scholarly journals DIPG-37. PREDICTING OUTCOME IN CHILDHOOD DIFFUSE MIDLINE GLIOMAS USING MAGNETIC RESONANCE IMAGING BASED TEXTURE ANALYSIS

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii294-iii294
Author(s):  
Elwira Szychot ◽  
Adam Youssef ◽  
Balaji Ganeshan ◽  
Raymond Endozo ◽  
Harpreet Hyare ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Spatial Arrangement ◽  
Imaging Biomarker ◽  
Resonance Imaging ◽  
Texture Parameter ◽  
Kaplan Meier ◽  
Texture Parameters ◽  
Apparent Diffusion ◽  
Predicting Outcome ◽  
Worse Prognosis

Abstract BACKGROUND Diffuse midline gliomas (DMG) are aggressive brain tumours with 10% overall survival (OS) at 18 months. Predicting OS will help refine treatment strategy in this patient group. MRI based texture analysis (MRTA) is a novel technique that provides objective information about spatial arrangement of MRI signal intensity and has potential as an imaging biomarker. OBJECTIVES: To investigate MRTA in predicting OS in childhood DMG. METHODS Retrospective study of patients diagnosed with DMG, based on radiological features, treated at our institution 2007–2017. MRIs were accomplished at diagnosis and 6 weeks after radiotherapy (54Gy in 30 fractions). MRTA, performed using TexRAD software, on T2W sequence and Apparent Diffusion Coefficient (ADC) maps encapsulated tumour in the largest single axial plane. MRTA comprised filtration-histogram technique using statistical and histogram metrics for quantification of texture. Kaplan-Meier analysis determined association of MRI texture parameters with OS. RESULTS 32 children 2–14 years (median 7 years) were included. MRTA was undertaken on T2W (n=32) and ADC (n=22). MRTA on T2W was better at prognosticating than on ADC maps. Children with homogenous tumour texture, at medium scale on baseline T2W MRI, had worse prognosis (mean p=0.0098, SD p=0.0115, entropy p=0.0422, mean of positive pixels (MPP) p=0.0051, kurtosis p=0.0374). MPP was the most significant texture parameter. Median survival in this group as identified by MRTA (medium texture, MPP) was 7.5 months versus 17.5 months. CONCLUSIONS DMG with more homogeneous texture on diagnostic MRI is associated with worse prognosis. MPP texture parameter is the most predictive of OS in childhood DMG.

scholarly journals Diffusion-weighted magnetic resonance imaging: biomarker for treatment response in oncology

2013 ◽  
Vol 46 (3) ◽  
pp. 178-180 ◽  
Author(s):  
Maria Luiza Testa ◽  
Rubens Chojniak ◽  
Letícia Silva Sene ◽  
Aline Santos Damascena
Keyword(s):  
Magnetic Resonance Imaging ◽  
Diffusion Coefficient ◽  
Quantitative Assessment ◽  
Therapeutic Response ◽  
Imaging Biomarker ◽  
Resonance Imaging ◽  
Adc Value ◽  
Early Increase ◽  
Apparent Diffusion ◽  
Weighted Magnetic Resonance Imaging

The authors report a case where a quantitative assessment of the apparent diffusion coefficient (ADC) of liver metastasis in a patient undergoing chemotherapy has shown to be an effective early marker for predicting therapeutic response, anticipating changes in tumor size. A lesion with lower initial ADC value and early increase in such value in the course of the treatment tends to present a better therapeutic response.

Value of MRI texture analysis for predicting new Gleason grade group

2021 ◽  
Vol 94 (1121) ◽  
pp. 20210005
Author(s):  
Xiaojing He ◽  
Hui Xiong ◽  
Haiping Zhang ◽  
Xinjie Liu ◽  
Jun Zhou ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Area Under The Curve ◽  
Gleason Grade ◽  
Diagnostic Efficiency ◽  
Resonance Imaging ◽  
Grade Group ◽  
Multiparametric Magnetic Resonance Imaging ◽  
Significant Difference ◽  
Apparent Diffusion ◽  
And Diffusion

