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 CT based radiomic approach on first line pembrolizumab in lung cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marta Zerunian ◽  
Damiano Caruso ◽  
Alberto Zucchelli ◽  
Michela Polici ◽  
Carlo Capalbo ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Progression Free Survival ◽  
Roc Curves ◽  
Mean Value ◽  
Response To Therapy ◽  
Imaging Biomarkers ◽  
First Line ◽  
Proportional Analysis ◽  
Contrast Enhanced Ct ◽  
Texture Parameters

AbstractClinical evaluation poorly predicts outcomes in lung cancer treated with immunotherapy. The aim of the study is to assess whether CT-derived texture parameters can predict overall survival (OS) and progression-free survival (PFS) in patients with advanced non-small-cell lung cancer (NSCLC) treated with first line Pembrolizumab. Twenty-one patients with NSLC were prospectively enrolled; they underwent contrast enhanced CT (CECT) at baseline and during Pembrolizumab treatment. Response to therapy was assessed both with clinical and iRECIST criteria. Two radiologists drew a volume of interest of the tumor at baseline CECT, extracting several texture parameters. ROC curves, a univariate Kaplan-Meyer analysis and Cox proportional analysis were performed to evaluate the prognostic value of texture analysis. Twelve (57%) patients showed partial response to therapy while nine (43%) had confirmed progressive disease. Among texture parameters, mean value of positive pixels (MPP) at fine and medium filters showed an AUC of 72% and 74% respectively (P < 0.001). Kaplan-Meyer analysis showed that MPP < 56.2 were significantly associated with lower OS and PFS (P < 0.0035). Cox proportional analysis showed a significant correlation between MPP4 and OS (P = 0.0038; HR = 0.89[CI 95%:0.83,0.96]). In conclusion, MPP could be used as predictive imaging biomarkers of OS and PFS in patients with NSLC with first line immune treatment.

scholarly journals Texture Analysis in the Assessment of Rectal Cancer: Comparison of T2WI and Diffusion-Weighted Imaging

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ming Li ◽  
Xiaodan Xu ◽  
Pengjiang Qian ◽  
Heng Jiang ◽  
Jianlong Jiang ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Diffusion Coefficient ◽  
High Resolution ◽  
Texture Analysis ◽  
Diffusion Weighted Imaging ◽  
Diagnostic Performance ◽  
Optimal Parameter ◽  
Diagnostic Efficiency ◽  
Apparent Diffusion ◽  
And Diffusion

Texture analysis (TA) techniques derived from T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) maps of rectal cancer can both achieve good diagnosis performance. This study was to compare TA from T2WI and ADC maps between different pathological T and N stages to confirm which TA analysis is better in diagnosis performance. 146 patients were enrolled in this study. Tumor TA was performed on every patient’s T2WI and ADC maps, respectively; then, skewness, kurtosis, uniformity, entropy, energy, inertia, and correlation were calculated. Our results demonstrated that those significant different parameters derived from T2WI had better diagnostic performance than those from ADC maps in differentiating pT3b-4 and pN1-2 stage tumors. In particular, the energy derived from T2WI was an optimal parameter for diagnostic efficiency. High-resolution T2WI plays a key point in the local stage of rectal cancer; thus, TA derived from T2WI may be a more useful tool to aid radiologists and surgeons in selecting treatment.

scholarly journals Comparison between prostate volume and intravesical prostatic protrusion in detecting bladder outlet obstruction due to benign prostatic hyperplasia

2012 ◽  
Vol 38 (1) ◽  
pp. 14-17 ◽  
Author(s):  
AKMS Hossain ◽  
AKMK Alam ◽  
AKMK Habib ◽  
MM Rashid ◽  
H Rahman ◽  
...  
Keyword(s):  
Benign Prostatic Hyperplasia ◽  
Bladder Outlet Obstruction ◽  
Prostate Volume ◽  
Digital Rectal Examination ◽  
Outlet Obstruction ◽  
Rank Correlation ◽  
Roc Curves ◽  
Prostatic Hyperplasia ◽  
Transabdominal Ultrasonography ◽  
Intravesical Prostatic Protrusion

