Towards the automatic computational assessment of enlarged perivascular spaces on brain magnetic resonance images: A systematic review

Enlarged perivascular spaces (EPVS), visible in brain MRI, are an important marker of small vessel disease and neuroinflammation. We systematically evaluated the literature up to June 2012 on possible methods for their computational assessment and analyzed confounds with lacunes and small white matter hyperintensities. We found six studies that assessed/identified EPVS computationally by seven different methods, and four studies that described techniques to automatically segment similar structures and are potentially suitable for EPVS segmentation. T2‐weighted MRI was the only sequence that identified all EPVS, but FLAIR and T1‐weighted images were useful in their differentiation. Inconsistency within the literature regarding their diameter and terminology, and overlap in shape, intensity, location, and size with lacunes, conspires against their differentiation and the accuracy and reproducibility of any computational segmentation technique. The most promising approach will need to combine various MR sequences and consider all these features for accurate EPVS determination. J. Magn. Reson. Imaging 2013;38:774–785. © 2013 Wiley Periodicals, Inc.     

Absence of late gadolinium enhancement on cardiac magnetic resonance imaging in ventricular fibrillation and nonischemic cardiomyopathy

Introduction

Cardiac magnetic resonance (CMR)‐identified late gadolinium enhancement (LGE), representing regional fibrosis, is often used to predict ventricular arrhythmia risk in nonischemic cardiomyopathy (NICM). However, LGE is more closely correlated with sustained monomorphic ventricular tachycardia (SMVT) than ventricular fibrillation (VF). We characterized CMR findings of ventricular LGE in VF survivors.

Methods

We examined consecutively resuscitated VF survivors undergoing contrast‐enhanced 1.5T CMR between 9/2007 and 7/2016. We excluded coronary artery disease, hypertrophic cardiomyopathy, amyloid, sarcoid, arrhythmogenic right ventricular cardiomyopathy, and channelopathy. Preexisting implantable cardioverter‐defibrillator (ICD) was a CMR contraindication. VF patients were divided into three groups: (1) NICM, (2) left ventricular (LV) dilatation with normal LV ejection fraction (LVEF), and (3) normal LV size and LVEF. Two groups of NICM patients with and without SMVT were examined for comparison.

Results

We analyzed 87 VF patients, and found that LGE was seen in 8/22 (36%) with NICM (LVEF 38 ± 11%, LV end‐diastolic volume index [LVEDVI] 134 ± 68 mL/BSA), 11/40 (28%) with LV dilatation and normal LVEF (LVEDVI 103 ± 17 mL/BSA), 4/25 (16%) with normal LV size and LVEF. Incidence of LGE in NICM patients without prior ventricular tachycardia/VF (LVEF 36 ± 12%, LVEDVI 141 ± 46 mL/body surface area [BSA]) was 117/277 and was not lower than those with VF and NICM (42% vs 36%; P = 0.59). By contrast, 22/37 NICM patients with SMVT (LVEF 42 ± 11%, LVEDVI 123 ± 48 mL/BSA) were LGE‐positive (59% NICM‐SMVT vs 36% NICM‐VF; P = 0.04).

Conclusion

Most VF survivors with a diagnosis of NICM did not have LGE on CMR and would not have met primary prevention ICD criteria based on LVEF. Absence of LGE may not portend a benign prognosis in NICM. Novel strategies for determining SCD risk in this cohort are required.

     

High‐Grade Histologic Features of DCIS are Associated with R5 Rather than R3 Calcifications in Breast Screening Mammography

Mammographic calcification is an important radiologic feature of early breast carcinoma whose index of suspicion for malignancy may be reported by a five‐tier R‐category system. This study aims to describe the histologic diagnoses underlying screen‐detected mammographic calcifications using both digital and screen‐film mammography, and to correlate these findings with radiologic R‐categories. Patients attending the Merrion Breast Screening Unit in Dublin between 2000 and 2011 were identified, who underwent needle‐core biopsy for assessment of mammographic calcifications without associated mass or architectural distortion. Radiologic R‐category was correlated with biopsy and excision histology reports. A total of 776 cases of calcification were identified, involving 769 individual patients. The radiologic R‐categories were as follows: R3 513 (66.1%), R4 192 (24.7%), R5 71 (9.1%). The positive predictive values for malignancy were R3 32.6%, R4 69.8%, R5 95.8%. Several histologic features of DCIS were associated with R5 rather than R3 radiology: high nuclear grade, solid or cribriform architecture, necrosis, periductal inflammation or fibrosis, and associated microinvasive or invasive carcinoma. Mammographic lesions and histologic whole and invasive tumors increased in size from R3 to R5. Radiologic size of calcifications correlated with whole (but not invasive) tumor size, although it tended to underestimate it by several millimeters. Digital‐detected calcifications were more likely than screen‐film detected to be categorized as R3 and less likely R4 or R5, and there was no significant difference in positive predictive value between the two imaging techniques in any R‐category. In conclusion, histologic features of DCIS, in particular those associated with high grade, are associated with R5 radiology. There is no significant difference in positive predictive value for malignancy in any R‐category between digital and screen‐film mammography.