The predictive value of preoperative apparent diffusion coefficient (ADC) for facial nerve outcomes after vestibular schwannoma resection: clinical study

2020 ◽  
Vol 162 (8) ◽  
pp. 1995-2005 ◽  
Author(s):  
Katherine E. Kunigelis ◽  
Patrick Hosokawa ◽  
Gregory Arnone ◽  
David Raban ◽  
Adam Starr ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Clinical Study ◽  
Apparent Diffusion Coefficient ◽  
Facial Nerve ◽  
Vestibular Schwannoma ◽  
Predictive Value ◽  
Apparent Diffusion

scholarly journals Volumetric voxelwise apparent diffusion coefficient histogram analysis for differentiation of the fourth ventricular tumors

2018 ◽  
Vol 31 (6) ◽  
pp. 554-564 ◽  
Author(s):  
Seyedmehdi Payabvash ◽  
Tarik Tihan ◽  
Soonmee Cha
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Predictive Value ◽  
Fourth Ventricle ◽  
Histogram Analysis ◽  
Mri Findings ◽  
Patient Age ◽  
Patient Âgé ◽  
Pilocytic Astrocytomas ◽  
Apparent Diffusion

Purpose We applied voxelwise apparent diffusion coefficient (ADC) histogram analysis in addition to structural magnetic resonance imaging (MRI) findings and patients’ age for differentiation of intraaxial posterior fossa tumors involving the fourth ventricle. Participants and methods Pretreatment MRIs of 74 patients with intraaxial brain neoplasm involving the fourth ventricle, from January 1, 2004 to December 31, 2015, were reviewed. The tumor solid components were segmented and voxelwise ADC histogram variables were determined. Histogram-driven variables, structural MRI findings, and patient age were combined to devise a differential diagnosis algorithm. Results The most common neoplasms were ependymomas ( n = 21), medulloblastoma ( n = 17), and pilocytic astrocytomas ( n = 13). Medulloblastomas followed by atypical teratoid/rhabdoid tumors had the lowest ADC histogram percentile values; whereas pilocytic astrocytomas and choroid plexus papillomas had the highest ADC histogram percentile values. In a multivariable multinominal regression analysis, the ADC 10th percentile value from voxelwise histogram was the only independent predictor of tumor type ( p < 0.001). In separate binary logistic regression analyses, the 10th percentile ADC value, tumor morphology, enhancement pattern, extension into Luschka/Magendie foramina, and patient age were predictors of different tumor types. Combining these variables, we devised a stepwise diagnostic model yielding 71% to 82% sensitivity, 91% to 95% specificity, 75% to 78% positive predictive value, and 89% to 95% negative predictive value for differentiation of ependymoma, medulloblastoma, and pilocytic astrocytoma. Conclusion We have shown how the addition of quantitative voxelwise ADC histogram analysis of the tumor solid component to structural findings and patient age can help with accurate differentiation of intraaxial posterior fossa neoplasms involving the fourth ventricle based on pretreatment MRI.

scholarly journals The diagnostic value of apparent diffusion coefficient to differentiate benign and malignant meningiomas

2021 ◽  
Vol 40 (2) ◽  
pp. 141-150
Author(s):  
Risa Marissa ◽  
Rachmi Fauziah Rahayu ◽  
Hari Wujoso ◽  
Subandi Subandi ◽  
Prasetyo Sarwono Putro ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Predictive Value ◽  
Diagnostic Value ◽  
Cross Sectional Study ◽  
High Morbidity ◽  
Cross Sectional ◽  
Adc Value ◽  
Flair Sequence ◽  
Apparent Diffusion

BACKGROUNDMeningiomas are the most common primary extra-axial non-glial intracranial tumors. The severe grade of meningioma, according to WHO, has the highest recurrence rate accompanied by high morbidity and mortality rates. Therefore, it is imperative to perform pre-operative assessments so the clinician can give prompt treatment to gain a better prognosis. It is a novel alternative way of predicting meningioma’s malignancy by calculating the tumor’s apparent diffusion coefficient (ADC) value. The objective of the study was to determine the value of ADC for differentiating benign and malignant meningiomas. METHODSThis cross-sectional study involved 32 subjects with clinically diagnosed or histologically verified meningioma (21 benign and 11 malignant). They underwent a head-magnetic resonance imaging (MRI) examination and biopsy. We calculated the ADC value by creating regions of interest (ROIs) on the solid part of the tumor, guided by contrast and fluid-attenuated inversion recovery (FLAIR) sequence. We analyzed the ADC value with independent t-test and Bland-Altman graphs, calculated the average difference, CI 95%, limit of agreement between observers, and ROC. RESULTSMean ADC of malignant meningiomas (0.877 ± 0.167 x 10-3 mm2/s) was significantly lower than that of benign meningiomas (0.990 ± 0.105 x 10-3 mm2/s) (p<0.05). The ADC threshold is 0.886 x 10-3 mm2/s with sensitivity 63.6%, specificity 85.7%, positive predictive value 70% and negative predictive value 81.8%. CONCLUSIONThe ADC value measurement provides a discriminative feature to differentiate between benign and malignant meningiomas. However, the clinical applicability still needs to be elucidated, as histopathological confirmation remains the mainstay of definitive diagnosis.

