OBJECTIVE.-The purpose of this study was to investigate whether MRI-typical and MRIatypical intraosseous vascular malformations are associated with familial cerebral cavernous malformation (FCCM). MATERIALS AND METHODS.-In a retrospective matched case-control study, two radiologists reviewed the spinal imaging, both CT and MRI, of 22 patients with FCCM seen between 2006 and 2017 and of age-and sex-matched control subjects for MRI-typical and MRIatypical intraosseous vascular malformations. Quantitative analysis of lesions identified included vertebral level, size, and number of lesions. Pathologic samples from two lesions were analyzed for histologic and immunohistochemical features. Whether the presence of typical, atypical, and total intraosseous vascular malformations differed between patients and control subjects was tested. For patients with complete spinal imaging, whether intraosseous vascular malformations were associated with age, sex, brain lesion count, and spinal lesion count was also tested. RESULTS.-MRI-atypical intraosseous vertebral malformations were more commonly present in patients with FCCM (p = 0.003). Sixteen lesions were found in nine patients and none in the control group. The numbers of MRI-typical intraosseous vascular malformations were similar between patients and control subjects (p = 0.480). Age was associated with typical intraosseous vascular malformations (p = 0.027), though not with atypical malformations. MRI-atypical malformations were larger (mean diameter double) than MRI-typical malformations (p = 0.023). Histologic analysis of two lesions from different patients with pathologic collapse revealed the same histologic features consistent with combined capillary-venous malformations.
BACKGROUND AND PURPOSE: Cavernous malformations occur most often in the brain but can occur in the spinal cord. Small studies of patients with familial cerebral cavernous malformations suggested a prevalence of spinal cord cavernous malformations of 20%-42%. We aimed to review our familial cohort and prospectively estimate the prevalence of spinal cord cavernous malformations. MATERIALS AND METHODS:We initially reviewed our familial cerebral cavernous malformations cohort for spinal cord cavernous malformations and reviewed clinical spine MR imaging examinations for sequence sensitivity. We then prospectively performed research MR imaging of the spinal cord in 29 patients from the familial cohort to estimate the prevalence.RESULTS: Gradient-based sequences identified the most spinal cord cavernous malformations on clinical MR images, forming the basis for developing our screening MR imaging. Screening spinal cord MR imaging demonstrated a prevalence of 72.4%, and a positive correlation with patient age and number of cerebral cavernous malformations.CONCLUSIONS: Spinal cord cavernous malformations occur commonly in the familial cerebral cavernous malformation population. Gradient-based sequences are the most sensitive and should be used when spinal cord cavernous malformations are suspected. This study establishes the prevalence in the familial population at around 70% and supports the idea that this condition is a progressive systemic disease that affects the entire central nervous system. ABBREVIATIONS: CM ¼ cavernous malformation; CCM ¼ cerebral cavernous malformation; SCCM ¼ spinal cord cavernous malformation; MEDIC ¼ Multi-Echo Data Image Combination C avernous malformations (CMs) are dilated capillary-type lowflow vascular malformations, which are prone to repeated hemorrhage and growth over time. [1][2][3][4][5] Cerebral cavernous malformations (CCMs) occur with a prevalence of about 0.5% in the general population. 1,2,6 About 80% of CCMs are sporadic, solitary, and often closely associated with a developmental venous anomaly, and about 20% of CCMs are familial/syndromic. 1,2 Mutations that lead to familial CCM syndrome can occur in 3 genes (CCM1 or KRIT1, CCM2, and CCM3 or PDCD10) with an autosomal dominant transmission. 2,4,[7][8][9] There is a particularly high prevalence of familial CCM syndrome (CCM1-common Hispanic mutation) in southwest North America due to a founder effect in early Hispanic settlers. 1,2,4,9 Spinal cord cavernous malformations (SCCMs) are less common than CCMs and have been considered rare, with relatively less attention in the CCM literature and most reported cases being sporadic nonfamilial SCCMs. [10][11][12][13][14][15][16][17][18][19] A 2009 report on a single Italian family with familial CCM found SCCMs in 5 of 12 patients (41.7%), 2 of which were discovered clinically and 3 of which were discovered with screening MR imaging (3 of 6 screened patients had SCCMs). 20 An additional 2017 report on 13 patients with familial CCM found upper SCCMs in 3 patients (23.1%). 21 Given thes...
