG patients with new enhancing lesion. We excluded 32 patients due to inadequate follow-up or technical limitation. FIELD STRENGTH/SEQUENCE: 3 T DCE and DSC MR. ASSESSMENT: Histogram and hot-spot analysis of cerebral blood volume (CBV), corrected CBV, Ktrans , area under the curve (AUC), and plasma volume (Vp). The reference standard of TR and/or RN was determined by histopathology in 43 surgically resected lesions or by clinical/imaging follow-up in the rest. STATISTICAL TESTS: Mann-Whitney U-tests, receiver operating characteristic (ROC) curve, and logistic regression analysis. RESULTS: A total of 68 lesions were included. There were 37 TR, 28 RN, and three lesions with equal proportions of TR and RN. TR had significantly higher CBV, corrected CBV, CBV ratio, corrected CBV ratio, AUC ratio, and Vp ratio (P < 0.05) than RN on hot-spot analysis. CBV had the highest diagnostic accuracy (AUROC 0.71). On histogram analysis, TR had higher CBV and corrected CBV maximal value compared with RN (P = 0.006, AUROC = 0.70). Only CBV on hot-spot analysis remained significant after correction for multiple comparison, with no significant improvement in diagnostic accuracy when using a combination of parameters (AUROC 0.71 vs. 0.76, P = 0.24). DATA CONCLUSION: DSC-derived CBV is the most accurate perfusion parameter in differentiating TR and RN. DSC and DCE-derived parameters reflecting the blood volume in an enhancing lesion are more accurate than the DCE-derived parameter Ktrans . Clinical practice may be best guided by blood volume measurements, rather than permeability assessment for differentiation of TR from RN. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2019;50:573-582.

Diagnosis of transition zone prostate cancer using T2-weighted (T2W) MRI: comparison of subjective features and quantitative shape analysis.

PURPOSE: To assess T2-weighted (T2W) MRI to differentiate transition zone (TZ) prostate cancer (PCa) from benign prostatic hyperplasia (BPH). MATERIALS AND METHODS: With IRB approval, 22 consecutive TZ PCa were retrospectively compared with 30 consecutive BPH (15 stromal, 15 glandular) nodules diagnosed using radical prostatectomy MRI maps. Two blinded radiologists (R1/R2) subjectively assessed the shape (round/oval vs. lenticular) and margin (circumscribed vs. blurred/indistinct) and for a T2W hypointense rim. Both radiologists segmented lesions extracting quantitative shape features (circularity, convexity and topology/skeletal branching). Statistical tests were performed using chi-square (subjective features), Mann-Whitney U (quantitative features), Cohen's kappa/Bland-Altman and receiver-operator characteristic analysis. RESULTS: There were differences in the subjective analysis of the shape, margin and absence of a T2W-rim comparing TZ PCa with BPH (p < 0.0001) with moderate to almost perfect agreement [kappa = 0.56 (shape), 0.72 (margin), 0.97 (T2W-rim)]. Area under the curve (AUC ± standard error) for diagnosis of TZ PCas was shape = 0.88 ± 0.05, margin = 0.89 ± 0.04, and T2W-rim = 0.91 ± 0.04. Shape, judged subjectively, was specific (100%/94% R1/R2) with low-to-moderate sensitivity (55%/88% R1/R2). Circularity and convexity differed between groups (p < 0.001) with no difference in topology/skeletal branches (p = 0.31). Agreement in measurements was substantial for significant quantitative variables and AUC ± SE, sensitivity and specificity for diagnosis of TZ PCa were: circularity = 0.98 ± 0.01, 90%/96%; convexity = 0.85 ± 0.06, 68%/97%. AUCs for circularity were higher than for subjective analysis (p = 0.01 and 0.26). CONCLUSION: Subjective analysis of T2W-MRI accurately diagnoses TZ PCa with high accuracy also demonstrated for quantitative shape analysis, which may be useful for future radiogenomic analysis of transition zone tumors. KEY POINTS: • Presence of a complete T2-weighted hypointense circumscribed rim accurately diagnoses BPH. • Round shape accurately diagnoses BPH and can be assessed quantitatively using circularity. • Lenticular shape accurately diagnoses TZ PCa and can be assessed quantitatively using convexity.

Diagnostic Accuracy of Unenhanced CT Analysis to Differentiate Low-Grade From High-Grade Chromophobe Renal Cell Carcinoma.