Objectives: To explore the potential value of multiparametric magnetic resonance imaging (mpMRI) texture analysis (TA) to predict new Gleason Grade Group (GGG). Methods Fifty-eight lesions of fifty patients who underwent mpMRI scanning, including T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) prior to trans-rectal ultrasound (TRUS)-guided core prostate biopsy, were retrospectively enrolled. TA parameters were obtained by the postprocessing software, and each lesion was assigned to its corresponding GGG. TA parameters derived from T2WI and DWI were statistically analyzed in detail. Results: Energy, inertia, and correlation derived from apparent diffusion coefficient (ADC) maps and T2WI had a statistically significant difference among the five groups. Kurtosis, energy, inertia, correlation on ADC maps and Energy, inertia on T2WI were moderately related to the GGG trend. ADC-energy and T2-energy were significant independent predictors of the GGG trend. ADC-energy, T2WI-energy, and T2WI-correlation had a statistically significant difference between GGG1 and GGG2-5. ADC-energy were significant independent predictors of the GGG1. ADC-energy, T2WI-energy, and T2WI-correlation showed satisfactory diagnostic efficiency of GGG1 (area under the curve (AUC) 84.6, 74.3, and 83.5%, respectively), and ADC-energy showed excellent sensitivity and specificity (88.9 and 95.1%, respectively). Conclusion: TA parameters ADC-energy and T2-energy played an important role in predicting GGG trend. Both ADC-energy and T2-correlation produced a high diagnostic power of GGG1, and ADC-energy was perfect predictors of GGG1. Advances in knowledge: TA parameters were innovatively used to predict new GGG trend, and the predictive factors of GGG1 were screen out.

scholarly journals Value of conventional magnetic resonance imaging texture analysis in the differential diagnosis of benign and borderline/malignant phyllodes tumors of the breast

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaoguang Li ◽  
Nianping Jiang ◽  
Chunlai Zhang ◽  
Xiangguo Luo ◽  
Peng Zhong ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Texture Analysis ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Gray Level ◽  
Resonance Imaging ◽  
Phyllodes Tumors ◽  
Texture Parameters ◽  
Solid Region ◽  
Gray Values

Abstract Background The purpose of this study was to determine the potential value of magnetic resonance imaging (MRI) texture analysis (TA) in differentiating between benign and borderline/malignant phyllodes tumors of the breast. Methods The preoperative MRI data of 25 patients with benign phyllodes tumors (BPTs) and 19 patients with borderline/malignant phyllodes tumors (BMPTs) were retrospectively analyzed. A gray-level histogram and gray-level cooccurrence matrix (GLCM) were used for TA with fat-suppressed T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) images, and 2- and 7-min postcontrast T1W images on dynamic contrast-enhanced MRI (DCE-T1WI2min and DCE-T1WI7min) between BPTs and BMPTs. Independent sample t-test and Mann-Whitney U test were performed for intergroup comparison. A regression model was established by using binary logistic regression analysis, and receiver operating characteristic (ROC) curve analysis was carried out to evaluate diagnostic efficiency. Results For ADC images, the texture parameters angular second moment (ASM), correlation, contrast, entropy and the minimum gray values of ADC images (ADCMinimum) showed significant differences between the BPT group and BMPT group (all p<0.05). The parameter entropy of FS-T2WI and the maximum gray values and kurtosis of the tumor solid region of DCE-T1WI7min also showed significant differences between these two groups. Except for ADCMinimum, angular second moment of FS-T2WI (FS-T2WIASM), and the maximum gray values of DCE-T1WI7min (DCE-T1WI7min-Maximum) of the tumor solid region, the AUC values of other positive texture parameters mentioned above were greater than 0.75. Binary logistic regression analysis demonstrated that the contrast of ADC images (ADCContrast) and entropy of FS-T2WI (FS-T2WIEntropy) could be considered independent texture variables for the differential diagnosis of BPTs and BMPTs. Combined, the AUC of these parameters was 0.891 (95% CI: 0.793–0.988), with a sensitivity of 84.2% and a specificity of up to 89.0%. Conclusion Texture analysis could be helpful in improving the diagnostic efficacy of conventional MR images in differentiating BPTs and BMPTs.

scholarly journals Texture Analysis of 18F-FDG PET/CT for Differential Diagnosis Spinal Metastases

2021 ◽  
Vol 7 ◽  
Author(s):  
Xin Fan ◽  
Han Zhang ◽  
Yuzhen Yin ◽  
Jiajia Zhang ◽  
Mengdie Yang ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Diagnostic Performance ◽  
Spinal Metastases ◽  
Texture Features ◽  
Classification Model ◽  
Support Vector ◽  
Kaplan Meier ◽  
Texture Parameters ◽  
Pet Ct ◽  
Fdg Pet Ct