scholarly journals Grading of meningioma tumors based on analyzing tumor volumetric histograms obtained from conventional MRI and apparent diffusion coefficient images

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Meysam Haghighi Borujeini ◽  
Masoume Farsizaban ◽  
Shiva Rahbar Yazdi ◽  
Alaba Tolulope Agbele ◽  
Gholamreza Ataei ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Predictive Value ◽  
Statistical Test ◽  
Post Contrast ◽  
Parametric Regression ◽  
Conventional Mri ◽  
Apparent Diffusion ◽  
Grade Ii

Abstract Background Our purpose was to evaluate the application of volumetric histogram parameters obtained from conventional MRI and apparent diffusion coefficient (ADC) images for grading the meningioma tumors. Results Tumor volumetric histograms of preoperative MRI images from 45 patients with the diagnosis of meningioma at different grades were analyzed to find the histogram parameters. Kruskal-Wallis statistical test was used for comparison between the parameters obtained from different grades. Multi-parametric regression analysis was used to find the model and parameters with high predictive value for the classification of meningioma. Mode; standard deviation on post-contrast T1WI, T2-FLAIR, and ADC images; kurtosis on post-contrast T1WI and T2-FLAIR images; mean and several percentile values on ADC; and post-contrast T1WI images showed significant differences among different tumor grades (P < 0.05). The multi-parametric linear regression showed that the ADC histogram parameters model had a higher predictive value, with cutoff values of 0.212 (sensitivity = 79.6%, specificity = 84.3%) and 0.180 (sensitivity = 70.9%, specificity = 80.8%) for differentiating the grade I from II, and grade II from III, respectively. Conclusions The multi-parametric model of volumetric histogram parameters in some of the conventional MRI series (i.e., post-contrast T1WI and T2-FLAIR images) along with the ADC images are appropriate for predicting the meningioma tumors’ grade.

scholarly journals Diagnostic performance of apparent diffusion coefficient values for the differentiation of intrahepatic cholangiocarcinoma from gastrointestinal adenocarcinoma liver metastases

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Temel Fatih Yilmaz ◽  
Mehmet Ali Gultekin ◽  
Hacı Mehmet Turk ◽  
Mehmet Besiroglu ◽  
Dilek Hacer Cesme ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Liver Metastases ◽  
Intrahepatic Cholangiocarcinoma ◽  
Predictive Value ◽  
Gastrointestinal System ◽  
Apparent Diffusion Coefficient Values ◽  
Study Results ◽  
Apparent Diffusion ◽  
Adc Values

Abstract Background We aimed to investigate whether there is a difference between intrahepatic cholangiocarcinoma (IHCC) and liver metastases of gastrointestinal system (GIS) adenocarcinoma in terms of apparent diffusion coefficient (ADC) values. Patients and methods From January 2018 to January 2020, we retrospectively examined 64 consecutive patients with liver metastases due to gastrointestinal system adenocarcinomas and 13 consecutive IHCC in our hospital’s medical records. After exclusions, fifty-three patients with 53 liver metastases and 10 IHCC were included in our study. We divided the patients into two groups as IHCC and liver metastases of GIS adenocarcinoma. For mean apparent diffusion coefficient (ADCmean) values, the region of interests (ROI) was placed in solid portions of the lesions. ADCmean values of groups were compared. Results The mean age of IHCC group was 62.50 ± 13.49 and mean age of metastases group was 61.15 ± 9.18. ADCmean values were significantly higher in the IHCC group compared to the metastatic group (p < 0.001). ROC curves method showed high diagnostic accuracy (AUC = 0.879) with cut-off value of < 1178 x 10-6 mm2/s for ADCmean (Sensitivity = 90.57, Specificity = 70.0, positive predictive value [PPV] = 94.1, negative predictive value [NPV] = 58.3) in differentiating adenocarcinoma metastases from IHCC. Conclusions The present study results suggest that ADC values have a potential role for differentiation between IHCC and GIS adenocarcinoma liver metastases which may be valuable for patient management.

Sign in / Sign up

Export Citation Format

Share Document