OBJECTIVE: The objective of our study was to evaluate tumor attenuation and texture on unenhanced CT for potential differentiation of low-grade from high-grade chromophobe renal cell carcinoma (RCC). MATERIALS AND METHODS: A retrospective study of 37 consecutive patients with chromophobe RCC (high-grade, n = 13; low-grade, n = 24) who underwent preoperative unenhanced CT between 2011 and 2016 was performed. Two radiologists (readers 1 and 2) blinded to the histologic grade of the tumor and outcome of the patients subjectively evaluated tumor homogeneity (3-point scale: completely homogeneous, mildly heterogeneous, or mostly heterogeneous). A third radiologist, also blinded to tumor grade and patient outcome, measured attenuation and contoured tumors for quantitative texture analysis. Comparisons were performed between high-grade and low-grade tumors using the chi-square test for subjective variables and sex, independent t tests for patient age and tumor attenuation, and Mann-Whitney U tests for texture analysis. Logistic regression models and ROC curves were computed. RESULTS: There were no differences in age or sex between the groups (p = 0.652 and 0.076). High-grade tumors were larger (mean ± SD, 62.6 ± 34.9 mm [range, 17.0-141.0 mm] vs 39.0 ± 17.9 mm [16.0-72.3 mm]; p = 0.009) and had higher attenuation (mean ± SD, 45.5 ± 8.2 HU [range, 29.0-55.0 HU] vs 35.3 ± 8.5 HU [14.0-51.0 HU]; p = 0.001) than low-grade tumors. CT size and attenuation achieved good accuracy to diagnose high-grade chromophobe RCC: The AUC ± standard error was 0.85 ± 0.08 (p < 0.0001) with a sensitivity of 69.0% and a specificity of 100%. Subjectively, high-grade tumors were more heterogeneous (mildly or markedly heterogeneous: 69.2% [9/13] for reader 1 and 76.9% [10/13] for reader 2; reader 1, p = 0.024; reader 2, p = 0.001) with moderate agreement (κ = 0.57). Combined texture features diagnosed high-grade tumors with a maximal AUC of 0.84 ± 0.06 (p < 0.0001). CONCLUSION: Tumor attenuation and heterogeneity assessed on unenhanced CT are associated with high-grade chromophobe RCC and correlate well with the histopathologic chromophobe tumor grading system.

Prostate Imaging Reporting and Data System, Version 2, Assessment Categories and Pathologic Outcomes in Patients With Gleason Score 3 + 4 = 7 Prostate Cancer Diagnosed at Biopsy.

OBJECTIVE: The purpose of this study is to assess associations between Prostate Imaging Reporting and Data System, version 2 (PI-RADSv2), categories and the presence of a tumor with a Gleason score (GS) of 4 + 3 = 7 or greater or the presence of extraprostatic extension (EPE) at radical prostatectomy (RP) in patients with a GS 3 + 4 = 7 tumor at biopsy. MATERIALS AND METHODS: A total of 81 men with GS 3 + 4 = 7 prostate cancer diagnosed by transrectal ultrasound-guided biopsy underwent multiparametric MRI and RP between 2012 and 2015. Two blinded radiologists assessed multiparametric MR images and assigned PI-RADSv2 assessment categories (categories 1-5) with the use of sector maps, which were compared with regard to the location of the tumor, the GS, and the presence of EPE at RP. Comparisons were performed between groups with the use of chi-square and multivariate analysis. Diagnostic accuracy was assessed using ROC curve analysis, and localization was compared using the Fisher exact test. RESULTS: A total of 53.1% of men (43/81) had EPE, and 21.0% (17/81) had GS 4 + 3 = 7 prostate cancer after RP, whereas 2.5% of men (2/81) had their tumors downgraded to GS 3 + 3 = 6. No statistically significant difference in patient age, prostate specific antigen level, or clinical stage existed between groups (p > 0.05). PI-RADSv2 assessment categories were significantly higher for GS 4 + 3 = 7 tumors (p = 0.03). PI-RADSv2 showed moderate accuracy for the diagnosis of GS 4 + 3 = 7 tumors (AUC, 0.65; 95% CI, 0.54-0.77), with a category of 4 or higher having a sensitivity and specificity for diagnosis of 94.1% and 23.4%, respectively. No patient with a PI-RADSv2 category lower than 3 had a GS 4 + 3 = 7 tumor. Accuracy of tumor localization ranged from 86.4% to 92.6%, with 88.2% of errors (15/17) occurring in GS 3 + 3 = 6 or GS 3 + 4 = 7 tumors (p = 0.30). PI-RADSv2 categories were noted to be higher when EPE was present (p < 0.001). Interobserver agreement was moderate (κ = 0.43). CONCLUSION: For GS 3 + 4 = 7 cancers detected at transrectal ultrasound-guided biopsy, higher PI-RADSv2 assessment categories are associated with upgrading to GS 4 + 3 = 7 cancer and with the presence of EPE after RP. A PI-RADSv2 score of 3 or higher was 100% sensitive for diagnosing GS 4 + 3 = 7 tumors.

