Bell's palsy misdiagnosis: characteristics of occult tumors causing facial paralysis.

OBJECTIVE: The aim of this study was to report the incidence and clinical course of a series of patients who were misdiagnosed with Bell's palsy and were eventually proven to have occult neoplasms. METHODS: Two hundred forty patients with unilateral facial paralysis who were assessed at the facial nerve reanimation clinic, Victoria Hospital, London Health Science Centre, from 2008 through 2017 were reviewed. Persistent paralysis without recovery was the presenting complaint. RESULTS: Nine patients (3.8%) who were proven to have occult neoplasms initially presented with a diagnosis of Bell's palsy. The mean diagnostic delay was 43.5 months. Four patients were proven to have skin cancers, 3 patients had parotid cancers, and 2 patients had facial nerve schwannomas as a final diagnosis. Initial magnetic resonance imaging (MRI) was performed in all 9 patients and 8 underwent a follow-up MRI. An occult tumor was identified upon review of the original MRI in one patient and at follow-up MRI in 8 patients. The mean time interval between the initial and follow-up imaging was 30.8 months. The disease status at most recent follow-up were no evidence of disease in 2 patients (22%) and alive with disease in 7 patients (78%). An irreversible, progressive pattern of facial paralysis combined with pain, multiple cranial neuropathies or history of skin cancer were predictable risk factors for occult tumors. Seven out of the 9 patients (77.8%) underwent at least one type of facial reanimation surgery, and the final subjective results by the surgeon were available for 5 patients. Three out of the 5 (60%) patients who were available for final subjective analysis were reported as Grade III according to the modified House-Brackmann scale. CONCLUSION: Occult facial nerve neoplasm should be suspected in patients with progressive and irreversible facial paralysis but the diagnosis may only become evident with follow-up imaging. Facial reanimation surgery is a satisfactory option for these patients.

Severe Intracranial Involvement in Giant Cell Arteritis: 5 Cases and Literature Review.

OBJECTIVE: Involvement of intracranial arteries in giant cell arteritis (GCA) is rare. We describe the neurologic complications of intracranial GCA (IC GCA) and available treatment options. METHODS: We describe 5 IC GCA cases from 3 Canadian vasculitis centers and review the literature. We searched English-language publications reporting similar patients meeting American College of Rheumatology (ACR) criteria for GCA and having intracranial artery involvement diagnosed by autopsy, magnetic resonance angiography, computed tomography angiography, or conventional angiography. RESULTS: All 5 cases of IC GCA met ACR criteria for GCA; 4 cases had a temporal artery biopsy that was consistent with GCA. All cases experienced cerebrovascular accident(s). Arteritis involved the following vessels: intracranial internal carotid (n = 1), vertebrobasilar arteries (n = 1), or both (n = 3). All cases received aspirin and oral prednisone (preceded by intravenous methylprednisone in 3 cases), combined with an immunosuppressant in 4 cases. All patients survived; 2 had complete neurological recovery, 3 had residual neurologic sequelae. The literature review included 42 cases from 28 publications. The clinical features of the reported cases were similar to those of our 5 cases. However, mortality was 100% in untreated cases (n = 2), 58% in those treated with corticosteroid alone (n = 31), and 40% in those treated with corticosteroid and an immunosuppressant (n = 10). CONCLUSION: IC GCA appears to be associated with neurologic complications and mortality. In some cases corticosteroid alone was not sufficient to prevent neurologic complications. The role of additional immunosuppressive agents needs further investigation.

Evaluating the impact of a Canadian national anatomy and radiology contouring boot camp for radiation oncology residents.

