Dataset Information

Rebound After Fingolimod and a Single Daclizumab Injection in a Patient Retrospectively Diagnosed With NMO Spectrum Disorder-MRI Apparent Diffusion Coefficient Maps in Differential Diagnosis of Demyelinating CNS Disorders.

ABSTRACT: Objective: Differential diagnosis of neuromyelitis optica spectrum disorders (NMOSD) and multiple sclerosis (MS) or mimics can be challenging, especially in patients with atypical presentations and negative serostatus for aquaporin-4 antibodies (AQP4-Ab). This brief research report describes magnetic resonance imaging (MRI) findings focusing on quantitative apparent diffusion coefficient (ADC) histogram analysis as a potential tool to differentiate NMOSD from MS. Methods: Longitudinal MRI data obtained during routine clinical examinations were retrospectively analyzed in a patient with histologically determined cerebral NMOSD, a patient with an acute tumefactive MS lesion, and a patient with ischemic stroke. Histogram analyses of ADC maps were evaluated. Results: A patient diagnosed with MS experienced a severe rebound after fingolimod withdrawal and a single daclizumab injection. Cerebral NMOSD manifestation was confirmed by brain biopsy. However, the patient did not fulfill consensus criteria for NMOSD and was AQP4-Ab negative. Comparison of ADC histogram analyses of this patient with those from a patient with MS and one with ischemic stroke revealed differential ADC characteristics: namely a more pronounced and prolonged ADC leftward shift in inflammatory than in ischemic pathology, even more accentuated in NMOSD versus MS. Conclusion: ADC map histograms and ADC threshold values for different conditions may be useful for differentiation of large inflammatory brain lesions and further studies are merited.

SUBMITTER: Wagner F

PROVIDER: S-EPMC6170610 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Rebound After Fingolimod and a Single Daclizumab Injection in a Patient Retrospectively Diagnosed With NMO Spectrum Disorder-MRI Apparent Diffusion Coefficient Maps in Differential Diagnosis of Demyelinating CNS Disorders.

Wagner Franca F Grunder Lorenz L Hakim Arsany A Kamber Nicole N Horn Michael P MP Muellner Julia J Hoepner Robert R Wiest Roland R Metz Imke I Chan Andrew A Salmen Anke A

Frontiers in neurology 20180927

<b>Objective:</b> Differential diagnosis of neuromyelitis optica spectrum disorders (NMOSD) and multiple sclerosis (MS) or mimics can be challenging, especially in patients with atypical presentations and negative serostatus for aquaporin-4 antibodies (AQP4-Ab). This brief research report describes magnetic resonance imaging (MRI) findings focusing on quantitative apparent diffusion coefficient (ADC) histogram analysis as a potential tool to differentiate NMOSD from MS. <b>Methods:</b> Longitudi ...[more]

PMID: 30319524

Similar Datasets

Project description:PurposeTo determine the feasibility of texture analysis of apparent diffusion coefficient (ADC) maps and to assess the performance of texture analysis and ADC to predict histologic grade, parametrial invasion, lymph node metastasis, International Federation of Gynecology and Obstetrics (FIGO) stage, recurrence, and recurrence-free survival (RFS) in patients with cervical carcinoma.Materials and methodsThis retrospective study included 58 patients with cervical carcinoma who were examined with a 1.5-T MRI system and diffusion-weighted imaging with b values of 0 and 1000 sec/mm2. Software with volumes of interest on ADC maps was used to extract 45 texture features, including higher-order texture features. Receiver operating characteristic (ROC) analysis was performed to compare the diagnostic performance of ADC map random forest models and of ADC values. Dunnett test, Spearman rank correlation coefficient, Kaplan-Meier analyses, log-rank test, and Cox proportional hazards regression analyses were also used for statistical analyses.ResultsThe ADC map random forest models showed a significantly larger area under the ROC curve (AUC) than the AUC of ADC values for predicting high-grade cervical carcinoma (P = .0036), but not for parametrial invasion, lymph node metastasis, stages III-IV, and recurrence (P = .0602, .3176, .0924, and .5633, respectively). The random forest models predicted that the mean RFS rates were significantly shorter for high-grade cervical carcinomas, parametrial invasion, lymph node metastasis, stages III-IV, and recurrence (P = .0405, < .0001, .0344, .0001, and .0015, respectively); the random forest models for parametrial invasion and stages III-IV were more useful than ADC values (P = .0018) for predicting RFS.ConclusionThe ADC map random forest models were more useful for noninvasively evaluating histologic grade, parametrial invasion, lymph node metastasis, FIGO stage, and recurrence and for predicting RFS in patients with cervical carcinoma than were ADC values.Keywords: Comparative Studies, Genital/Reproductive, MR-Diffusion Weighted Imaging, MR-Imaging, Neoplasms-Primary, Pathology, Pelvis, Tissue Characterization, UterusSupplemental material is available for this article.© RSNA, 2020See also the commentary by Reinhold and Nougaret in this issue.