Evaluation of apparent diffusion coefficient and MR volumetry as independent associative factors for extra-prostatic extension (EPE) in prostatic carcinoma.

BACKGROUND: To assess mean apparent diffusion coefficient (ADC) and MR-derived tumor volume (Vt) as associative factors for extra-prostatic extension (EPE) in prostate cancer (PCa). METHODS: With institutional review board approval, 73 consecutive patients diagnosed with PCa at trans-rectal ultrasound biopsy underwent preoperative multi-parametric (T2W+DWI+DCE) 3 Tesla MRI before radical prostatectomy between 2012 and 2014; 52% (38/73) patients had EPE. Clinical parameters including: age, prostate serum antigen (PSA), digital rectal examination (DRE) and percentage positive cores (PPC) were recorded. Two blinded radiologists subjectively evaluated for EPE using PI-RADS with T2W-MRI. A third blinded radiologist recorded: mean ADC (mm(2) /s) of tumor and tumor volume on ADC and T2W (derived from planar volumetry). VtMAX (the largest volume on ADC or T2W) was documented. Multivariate and receiver operator characteristic analyses were performed. RESULTS: There were no significant differences in age, DRE, or Gleason score between groups (P = 0.52, 0.06, 0.61, 0.36). PSA approached significance being higher with EPE (12.9 ± 12.6 versus 8.2 ± 7.4; P = 0.06). PPC was higher with EPE (60.9 ± 21.9% versus 38.3 ± 21.6%; P < 0.01) with an area under the curve (AUC) of 0.78 and sensitivity/specificity = 75.7/75% when PPC ≥ 45%. AUC for T2W-MRI was 0.46-0.51 with sensitivity/specificity = 40.0-42.9/48.6-57.1% (R1, R2). Inter-observer agreement was fair, k = 0.39. There was no difference in mean ADC between groups (0.89 ± 0.25 versus 0.88 ± 0.19 [EPE] mm(2) /s), P = 0.70. T2W-Vt, ADC-Vt, and VtMAX were larger with EPE (5.1 ± 7.4, 5.8 ± 6.5, 6.3 ± 7.4 cm(3) versus 1.6 ± 1.8, 1.8 ± 1.3, 2.1 ± 1.8), P < 0.01. VtMAX AUC was 0.77 with sensitivity/specificity = 78.4/73.5% when VtMAX ≥ 2.1 cm(3) which outperformed all other parameters (P > 0.05) except PPC (P = 0.6) for the diagnosis EPE. CONCLUSION: MR volumetry and percentage of positive core biopsies are associated with EPE; whereas, in this study, other clinical and MR parameters including mean ADC and subjective T2W-MR analysis were not useful for assessment of EPE.

Whole-Tumor Quantitative Apparent Diffusion Coefficient Histogram and Texture Analysis to Predict Gleason Score Upgrading in Intermediate-Risk 3 + 4 = 7 Prostate Cancer.

OBJECTIVE: The objective of our study was to evaluate whole-lesion quantitative apparent diffusion coefficient (ADC) for the prediction of Gleason score (GS) upgrading in 3 + 4 = 7 prostate cancer. MATERIALS AND METHODS: Fifty-four patients with GS 3 + 4 = 7 prostate cancer diagnosed at systematic transrectal ultrasound (TRUS)-guided biopsy underwent 3-T MRI and radical prostatectomy (RP) between 2012 and 2014. A blinded radiologist contoured dominant tumors on ADC maps using histopathologic correlation. The whole-lesion mean ADC, ADC ratio (normalized to peripheral zone), ADC histogram, and texture analysis were compared between tumors with GS upgrading and those without GS upgrading using multivariate ROC analyses and logistic regression modeling. RESULTS: Tumors were upgraded to GS 4 + 3 = 7 after RP in 26% (n = 14) of the 54 patients, and tumors were downgraded after RP in none of the patients. The mean ADC, ADC ratio, 10th-centile ADC, 25th-centile ADC, and 50th-centile ADC were similar between patients with GS 3 + 4 = 7 tumors (0.99 ± 0.22, 0.58 ± 0.15, 0.77 ± 0.31, 0.94 ± 0.28, and 1.15 ± 0.24, respectively) and patients with upgraded GS 4 + 3 = 7 tumors (1.02 ± 0.18, 0.55 ± 0.11, 0.71 ± 0.26, 0.89 ± 0.20, and 1.11 ± 0.16) (p > 0.05). Regression models combining texture features improved the prediction of GS upgrading. The combination of kurtosis, entropy, and skewness yielded an AUC of 0.76 (SE = 0.07) (p < 0.001), a sensitivity of 71%, and a specificity of 73%. The combination of kurtosis, heterogeneity, entropy, and skewness yielded an AUC of 0.77 (SE = 0.07) (p < 0.001), a sensitivity of 71%, and a specificity of 78%. CONCLUSION: In this study, whole-lesion mean ADC, ADC ratio, and ADC histogram analysis were not predictive of pathologic upgrading of GS 3 + 4 = 7 prostate cancer after RP. ADC texture analysis improved accuracy.