Purpose: To evaluate the value of texture analysis for the differential diagnosis of spinal metastases and to improve the diagnostic performance of 2-deoxy-2-[fluorine-18]fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) for spinal metastases.Methods: This retrospective analysis of patients who underwent PET/CT between December 2015 and January 2020 at Shanghai Tenth People's Hospital due to high FDG uptake lesions in the spine included 45 cases of spinal metastases and 44 cases of benign high FDG uptake lesions in the spine. The patients were randomly divided into a training group of 65 and a test group of 24. Seventy-two PET texture features were extracted from each lesion, and the Mann-Whitney U-test was used to screen the training set for texture parameters that differed between the two groups in the presence or absence of spinal metastases. Then, the diagnostic performance of the texture parameters was screened out by receiver operating characteristic (ROC) curve analysis. Texture parameters with higher area under the curve (AUC) values than maximum standardized uptake values (SUVmax) were selected to construct classification models using logistic regression, support vector machines, and decision trees. The probability output of the model with high classification accuracy in the training set was used to compare the diagnostic performance of the classification model and SUVmax using the ROC curve. For all patients with spinal metastases, survival analysis was performed using the Kaplan-Meier method and Cox regression.Results: There were 51 texture parameters that differed meaningfully between benign and malignant lesions, of which four had higher AUC than SUVmax. The texture parameters were input to build a classification model using logistic regression, support vector machine, and decision tree. The accuracy of classification was 87.5, 83.34, and 75%, respectively. The accuracy of the manual diagnosis was 84.27%. Single-factor survival analysis using the Kaplan-Meier method showed that intensity was correlated with patient survival.Conclusion: Partial texture features showed higher diagnostic value for spinal metastases than SUVmax. The machine learning part of the model combined with the texture parameters was more accurate than manual diagnosis. Therefore, texture analysis may be useful to assist in the diagnosis of spinal metastases.

scholarly journals Differentiating prostate cancer from benign prostatic hyperplasia using whole-lesion histogram and texture analysis of diffusion- and T2-weighted imaging

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pengyi Xing ◽  
Luguang Chen ◽  
Qingsong Yang ◽  
Tao Song ◽  
Chao Ma ◽  
...  
Keyword(s):  
Benign Prostatic Hyperplasia ◽  
Texture Analysis ◽  
Diagnostic Performance ◽  
Roc Curves ◽  
Prostatic Hyperplasia ◽  
Imaging Biomarkers ◽  
Image Histogram ◽  
Texture Parameters ◽  
Apparent Diffusion ◽  
Adc Values

Abstract Background To explore the usefulness of analyzing histograms and textures of apparent diffusion coefficient (ADC) maps and T2-weighted (T2W) images to differentiate prostatic cancer (PCa) from benign prostatic hyperplasia (BPH) using histopathology as the reference. Methods Ninety patients with PCa and 112 patients with BPH were included in this retrospective study. Differences in whole-lesion histograms and texture parameters of ADC maps and T2W images between PCa and BPH patients were evaluated using the independent samples t-test. The diagnostic performance of ADC maps and T2W images in being able to differentiate PCa from BPH was assessed using receiver operating characteristic (ROC) curves. Results  The mean, median, 5th, and 95th percentiles of ADC values in images from PCa patients were significantly lower than those from BPH patients (p < 0.05). Significant differences were observed in the means, standard deviations, medians, kurtosis, skewness, and 5th percentile values of T2W image between PCa and BPH patients (p < 0.05). The ADC5th showed the largest AUC (0.906) with a sensitivity of 83.3 % and specificity of 89.3 %. The diagnostic performance of the T2W image histogram and texture analysis was moderate and had the largest AUC of 0.634 for T2WKurtosis with a sensitivity and specificity of 48.9% and 79.5 %, respectively. The diagnostic performance of the combined ADC5th & T2WKurtosis parameters was also similar to that of the ADC5th & ADCDiff−Variance. Conclusions Histogram and texture parameters derived from the ADC maps and T2W images for entire prostatic lesions could be used as imaging biomarkers to differentiate PCa and BPH biologic characteristics, however, histogram parameters outperformed texture parameters in the diagnostic performance.

scholarly journals Overexpressed pseudogene MT1L associated with tumor immune infiltrates and indicates a worse prognosis in BLCA

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yanpeng Ding ◽  
Nuomin Liu ◽  
Mengge Chen ◽  
Yulian Xu ◽  
Sha Fang ◽  
...  
Keyword(s):  
Immune Cells ◽  
Biological Function ◽  
Prognostic Biomarker ◽  
Poor Survival ◽  
Common Cancer ◽  
Kaplan Meier ◽  
Cox Analysis ◽  
Kaplan Meier Plotter ◽  
Worse Prognosis