The objectives of this study were to determine and compare the correlation of intravesical prostatic protrusion (IPP) and prostate volume (PV) with bladder outlet obstruction (BOO). This study was conducted in the department of urology, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh, between July 2009 to September 2010. Fifty benign prostatic hyperplasia (BPH) patients were included in the study. Their evaluation consisted of history along with International Prostate Symptoms Score (IPSS), digital rectal examination (DRE), transabdominal ultrasonography to measure prostate volume, intravesical prostatic protrusion & post voidal residual (PVR) urine and pressure-flow studies to detect bladder outflow obstruction (BOO). Statistical analysis included Unpaired ‘t’ test, Chisquare test and Spearman’s Rank correlation test. Receiver Operator Characteristic (ROC) curves were used to compare the correlation of PV and IPP with BOO. Mean prostate volume was significantly larger in bladder outlet obstructed patients (P<0.05). Mean IPP was significantly greater in obstructed patients (P<0.001). Area under ROC curve was 0.700 for PV and 0.821 for IPP. Prostate volume & intravesical prostatic protrusion measured through transabdominal ultrasonography are noninvasive and accessible method that significantly correlates with bladder outlet obstruction in patients with benign prostatic hyperplasia and the correlation of IPP is much more stronger than that of prostate volume. Introduction Benign prostatic hyperplasia (BPH) is one of the most common diseases in elderly men. The prevalence of histological BPH increases with age and appears in approximately 40% of men aged 50- 60 years and in approximately 90% of men aged more than 80 years1. Benign prostatic hyperplasia may lead to prostatic enlargement, bladder outlet obstruction (BOO) and lower urinary tract symptoms (LUTS). But the symptoms and obstruction do not entirely depend on prostate’s size. In contrast, intravesical prostatic protrusion (IPP) has been found to correlate with BOO2. IPP is a morphological change due to overgrowth of prostatic median and lateral lobes into the bladder and may lead to diskinetic movement of bladder during voiding. This IPP would cause more obstruction than if there were no protrusion and just enlargement of lateral lobes, as the strong bladder contraction could force open a channel between the lobes3. Several studies have previously demonstrated that the ultrasonographic measurement of IPP is able to detect BOO in BPH patients quickly and non-invasively4. This study was designed to diagnose BOO through non-invasive methods and aimed to define the correlationDOI: http://dx.doi.org/10.3329/bmrcb.v38i1.10446  Bangladesh Med Res Counc Bull 2012; 38: 14-17

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.

Diagnostic accuracy of apparent diffusion coefficient (ADC) value in differentiating malignant from benign solid liver lesions: a systematic review and meta-analysis

2021 ◽  
pp. 20210059
Author(s):  
Farhad Nalaini ◽  
Fatemeh Shahbazi ◽  
Seyedeh Maryam Mousavinezhad ◽  
Ali Ansari ◽  
Mohammadgharib Salehi
Keyword(s):  
Systematic Review ◽  
Diffusion Coefficient ◽  
Diagnostic Performance ◽  
Meta Analysis ◽  
Liver Lesions ◽  
Apparent Diffusion ◽  
Adc Values ◽  
Malignant Lesions ◽  
Malignant Liver ◽  
Malignant Liver Lesions

Objectives: We undertook a systematic review and meta-analysis of the diagnostic performance of mean apparent diffusion coefficient (ADC) values derived by diffusion-weighted (DW)-MRI in the characterization of solid benign and malignant liver lesions, and to assess their value in discriminating these lesions in daily routine practice. Methods: A systematic review of PubMed, Embase, Scopus, and Web of Science was conducted to retrieve studies that used ADC values for differentiating solid benign/dysplastic nodules and malignant liver lesions. A bivariate random-effects model with pooled sensitivity and specificity values with 95% CI (confidence interval) was used. This meta-analysis was performed on the per-lesion basis. Summary receiver operating characteristic (SROC) plot and area under curve (AUC) were created. Results: A total of 14 original articles were retrieved. The combined (95% CI) sensitivity and specificity of mean ADC values for differentiating solid benign from malignant lesions were 78% (67 to 86%) and 74% (64 to 81%), respectively. The pooled (95% CI) positive and negative LRs were respectively 3 (2.3 to 3.8) and 0.3 (0.21 to 0.43). The DOR (95% CI) was 10 (7 to 15). The AUC (95% CI) of the SROC plot was 82% (78 to 85%). Reporting bias was negligible (P value of regression test = 0.36). Mean size of malignant lesions and breathing pattern of MRI were found to be sources of heterogeneity of pooled sensitivity. Conclusion: ADC measurement independently may not be an optimal diagnostic imaging method for differentiating solid malignant from solid benign hepatic lesions. The meta-analysis showed that ADC measurement had moderate diagnostic accuracy for characterizing solid liver lesions. Further prospective and comparative studies with pre-specified ADC thresholds could be performed to investigate the best MRI protocol and ADC threshold for characterizing solid liver lesions. Advances in knowledge: ADC measurement by DW-MRI does not have a good diagnostic performance to differentiate solid malignant from solid benign lesions. Therefore, we suggest not using ADC values in clinical practice to evaluate solid liver lesions.

scholarly journals Whole-liver histogram and texture analysis on T1 maps improves the risk stratification of advanced fibrosis in NAFLD

2020 ◽  
Author(s):  
Xinxin Xu ◽  
Hong Zhu ◽  
Ruokun Li ◽  
Huimin Lin ◽  
Robert Grimm ◽  
...  
Keyword(s):  
Liver Disease ◽  
High Risk ◽  
Risk Stratification ◽  
Texture Analysis ◽  
Fatty Liver Disease ◽  
Diagnostic Performance ◽  
Multivariate Model ◽  
Advanced Fibrosis ◽  
Nonalcoholic Fatty Liver ◽  
Texture Parameters