Quantitative non-contrast measurements improve diagnosing dural venous sinus thrombosis.

INTRODUCTION: The only direct sign of sinus thrombosis on non-contrast computerized tomography (NCCT) is the hyperdense sign. The purpose of our study was to assess quantitative parameters for diagnosis of superficial venous sinus thrombosis and to compare these quantitative criteria with the current standard of qualitative evaluation. METHODS: This retrospective case-control study included 18 patients with acute superficial sinus thrombosis and 18 matched controls. Three blinded readers independently evaluated the NCCT for the presence of hyperdense sign using axial slices only followed by axial slices with multiplanar reformats. Absolute attenuation values and ratios were calculated for thrombosed and non-thrombosed sinuses: Ratiotarget sinus/lowest attenuation sinus, Ratiotarget sinus/basilar artery, Ratiotarget sinus/internal carotid artery, Ratiotarget sinus/temporal lobe, and Ratiotarget sinus/frontal lobe. RESULTS: There was a significant difference in absolute attenuation values and ratios between thrombosed and non-thrombosed sinuses, with the absolute attenuation and the Ratiotarget sinus/lowest attenuation sinus being the most differentiating. The mean attenuation for thrombosed sinuses was 69 Hounsfield units (HU) (95 % CI 65-72 HU) vs. 52 HU (95 % CI 51-54) for non-thrombosed, P < 0.0001. The mean Ratiotarget/lowest attenuation was 1.5 (95 % CI 1.4-1.6) for thrombosed sinuses vs. 1.1 (95 % CI 1.0-1.1) for non-thrombosed, P < 0.0001. Optimal thresholds of 62 HU and 1.3 yielded sensitivities of 81 and 84 %, respectively. Hyperdense sign had a sensitivity of 63 % on axial images and 67 % with the addition of multiplanar reformats. CONCLUSION: Density measurements result in substantial improvement over visual inspection in the diagnosis of superficial venous sinus thrombosis on NCCT.

Can Quantitative CT Texture Analysis be Used to Differentiate Fat-poor Renal Angiomyolipoma from Renal Cell Carcinoma on Unenhanced CT Images?

PURPOSE: To determine the accuracy of texture analysis to differentiate fat-poor angiomyolipoma (fp-AML) from renal cell carcinoma (RCC) on unenhanced computed tomography (CT) images. MATERIALS AND METHODS: In this institutional review board-approved retrospective case-control study, patients with AML and RCC were identified from the pathology database: there were 16 patients with fp-AML (no visible fat at unenhanced CT) and 84 patients with RCC. Axial unenhanced CT images were contoured manually by two independent analysts. Texture analysis was performed for each lesion, and reproducibility was assessed. Texture features related to the gray-level histogram, gray-level co-occurrence, and run-length matrix statistics were evaluated. The most discriminative features were used to generate support vector machine (SVM) classifiers. Diagnostic accuracy of textural features was assessed and 10-fold cross validation was performed. Unenhanced CT images for each patient were independently reviewed by two blinded radiologists who subjectively graded lesion heterogeneity on a five-point scale. Differences in area under the receiver operating characteristic curve (AUC) between subjective heterogeneity ratings and textural features were evaluated by using the DeLong method. RESULTS: There was lower lesion homogeneity and higher lesion entropy in RCCs (P ≤ .01). A model incorporating several texture features resulted in an AUC of 0.89 ± 0.04. The average SVM accuracy of textural features ranged from 83% to 91% (after 10-fold cross validation). An optimal subjective heterogeneity rating of 2 or higher was identified as a predictor of RCC for both readers, with no significant difference in AUC between readers (P = .06). Each of the three textural-based classifiers was more accurate than either radiologists' subjective heterogeneity ratings for the models incorporating a subset of the top three textural features (difference in AUC between textural features and subjective visual heterogeneity, 0.25; 95% confidence interval: 0.02, 0.47; P = .03). CONCLUSION: CT texture analysis can be used to accurately differentiate fp-AML from RCC on unenhanced CT images.

