Evaluation of magnetic resonance imaging criteria for Meckel's cave lesion: logistic regression analysis and correlation with surgical findings

Abstract Lesions of Meckel's cave are extremely uncommon and difficult to diagnose. The symptoms and signs are variable, and the lesion may not appear on routine roentgenographic or computed tomographic examination. A patient with a small epidermoid tumor of Meckel's cave that was diagnosed by magnetic resonance imaging is herein reported. The epidermoid appeared as a low-intensity mass on the T1-weighted image and as a high-intensity mass on the T2-weighted image. Coronal sections defined the anatomic relationship to the trigeminal nerve. Preoperative recordings of the trigeminal sensory evoked response may be predictive of postoperative recovery of neurological deficits. Furthermore, intraoperative recording was extremely useful in avoiding inadvertent neurological injury. Review of the literature confirms the rarity of this lesion and the usefulness of magnetic resonance imaging in diagnosing it, although based on a limited number of cases.

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Trigeminal Neuralgia in a Patient with a Dural Arteriovenous Fistula in Meckel's Cave: Case Report

Neurosurgery ◽

10.1227/01.neu.0000069535.42897.1f ◽

2003 ◽

Vol 53 (1) ◽

pp. 216-221 ◽

Cited By ~ 28

Author(s):

Rose Du ◽

Devin K. Binder ◽

Van Halbach ◽

Nancy Fischbein ◽

Nicholas M. Barbaro

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Trigeminal Neuralgia ◽

Arteriovenous Fistula ◽

Trigeminal Nerve ◽

Dural Arteriovenous Fistula ◽

Gasserian Ganglion ◽

Resonance Imaging ◽

Meckel’S Cave ◽

Meckel's Cave

Abstract OBJECTIVE AND IMPORTANCE Trigeminal neuralgia is often the result of vascular compression at the root entry zone of the trigeminal nerve. We report a case of trigeminal neuralgia in a patient with a dural arteriovenous fistula in Meckel's cave. Endovascular closure of the fistula resulted in elimination of the patient's pain at the gasserian ganglion level. CLINICAL PRESENTATION A 77-year-old woman was referred for treatment of trigeminal neuralgia after failed conservative treatment, including multiple gasserian ganglion blocks. Magnetic resonance imaging of the brain suggested a vascular lesion, and cerebral angiography demonstrated a dural arteriovenous fistula in Meckel's cave. INTERVENTION Endovascular coil embolization was performed, with obliteration of the dural arteriovenous fistula and resolution of facial pain but with decreased sensation in the face. CONCLUSION Trigeminal neuralgia may be associated with complex vascular lesions around the base of the brain and along the course of the trigeminal nerve. The evaluation of patients with trigeminal neuralgia should include high-quality, thin-section, magnetic resonance imaging scans, to exclude the possibility of vascular lesions and other structural lesions. In particular, patients who are being evaluated for surgical treatment of trigeminal neuralgia should undergo magnetic resonance imaging, with a focus on the course of the trigeminal nerve.

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Relationship between magnetic resonance imaging lesions and knee symptoms in early knee osteoarthritis: A cross-sectional Japanese population study

10.21203/rs.3.rs-44187/v1 ◽

2020 ◽

Author(s):

Seiya Ota ◽

Eiji Sasaki ◽

Shizuka Sasaki ◽

Daisuke Chiba ◽

Yuka Kimura ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Logistic Regression ◽

Regression Analysis ◽

Magnetic Resonance ◽

Cartilage Damage ◽

Resonance Imaging ◽

Radiographic Evidence ◽

Cross Sectional ◽

Meniscal Lesions ◽

Structural Abnormalities

Abstract Background: The prevalence of minute structural abnormalities in early knee osteoarthritis (KOA) and their association with knee symptoms remains unclear. We investigated the prevalence of abnormalities detected by magnetic resonance imaging (MRI) and their relation to knee symptoms in women without radiographic evidence of KOA.Methods: This cross-sectional cohort study in a Japanese population included 261 women without radiographic evidence of KOA, which was defined as a Kellgren‒Lawrence grade < 2. All participants underwent T2-weighted fat-suppressed MRI of their right knee. Structural abnormalities (cartilage damage, bone marrow lesions [BMLs], subchondral cysts, bone attrition, osteophytes, meniscal lesions, and synovitis) were scored according to the Whole-Organ MRI Scoring method. Knee symptoms were evaluated by the Knee injury and Osteoarthritis and Outcome Score (KOOS). Participants were divided into early KOA and non-KOA groups based on early KOA classification criteria. Logistic regression analysis was performed to evaluate the relationship between MRI abnormalities and knee symptoms.Results: Cartilage damage were the most common abnormality (53%), followed by osteophytes (43%), and BMLs (33%). The prevalence of BMLs (47%), meniscal lesions (26%), and synovitis (37%) was higher in early KOA than in non-KOA. On logistic regression analysis, synovitis (odds ratio [OR] = 1.901, P = 0.013) and meniscal lesions (OR = 1.410, P = 0.045) were positively associated with the presence of early KOA.Conclusions: The prevalence of BMLs, meniscal lesions, and synovitis was higher in symptomatic knees. Synovitis was most strongly associated with knee pain and might be a therapeutic target in patients with early KOA.