Abstract Objectives To assess whole-liver texture analysis on T1 maps for risk stratification of advanced fibrosis in patients with suspected nonalcoholic fatty liver disease (NAFLD). Methods This retrospective study included 53 patients. Histogram and texture parameters (volume, mean, SD, median, 5th percentile, 95th percentile, skewness, kurtosis, diff-entropy, diff-variance, contrast, and entropy) of T1 maps were calculated based on the semi-automatically segmented whole-liver volume. A two-step approach combining the Nonalcoholic Fatty Liver Disease Fibrosis Score (NFS) and Fibrosis-4 Index (FIB-4) with the liver stiffness measurement (LSM) for the risk stratification was used. Univariate analysis was performed to identify significant parameters. Logistic regression models were then run on the significant features. Diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis. Results In total, 33 (62%) subjects had a low risk and 20 (38%) subjects had an intermediate-to-high risk of advanced fibrosis. The following significantly different parameters with the best performance were diff-entropy, entropy, and diff-variance, with AUROC 0.837 (95% CI 0.73–0.95), 0.821 (95% CI 0.71–0.94), and 0.807 (95% CI 0.69–0.93). The optimal combination of median, 5th percentile, and diff-entropy as a multivariate model improved the diagnostic performance to diagnose an intermediate-to-high risk of advanced fibrosis with AUROC 0.902(95% CI 0.79–0.97). Conclusions Parameters obtained by histogram and texture analysis of T1 maps may be a noninvasive analytical approach for stratifying the risk of advanced fibrosis in NAFLD. Key Points • Variable flip angle (VFA) T1 mapping can be used to acquire 3D T1 maps within a clinically acceptable duration. • Whole-liver histogram and texture parameters on T1 maps in patients with NAFLD can distinguish those with an intermediate-to-high risk of advanced fibrosis. • The multivariate model of combination of texture parameters improved the diagnostic performance for a high risk of advanced fibrosis and clinical parameters offer no added value to the multivariate model.

scholarly journals Diagnostic Accuracy of Quantitative Imaging Biomarkers in the Differentiation of Benign and Malignant Vertebral Lesions

2021 ◽  
Author(s):  
Frederic Carsten Schmeel ◽  
Simon Jonas Enkirch ◽  
Julian Alexander Luetkens ◽  
Anton Faron ◽  
Nils Lehnen ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Diagnostic Performance ◽  
Spin Echo ◽  
Quantitative Imaging ◽  
Imaging Biomarkers ◽  
Proton Density ◽  
Single Shot ◽  
Apparent Diffusion ◽  
Malignant Lesions ◽  
Magnetic Resonance Imaging Mri

Abstract Purpose To compare and combine the diagnostic performance of the apparent diffusion coefficient (ADC) derived from diffusion-weighted imaging (DWI) and proton density fat fraction (PDFF) derived from chemical-shift encoding (CSE)-based water-fat magnetic resonance imaging (MRI) for distinguishing benign and malignant vertebral bone marrow lesions (VBML). Methods A total of 55 consecutive patients with 53 benign (traumatic, inflammatory and primary) and 36 malignant (metastatic and hematologic) previously untreated VBMLs were prospectively enrolled in this IRB-approved study and underwent sagittal DWI (single-shot spin-echo echo-planar with multi-slice short TI inversion recovery fat suppression) and CSE-based MRI (gradient-echo 6‑point modified Dixon) in addition to routine clinical spine MRI at 1.5 T or 3.0 T. Diagnostic reference standard was established according to histopathology or imaging follow-up. The ADC = ADC (0, 800) and PDFF = fat / (water + fat) were calculated voxel-wise and examined for differences between benign and malignant lesions. Results The ADC and PDFF values of malignant lesions were significantly lower compared to benign lesions (mean ADC 861 × 10−6 mm2/s vs. 1323 × 10−6 mm2/s, p < 0.001; mean PDFF 3.1% vs. 28.2%, p < 0.001). The areas under the curve (AUC) and diagnostic accuracies were 0.847 (p < 0.001) and 85.4% (cut-off at 1084.4 × 10−6 mm2/s) for ADC and 0.940 (p < 0.001) and 89.9% for PDFF (cut-off at 7.8%), respectively. The combined use of ADC and PDFF improved the diagnostic accuracy to 96.6% (malignancy if ADC ≤ 1118.2 × 10−6 mm2/s and PDFF ≤ 20.0%, otherwise benign). Conclusion Quantitative evaluation of both ADC and PDFF was useful in differentiating benign VBMLs from malignancy. The combination of ADC and PDFF improved the diagnostic performance and yielded high diagnostic accuracy for the differentiation of benign and malignant VBMLs.

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