Abstract Background BLCA is a common cancer worldwide, and it is both aggressive and fatal. Immunotherapy (ICT) has achieved an excellent curative effect in BLCA; however, only some BLCA patients can benefit from ICT. MT1L is a pseudogene, and a previous study suggested that MT1L can be used as an indicator of prognosis in colorectal cancer. However, the role of MT1L in BLCA has not yet been determined. Methods Data were collected from TCGA, and logistic regression, Kaplan-Meier plotter, and multivariate Cox analysis were performed to demonstrate the correlation between the pseudogene MT1L and the prognosis of BLCA. To identify the association of MT1L with tumor-infiltrating immune cells, TIMER and TISIDB were utilized. Additionally, GSEA was performed to elucidate the potential biological function. Results The expression of MT1L was decreased in BLCA. Additionally, MT1L was positively correlated with immune cells, such as Tregs (ρ = 0.708) and MDSCs (ρ = 0.664). We also confirmed that MT1L is related to typical markers of immune cells, such as PD-1 and CTLA-4. In addition, a high MT1L expression level was associated with the advanced T and N and high grade in BLCA. Increased expression of MT1L was significantly associated with shorter OS times of BLCA patients (p < 0.05). Multivariate Cox analysis revealed that MT1L expression could be an independent prognostic factor in BLCA. Conclusion Collectively, our findings demonstrated that the pseudogene MT1L regulates the immune microenvironment, correlates with poor survival, and is an independent prognostic biomarker in BLCA.

scholarly journals Weight loss early after discharge predicts the risk of rehospitalization in non-obese patients with heart failure preserved ejection fraction

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
K Kamisaka ◽  
K Kamiya ◽  
K Iwatsu ◽  
N Iritani ◽  
Y Iida ◽  
...  
Keyword(s):  
Heart Failure ◽  
Weight Loss ◽  
Regression Analysis ◽  
Ejection Fraction ◽  
Associated Factors ◽  
Clinical Characteristics ◽  
Obese Patients ◽  
Preserved Ejection Fraction ◽  
Kaplan Meier ◽  
Worse Prognosis

Abstract Background Weight loss (WL) has been considered as a prognostic factor in heart failure with reduced ejection fraction (HFrEF). However, the prognosis and associated factors of WL in heart failure with preserved ejection fraction (HFpEF) have remained unclear. Purpose This study aimed to examine the prevalence, prognosis, and clinical characteristics of worse prognosis based on the identified WL after discharge in HFpEF. Methods The study was conducted as a part of a multicenter cohort study (Flagship). The cohort study enrolled ambulatory HF who hospitalized due to acute HF or exacerbation of chronic HF. Patients with severe cognitive, psychological disorders or readmitted within 6-month after discharge were excluded in the study. WL was defined as ≥5% weight loss in 6-month after discharge and HFpEF was defined as left ventricular ejection fraction (LVEF) ≥50% at discharge. Age, gender, etiology, prior HF hospitalization, New York Heart Association (NYHA) class, brain natriuretic peptide (BNP) or N-terminal-proBNP (NT-proBNP), anemia (hemoglobin; male &lt;13g/dL, female &lt;12g/dL), serum albumin, Geriatric Depression Scale, hand grip strength and comorbidities were collected at discharge. Patients were stratified according to their body mass index (BMI) at discharge as non-obese (BMI &lt;25) or obese (BMI ≥25). We analyzed the association between WL and HF rehospitalization from 6 month to 2 years after discharge using Kaplan-Meier curve analysis and Cox regression analysis adjusted for age and gender, and clinical characteristics associated to worse prognosis in WL using logistic regression analysis adjusted for potential confounders in HFpEF. Results A total of 619 patients with HFpEF were included in the analysis. The prevalence of WL was 12.9% in 482 non-obese and 15.3% in 137 obese patients. During 2 years, 72 patients were readmitted for HF (non-obese: 48, obese: 24). WL in non-obese independently associated with poor prognosis (hazard ratio: 2.2: 95% confidence interval: 1.13–4.25) after adjustment for age and sex, while WL in obese patients did not. Logistic regression analysis chose age (odds ratio 1.02 per 1 year; 1.00–1.05), anemia (2.14; 1.32–3.48), and BNP ≥200pg/mL or NT-proBNP ≥900pg/mL (1.83; 1.18–2.86) as independent associated factors for worse prognosis of WL in non-obese patients. Conclusion In HFpEF, WL in early after discharge in non-obese elderly patients may be a prognostic indicator for HF rehospitalization. HF management including WL prevention along with controlling anemia is likely to improve prognosis in this population. Kaplan Meier survival curves Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): A Grant-in-Aid for Scientific Research (A) from the Japan Society for the Promotion of Science

Sign in / Sign up

Export Citation Format

Share Document