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A Logistic Regression Analysis for Tissue Stiffness Categorization Through Magnetic Resonance Elastography

10.1115/1.0004411v ◽

2021 ◽

Author(s):

Mohammadreza Ramzanpour ◽

Mohammad Hosseini-Farid ◽

Jayse Mclean ◽

Mariusz Ziejewski ◽

Ghodrat Karami

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Magnetic Resonance ◽

Logistic Regression Analysis ◽

Magnetic Resonance Elastography ◽

Tissue Stiffness

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Multiple-response regression analysis links magnetic resonance imaging features to de-regulated protein expression and pathway activity in lower grade glioma

Oncoscience ◽

10.18632/oncoscience.353 ◽

2017 ◽

Vol 4 (5-6) ◽

pp. 57-66 ◽

Cited By ~ 5

Author(s):

Michael Lehrer ◽

Arvind Rao ◽

Anindya Bhadra ◽

Visweswaran Ravikumar ◽

James Y. Chen ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Regression Analysis ◽

Magnetic Resonance ◽

Protein Expression ◽

Lower Grade ◽

Multiple Response ◽

Imaging Features ◽

Resonance Imaging ◽

Pathway Activity ◽

Lower Grade Glioma

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Logistic Regression Algorithm Differentiates Gulf War Illness (GWI) Functional Magnetic Resonance Imaging (fMRI) Data from a Sedentary Control

Brain Sciences ◽

10.3390/brainsci10050319 ◽

2020 ◽

Vol 10 (5) ◽

pp. 319

Author(s):

Destie Provenzano ◽

Stuart D. Washington ◽

Yuan J. Rao ◽

Murray Loew ◽

James N. Baraniuk

Keyword(s):

Magnetic Resonance Imaging ◽

Logistic Regression ◽

Magnetic Resonance ◽

Functional Magnetic Resonance Imaging ◽

Gulf War ◽

Functional Magnetic Resonance ◽

Resonance Imaging ◽

Sedentary Control ◽

Gulf War Illness ◽

Cognitive Differences

Gulf War Illness (GWI) is a debilitating condition characterized by dysfunction of cognition, pain, fatigue, sleep, and diverse somatic symptoms with no known underlying pathology. As such, uncovering objective biomarkers such as differential regions of activity within a Functional Magnetic Resonance Imaging (fMRI) scan is important to enhance validity of the criteria for diagnosis. Symptoms are exacerbated by mild activity, and exertional exhaustion is a key complaint amongst sufferers. We modeled this exertional exhaustion by having GWI (n = 80) and sedentary control (n = 31) subjects perform submaximal exercise stress tests on two consecutive days. Cognitive differences were assessed by comparing fMRI scans performed during 2-Back working memory tasks before and after the exercise. Machine learning algorithms were used to identify differences in brain activation patterns between the two groups on Day 1 (before exercise) and Day 2 (after exercise). The numbers of voxels with t > 3.17 (corresponding to p < 0.001 uncorrected) were determined for brain regions defined by the Automated Anatomical Labeling (AAL) atlas. Data were divided 70:30 into training and test sets. Recursive feature selection identified twenty-nine regions of interest (ROIs) that significantly distinguished GWI from control on Day 1 and 28 ROIs on Day 2. Ten regions were present in both models between the two days, including right anterior insula, orbital frontal cortex, thalamus, bilateral temporal poles, and left supramarginal gyrus and cerebellar Crus 1. The models had 70% accuracy before exercise on Day 1 and 85% accuracy after exercise on Day 2, indicating the logistic regression model significantly differentiated subjects with GWI from the sedentary control group. Exercise caused changes in these patterns that may indicate the cognitive differences caused by exertional exhaustion. A second set of predictive models was able to classify previously identified GWI exercise subgroups START, STOPP, and POTS for both Days 1 and Days 2 with 67% and 69% accuracy respectively. This study was the first of its kind to differentiate GWI and the three sub-phenotypes START, STOPP, and POTS from a sedentary control using a logistic regression estimation method.

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Increasing utilization of multi-parametric magnetic resonance imaging in prostate cancer active surveillance.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.7_suppl.125 ◽

2019 ◽

Vol 37 (7_suppl) ◽

pp. 125-125

Author(s):

Avinash Maganty ◽

Michelle Yu ◽

Liam C Macleod ◽

Jonathan G Yabes ◽

Mina M Fam ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Prostate Cancer ◽

Logistic Regression ◽

Magnetic Resonance ◽

Active Surveillance ◽

Urban Areas ◽

Resonance Imaging ◽

Entire Study ◽

Multivariable Logistic Regression ◽

Comorbidity Burden

125 Background: Multi-parametric resonance imaging (mpMRI) has emerged as a tool that may improve risk-stratification and decrease repeated biopsies in men electing active surveillance. However, the extent to which mpMRI has been implemented in active surveillance has not been established. Therefore, we sought to characterize the use of multiparametric magnetic resonance imaging (mpMRI) in Medicare beneficiaries electing active surveillance for prostate cancer. Methods: SEER-Medicare claims data, we identified men with localized prostate cancer diagnosed between 2008-2013 and managed with active surveillance. We classified men into two treatment groups: active surveillance without mpMRI and active surveillance with mpMRI. We then fit a multivariable logistic regression models to examine changing mpMRI utilization over time, and factors associated with the receipt of mpMRI. Results: We identified 9,467 men on active surveillance. Of these, 8,178 (86%) did not receive mpMRI and 1,289 (14%) received mpMRI. The likelihood of receiving mpMRI over the entire study period increased by 3.7% (p = 0.004). On multivariable logistic regression, patients who were younger, white, had lower comorbidity burden, lived in the northeast and west, had higher incomes and lived in more urban areas had greater odds of receiving mpMRI (all p < 0.05). Conclusions: From 2008-2013, use of mpMRI in active surveillance increased gradually but significantly. Receipt of mpMRI among men on surveillance for prostate cancer varied significantly across demographic, geographic and socioeconomic strata. Going forward, studies should investigate causes for this variation and define ideal strategies for equitable, cost-effective dissemination of mpMRI technology.

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