BACKGROUND: Radiation therapy treatment planning has advanced over the past 2 decades, with increased emphasis on 3-dimensional imaging for target and organ-at-risk (OAR) delineation. Recent studies suggest a need for improved resident instruction in this area. We developed and evaluated an intensive national educational course ("boot camp") designed to provide dedicated instruction in site-specific anatomy, radiology, and contouring using a multidisciplinary (MDT) approach. METHODS: The anatomy and radiology contouring (ARC) boot camp was modeled after prior single-institution pilot studies and a needs-assessment survey. The boot camp incorporated joint lectures from radiation oncologists, anatomists, radiologists, and surgeons, with hands-on contouring instruction and small group interactive seminars using cadaveric prosections and correlative axial radiographs. Outcomes were evaluated using pretesting and posttesting, including anatomy/radiology multiple-choice questions (MCQ), timed contouring sessions (evaluated relative to a gold standard using Dice similarity metrics), and qualitative questions on satisfaction and perceived effectiveness. Analyses of pretest versus posttest scores were performed using nonparametric paired testing. RESULTS: Twenty-nine radiation oncology residents from 10 Canadian universities participated. As part of their current training, 29%, 75%, and 21% receive anatomy, radiology, and contouring instruction, respectively. On posttest scores, the MCQ knowledge scores improved significantly (pretest mean 60% vs posttest mean 80%, P<.001). Across all contoured structures, there was a 0.20 median improvement in students' average Dice score (P<.001). For individual structures, significant Dice improvements occurred in 10 structures. Residents self-reported an improved ability to contour OARs and interpret radiographs in all anatomic sites, 92% of students found the MDT format effective for their learning, and 93% found the boot camp more effective than educational sessions at their own institutions. All of the residents (100%) would recommend this course to others. CONCLUSIONS: The ARC boot camp is an effective intervention for improving radiation oncology residents' knowledge and understanding of anatomy and radiology in addition to enhancing their confidence and accuracy in contouring.

Regression Segmentation for M³ Spinal Images.

Clinical routine often requires to analyze spinal images of multiple anatomic structures in multiple anatomic planes from multiple imaging modalities (M(3)). Unfortunately, existing methods for segmenting spinal images are still limited to one specific structure, in one specific plane or from one specific modality (S(3)). In this paper, we propose a novel approach, Regression Segmentation, that is for the first time able to segment M(3) spinal images in one single unified framework. This approach formulates the segmentation task innovatively as a boundary regression problem: modeling a highly nonlinear mapping function from substantially diverse M(3) images directly to desired object boundaries. Leveraging the advancement of sparse kernel machines, regression segmentation is fulfilled by a multi-dimensional support vector regressor (MSVR) which operates in an implicit, high dimensional feature space where M(3) diversity and specificity can be systematically categorized, extracted, and handled. The proposed regression segmentation approach was thoroughly tested on images from 113 clinical subjects including both disc and vertebral structures, in both sagittal and axial planes, and from both MRI and CT modalities. The overall result reaches a high dice similarity index (DSI) 0.912 and a low boundary distance (BD) 0.928 mm. With our unified and expendable framework, an efficient clinical tool for M(3) spinal image segmentation can be easily achieved, and will substantially benefit the diagnosis and treatment of spinal diseases.

Gradient competition anisotropy for centerline extraction and segmentation of spinal cords.

Centerline extraction and segmentation of the spinal cord--an intensity varying and elliptical curvilinear structure under strong neighboring disturbance are extremely challenging. This study proposes the gradient competition anisotropy technique to perform spinal cord centerline extraction and segmentation. The contribution of the proposed method is threefold--1) The gradient competition descriptor compares the image gradient obtained at different detection scales to suppress neighboring disturbance. It reliably recognizes the curvilinearity and orientations of elliptical curvilinear objects. 2) The orientation coherence anisotropy analyzes the detection responses offered by the gradient competition descriptor. It enforces structure orientation consistency to sustain strong disturbance introduced by high contrast neighboring objects to perform centerline extraction. 3) The intensity coherence segmentation quantifies the intensity difference between the centerline and the voxels in the vicinity of the centerline. It effectively removes the object intensity variation along the structure to accurately delineate the target structure. They constitute the gradient competition anisotropy method which can robustly and accurately detect the centerline and boundary of the spinal cord. It is validated and compared using 25 clinical datasets. It is demonstrated that the proposed method well suits the applications of spinal cord centerline extraction and segmentation.

Intervertebral disc segmentation in MR images using anisotropic oriented flux.

This study proposes an unsupervised intervertebral disc segmentation system based on middle sagittal spine MR scans. The proposed system employs the novel anisotropic oriented flux detection scheme which helps distinguish the discs from the neighboring structures with similar intensity, recognize ambiguous disc boundaries, and handle the shape and intensity variation of the discs. Based on minimal user interaction, the proposed system begins with vertebral body tracking to infer the information regarding the positions and orientations of the target intervertebral discs. The information is employed in a set of image descriptors, which jointly constitute an energy functional describing the desired disc segmentation result. The energy functional is minimized by a level set based active contour model to perform disc segmentation. The proposed segmentation system is evaluated using a database consisting of 455 intervertebral discs extracted from 69 middle sagittal slices. It is demonstrated that the proposed method is capable of delivering accurate results for intervertebral disc segmentation.