Diagnosis of Sarcomatoid Renal Cell Carcinoma With CT: Evaluation by Qualitative Imaging Features and Texture Analysis.

OBJECTIVE: The objective of our study was to determine whether CT findings, including texture analysis, can differentiate sarcomatoid renal cell carcinoma (RCC) from clear cell RCC. MATERIALS AND METHODS: A retrospective case-control study was performed of consecutive patients with a histologic diagnosis of sarcomatoid RCC (n = 20) and clear cell RCC (n = 25) who underwent preoperative CT over a 3-year period. The CT images were independently reviewed by two blinded abdominal radiologists; they evaluated the following: tumor heterogeneity, tumor margin, calcification, intratumoral neovascularity, peritumoral neovascularity, renal sinus invasion, renal vein invasion, and adjacent organ invasion. Interobserver agreement was assessed using the Cohen kappa coefficient, and results were compared between groups using an independent Student t test and the chi-square test with a Bonferroni correction. For texture analysis, gray-level co-occurrence and run-length matrix features were extracted and compared using Mann-Whitney U tests. ROC curves for each tumor were constructed, and AUCs were calculated. RESULTS: Overall, sarcomatoid RCCs were larger than clear cell RCCs, measuring 77 ± 27 mm (mean ± SD) compared with 50 ± 29 mm (p = 0.003), respectively; however, there was no difference in tumor size between the tumors that were compared using texture analysis or subjective analysis (p = 0.06 and 0.03, respectively). From the subjective analysis, only peritumoral neovascularity (readers 1 and 2: 70% and 70% sarcomatoid RCCs vs 0% and 41.6% clear cell RCCs, respectively; p = 0.001) and the size of the peritumoral vessels (p < 0.001) differed between sarcomatoid RCCs and clear cell RCCs, and interobserver agreement was fair (κ = 0.38). Other subjective imaging features did not differ between the tumors (p > 0.005). There was greater run-length nonuniformity and greater gray-level nonuniformity in sarcomatoid RCCs than in clear cell RCCs (p = 0.03 and p = 0.04, respectively). The combined textural features identified sarcomatoid RCC with an AUC of 0.81 ± 0.08 (standard error) (p < 0.0001). CONCLUSION: Large tumor size, the presence of peritumoral neovascularity, and larger peritumoral vessels are features that are more commonly associated with sarcomatoid RCCs than with clear cell RCCs. Sarcomatoid RCCs are also more heterogeneous by texture analysis than clear cell RCCs.

Externalization of tunneled hemodialysis catheter in patients with tunnel or exit-site infections and limited access options.

PURPOSE: To evaluate the viability and effectiveness of temporary externalization of a tunneled hemodialysis (HD) catheter in catheter-dependent HD patients presenting with catheter-related tunnel or exit-site infection, documented central venous stenosis, and limited alternative venous access. MATERIALS AND METHODS: All catheter-dependent HD patients with known central venous stenosis presenting with exit-site or tunnel infection and who subsequently underwent catheter externalization between February 2008 and May 2012 were reviewed. After catheter externalization, patients were concurrently treated with antibiotics for approximately 3 weeks before reinsertion of a new tunneled catheter. Treatment outcomes were collected, with treatment failures defined as reinfection with the same organism within 45 days of tunneled catheter reinsertion. RESULTS: There were 42 catheter externalization procedures performed in 26 patients for 42 exit-site or tunnel infections. Technical success rate for catheter externalization was 100%, with no complications during the externalization procedure and preservation of all original access sites. Treatment failure occurred in 9.8% (4 of 41) of cases. Median infection-free survival after treatment and retunneling of a new dialysis catheter was 80 days. One major periprocedural complication of death occurred before reinsertion of a new tunneled catheter. Minor complications after the procedure occurred in four patients and included three cases of a small persistent wound at the temporary supraclavicular access site and one initially nonfunctioning externalized catheter. CONCLUSIONS: Temporary dialysis catheter externalization appears both technically feasible and effective for the treatment of exit-site and tunnel infections, while allowing preservation of the venous access site in catheter-dependent HD patients with central venous stenosis and limited alternative venous access.