Purpose To determine if adrenal calcifications seen at computed tomography (CT) are associated with familial cerebral cavernous malformations (fCCMs) in carriers of the CCM1 Common Hispanic Mutation. Materials and Methods This study was approved by the institutional review board. The authors retrospectively reviewed abdominal CT scans in 38 patients with fCCM, 38 unaffected age- and sex-matched control subjects, and 13 patients with sporadic, nonfamilial cerebral cavernous malformation (CCM). The size, number, and laterality of calcifications and the morphologic characteristics of the adrenal gland were recorded. Brain lesion count was recorded from brain magnetic resonance (MR) imaging in patients with fCCM. The prevalence of adrenal calcifications in patients with fCCM was compared with that in unaffected control subjects and those with sporadic CCM by using the Fisher exact test. Additional analyses were performed to determine whether age and brain lesion count were associated with adrenal findings in patients with fCCM. Results Small focal calcifications (SFCs) (≤5 mm) were seen in one or both adrenal glands in 19 of the 38 patients with fCCM (50%), compared with 0 of the 38 unaffected control subjects (P < .001) and 0 of the 13 subjects with sporadic CCM (P = .001). Adrenal calcifications in patients with fCCM were more frequently left sided, with 17 of 19 patients having more SFCs in the left adrenal gland than the right adrenal gland and 50 of the 61 observed SFCs (82%) found in the left adrenal gland. No subjects had SFCs on the right side only. In patients with fCCM, the presence of SFCs showed a positive correlation with age (P < .001) and number of brain lesions (P < .001). Conclusion Adrenal calcifications identified on CT scans are common in patients with fCCM and may be a clinically silent manifestation of disease.
Introduction Familial cerebral cavernous malformation (CCM) patients present with multiple lesions that can grow both in number and size over time and are reliably detected on susceptibility-weighted imaging (SWI). Manual counting of lesions is arduous and subject to high variability. We aimed to develop an automated algorithm for counting CCM microbleeds (lesions <5mm in diameter) on SWI images. Methods Fifty-seven familial CCM type-1 patients were included in this institutional review board-approved study. Baseline SWI (n=57) and follow-up SWI (n=17) were performed on a 3T Siemens MR scanner with lesions counted manually by the study neuroradiologist. We modified an algorithm for detecting radiation-induced microbleeds on SWI images in brain tumor patients, using a training set of 22 manually delineated CCM microbleeds from 2 random scans. Manual and automated counts were compared using linear regression with robust standard errors, intra-class correlation (ICC), and paired t-tests. A validation analysis comparing the automated counting algorithm and a consensus read from two neuroradiologists was used to calculate sensitivity, the proportion of microbleeds correctly identified by the automated algorithm. Results Automated and manual microbleed counts were in strong agreement in both baseline (ICC=0.95, p<0.001) and longitudinal (ICC=0.88, p<0.001) analyses, with no significant difference between average counts (baseline p=0.11, longitudinal p=0.29). In the validation analysis, the algorithm correctly identified 662 of 1325 microbleeds (sensitivity=50%), again with strong agreement between approaches (ICC=0.77, p<0.001). Conclusion The automated algorithm is a consistent method for counting microbleeds in familial CCM patients that can facilitate lesion quantification and tracking.
Background: Patient-reported quality of life (QoL) using standardized tools have been proposed as outcome measures in clinical trials. The NeuroQoL scale has been evaluated in patients with common neurological disorders (e.g., ischemic stroke, epilepsy, ALS, and Parkinson’s), but has not been applied to familial cerebral cavernous malformation (FCCM). FCCM is typically characterized by multiple brain lesions that can cause clinical symptoms (hemorrhages, seizures, headaches, neurological deficits) and affect QoL. The purpose of this study was to summarize NeuroQoL domain scores in FCCM patients. Methods: NeuroQoL short forms covering 12 QoL domains (Figure) were completed by 50 FCCM adults enrolled in the Brain Vascular Malformation Consortium CCM Project. Raw scores summing responses in each domain were converted to T-scores, which are standardized to general (8 domains) or clinical (4 domains) reference populations with mean of 50 and standard deviation of 10. One-sample t-tests were used to determine whether mean T-scores were significantly different from 50 (p<0.05). Results: We observed significant differences between FCCM and the reference populations on several domains (Figure). Compared to the general reference population, FCCM patients were more likely to have higher positive affect (56, p<0.001) and less depression (55, p<0.001), but lower social satisfaction (48, p=0.032). Compared to the clinical reference population, FCCM patients reported significantly less stigma (61, p<0.001) and less fatigue (54, p=0.018). Conclusion: FCCM patients differed from the reference populations on several NeuroQoL domains, including positive affect, depression, stigma, fatigue and social satisfaction. Further studies are needed to understand the effect of clinical symptoms on NeuroQoL domains in FCCM.
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