Project description:BackgroundBrain metastases are particularly common in patients with small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), with NSCLC showing a less aggressive clinical course and lower chemo- and radio sensitivity compared to SCLC. Early adequate therapy is highly desirable and depends on a reliable classification of tumor type. The apparent diffusion coefficient is a noninvasive neuroimaging marker with the potential to differentiate between major histological subtypes. Here we determine the sensitivity and specificity of the apparent diffusion coefficient to distinguish between NSCLC and SCLC.MethodsWe enrolled all NSCLC and SCLC patients diagnosed between 2008 and 2019 at the University Medical Center Göttingen. Cranial MR scans were visually inspected for brain metastases and the ratio of the apparent diffusion coefficient (ADC) was calculated by dividing the ADC measured within the solid part of a metastasis by a reference ADC extracted from an equivalent region in unaffected tissue on the contralateral hemisphere.ResultsOut of 411 enrolled patients, we detected 129 patients (83 NSCLC, 46 SCLC) with sufficiently large brain metastases with histologically classified lung cancer and no hemorrhage. We analyzed 185 brain metastases, 84 of SCLC and 101 of NSCLC. SCLC brain metastases showed an ADC ratio of 0.68 ± 0.12 SD, and NSCLC brain metastases showed an ADC ratio of 1.47 ± 0.31 SD. Receiver operating curve statistics differentiated brain metastases of NSCLC from SCLC with an area under the curve of 0.99 and a 95% CI of 0.98 to 1, p < 0.001. Youden's J cut-point is 0.97 at a sensitivity of 0.989 and a specificity of 0.988.ConclusionsIn patients with lung cancer and brain metastases with solid tumor parts, ADC ratio enables an ad hoc differentiation of SCLC and NSCLC, easily achieved during routine neuroradiological examination. Non-invasive MR imaging enables an early-individualized management of brain metastases from lung cancer.Trial registrationThe study was registered in the German Clinical Trials Register (DRKS00023016).

Project description:Background and Purpose- In this era of endovascular therapy (EVT) with early, complete recanalization and reperfusion, we have observed an even more rapid apparent diffusion coefficient (ADC) normalization within the acute ischemic lesion compared with the natural history or IV-tPA-treated patient. In this study, we aimed to evaluate the effect of revascularization on ADC evolution within the core lesion in the first 24 hours in acute ischemic stroke patients. Methods- This retrospective study included anterior circulation acute ischemic stroke patients treated with EVT with or without intravenous tPA (IVT) from 2015 to 2017 compared with a consecutive cohort of IVT-only patients treated before 2015. Diffusion-weighted imaging and ADC maps were used to quantify baseline core lesions. Median ADC value change and core reversal were determined at 24 hours. Diffusion-weighted imaging lesion growth was measured at 24 hours and 5 days. Good clinical outcome was defined as modified Rankin Scale score of 0 to 2 at 90 days. Results- Twenty-five patients (50%) received IVT while the other 25 patients received EVT (50%) with or without IVT. Between these patient groups, there were no differences in age, sex, baseline National Institutes of Health Stroke Scale, interhospital transfer, or IVT rates. Thirty-two patients (64%) revascularized with 69% receiving EVT. There was a significant increase in median ADC value of the core lesion at 24 hours in patients who revascularized compared with further ADC reduction in nonrevascularization patients. Revascularization patients had a significantly higher rate of good clinical outcome at 90 days, 63% versus 9% (P=0.003). Core reversal at 24 hours was significantly higher in revascularization patients, 69% versus 22% (P=0.002). Conclusions- ADC evolution in acute ischemic stroke patients with early, complete revascularization, now more commonly seen with EVT, is strikingly different from our historical understanding. The early ADC normalization we have observed in this setting may include a component of secondary injury and serve as a potential imaging biomarker for the development of future adjunctive therapies. Clinical Trial Registration- URL: https://www.clinicaltrials.gov. Unique identifier: NCT00009243.

Dataset Information

Rebound After Fingolimod and a Single Daclizumab Injection in a Patient Retrospectively Diagnosed With NMO Spectrum Disorder-MRI Apparent Diffusion Coefficient Maps in Differential Diagnosis of Demyelinating CNS Disorders.

Publications

Rebound After Fingolimod and a Single Daclizumab Injection in a Patient Retrospectively Diagnosed With NMO Spectrum Disorder-MRI Apparent Diffusion Coefficient Maps in Differential Diagnosis of Demyelinating CNS Disorders.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets