Haralick textural features on T2‐weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer

No abstract is available for this paper.

• Publication year

  2017

• Venue

  Journal of Magnetic Resonance Imaging

• Publication date

  2017-01-01

• Fields of study

  Medicine

• Identifiers
  DOI 10.1002/jmri.25335PMID 27345946
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Synopsis of the PI-RADS v2 Guidelines for Multiparametric Prostate Magnetic Resonance Imaging and Recommendations for Use.

  2016cited by this paper
• Use of texture analysis based on contrast‐enhanced MRI to predict treatment response to chemoradiotherapy in nasopharyngeal carcinoma

  2016cited by this paper
• MR-T2-weighted signal intensity: a new imaging biomarker of prostate cancer aggressiveness

  2016cited by this paper
• A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities

  2015cited by this paper
• A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities

  2015cited by this paper
• Texture features on T2-weighted magnetic resonance imaging: new potential biomarkers for prostate cancer aggressiveness

  2015cited by this paper
• 18F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort

  2015cited by this paper
• Evaluation of tumor-derived MRI-texture features for discrimination of molecular subtypes and prediction of 12-month survival status in glioblastoma.

  2015cited by this paper
• Use of the Prostate Imaging Reporting and Data System (PI-RADS) for Prostate Cancer Detection with Multiparametric Magnetic Resonance Imaging: A Diagnostic Meta-analysis.

  2015cited by this paper
• A framework for multimodal imaging-based prognostic model building: Preliminary study on multimodal MRI in Glioblastoma Multiforme

  2015cited by this paper
• Texture analysis on MR images helps predicting non-response to NAC in breast cancer

  2015influential reference
• Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores

  2015cited by this paper
• Clinical utility of the normalized apparent diffusion coefficient for preoperative evaluation of the aggressiveness of prostate cancer

  2014cited by this paper
• Multi-Image Texture Analysis in Classification of Prostatic Tissues from MRI. Preliminary Results

  2014cited by this paper
• Non-small cell lung cancer: histopathologic correlates for texture parameters at CT.

  2013cited by this paper
• Texture analysis in assessment and prediction of chemotherapy response in breast cancer

  2013influential reference
• Quantitative analysis of multiparametric prostate MR images: differentiation between prostate cancer and normal tissue and correlation with Gleason score--a computer-aided diagnosis development study.

  2013cited by this paper
• Computer-aided diagnosis of prostate cancer in the peripheral zone using multiparametric MRI

  2012cited by this paper
• Snakes With an Ellipse-Reproducing Property

  2012cited by this paper
• Radiomics: extracting more information from medical images using advanced feature analysis.

  2012cited by this paper
• Pretreatment endorectal coil magnetic resonance imaging findings predict biochemical tumor control in prostate cancer patients treated with combination brachytherapy and external-beam radiotherapy.

  2012influential reference
• Novel head and neck cancer survival analysis approach: Random survival forests versus cox proportional hazards regression

  2012cited by this paper
• Central gland and peripheral zone prostate tumors have significantly different quantitative imaging signatures on 3 tesla endorectal, in vivo T2‐weighted MR imagery

  2012cited by this paper
• Prostate cancer vs. post-biopsy hemorrhage: diagnosis with T2- and diffusion-weighted imaging.

  2011cited by this paper
• Relationship between apparent diffusion coefficients at 3.0-T MR imaging and Gleason grade in peripheral zone prostate cancer

  2011cited by this paper
• Is apparent diffusion coefficient associated with clinical risk scores for prostate cancers that are visible on 3-T MR images?

  2011cited by this paper
• Diffusion-weighted endorectal MR imaging at 3 T for prostate cancer: tumor detection and assessment of aggressiveness.

  2011cited by this paper
• Relationship between apparent diffusion coefficients at 3.0-T MR imaging and Gleason grade in peripheral zone prostate cancer.

  2011cited by this paper
• Diffusion-weighted and dynamic contrast-enhanced MRI of prostate cancer: correlation of quantitative MR parameters with Gleason score and tumor angiogenesis.

  2011cited by this paper
• Is apparent diffusion coefficient associated with clinical risk scores for prostate cancers that are visible on 3-T MR images?

  2011cited by this paper
• Prostate cancer vs. post‐biopsy hemorrhage: Diagnosis with T2‐ and diffusion‐weighted imaging

  2010cited by this paper
• Pretreatment endorectal magnetic resonance imaging and magnetic resonance spectroscopic imaging features of prostate cancer as predictors of response to external beam radiotherapy.

  2009cited by this paper
• Effects of MRI acquisition parameter variations and protocol heterogeneity on the results of texture analysis and pattern discrimination: an application-oriented study.

  2009cited by this paper
• Non-Hodgkin lymphoma response evaluation with MRI texture classification

  2009cited by this paper
• Whole brain radiotherapy with radiosensitizer for brain metastases

  2009cited by this paper
• Computerized characterization of prostate cancer by fractal analysis in MR images

  2009cited by this paper
• Intensity-modulated radiation therapy: supportive data for prostate cancer.

  2008cited by this paper
• Prostate cancer: role of pretreatment MR in predicting outcome after external-beam radiation therapy--initial experience.

  2008cited by this paper
• The Phoenix definition of biochemical failure predicts for overall survival in patients with prostate cancer

  2008influential reference
• Risk of prostate cancer recurrence in men treated with radiation alone or in conjunction with combined or less than combined androgen suppression therapy.

  2008cited by this paper
• Random survival forests

  2008cited by this paper
• 3D Computation of Gray Level Co-occurrence in Hyperspectral Image Cubes

  2007cited by this paper
• Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors

  2005cited by this paper
• Texture analysis for tissue discrimination on T1‐weighted MR images of the knee joint in a multicenter study: Transferability of texture features and comparison of feature selection methods and classifiers

  2005cited by this paper
• Quantifying the impact of seminal vesicle invasion identified using endorectal magnetic resonance imaging on PSA outcome after radiation therapy for patients with clinically localized prostate cancer.

  2004cited by this paper
• MRI texture analysis on texture test objects, normal brain and intracranial tumors.

  2003cited by this paper
• Random Forests

  2001cited by this paper
• Biochemical outcome after radical prostatectomy, external beam radiation therapy, or interstitial radiation therapy for clinically localized prostate cancer.

  1998cited by this paper
• Biochemical outcome after radical prostatectomy, external beam radiation therapy, or interstitial radiation therapy for clinically localized prostate cancer.

  1998cited by this paper
• A simulation study of the number of events per variable in logistic regression analysis.

  1996cited by this paper
• MR image texture analysis--an approach to tissue characterization.

  1993cited by this paper
• Textural Features for Image Classification

  1973cited by this paper

• Radiomics as a tool for predicting biochemical recurrence after total prostatectomy: a systematic review and meta-analysis.

  2026cites this paper
• Radiomics-Based Characterization of Aggressive Prostate Cancer Variants: Diagnostic Challenges and Opportunities

  2026cites this paper
• Precision medicine in prostate cancer: individualized treatment through radiomics, genomics, and biomarkers

  2025cites this paper
• Radiological and Biological Dictionary of Radiomics Features: Addressing Understandable AI Issues in Personalized Prostate Cancer; Dictionary Version PM1.0

  2025cites this paper
• Combining MRI radiomics, hypoxia gene signature score and clinical variables for prediction of biochemical recurrence-free survival after radiotherapy in prostate cancer

  2025cites this paper
• A method for sensitivity analysis of automatic contouring algorithms across different contrast weightings using synthetic magnetic resonance imaging

  2025cites this paper
• Evaluating the prognostic significance of artificial intelligence-delineated gross tumor volume and prostate volume measurements for prostate radiotherapy.

  2025cites this paper
• Evaluating the feasibility of AI-predicted bpMRI image features for predicting prostate cancer aggressiveness: a multi-center study

  2025cites this paper
• A Method for Sensitivity Analysis of Automatic Contouring Algorithms Across Different MRI Contrast Weightings Using SyntheticMR

  2025cites this paper
• Computed Tomography-Based Radiomics Prediction of Biochemical Failure and Distant Metastasis in Patients With High- and Very High-Risk Localized Prostate Cancer

  2025cites this paper
• Magnetic Resonance Imaging Techniques for Post-Treatment Evaluation After External Beam Radiation Therapy of Prostate Cancer: Narrative Review

  2024cites this paper
• Developmental trends and knowledge frameworks in the application of radiomics in prostate cancer: a bibliometric analysis from 2000 to 2024

  2024cites this paper
• Biological and Radiological Dictionary of Radiomics Features: Addressing Understandable AI Issues in Personalized Prostate Cancer; Dictionary Version PM1.0

  2024cites this paper
• Prediction of prostate cancer recurrence after radiotherapy using a fused machine learning approach: utilizing radiomics from pretreatment T2W MRI images with clinical and pathological information

  2024cites this paper
• Radiomics and Mechanistic Hybrid Model for Prediction of Recurrence in Prostate Cancer

  2024cites this paper
• Radiogenomics Map-Based Molecular and Imaging Phenotypical Characterization in Localised Prostate Cancer Using Pre-Biopsy Biparametric MR Imaging

  2024cites this paper
• APOE from astrocytes restores Alzheimer’s Aβ-pathology and DAM-like responses in APOE deficient microglia

  2024cites this paper
• Machine learning based prediction of image quality in prostate MRI using rapid localizer images

  2024cites this paper
• Deep-learning models for image-based gynecological cancer diagnosis: a systematic review and meta- analysis

  2024cites this paper
• Evaluation of a Deep Learning-based Algorithm for Post-Radiotherapy Prostate Cancer Local Recurrence Detection Using Biparametric MRI.

  2023cites this paper
• Robustness of magnetic resonance imaging and positron emission tomography radiomic features in prostate cancer: Impact on recurrence prediction after radiation therapy

  2023cites this paper
• Computed Tomography-Based Radiomics for Long-Term Prognostication of High-Risk Localized Prostate Cancer Patients Received Whole Pelvic Radiotherapy

  2023cites this paper
• Radiomics for the radiologist: opportunities and challenges

  2023cites this paper
• Spatial assessments in texture analysis: what the radiologist needs to know

  2023cites this paper
• Prostate Region-Wise Imaging Biomarker Profiles for Risk Stratification and Biochemical Recurrence Prediction

  2023influential citation
• MRI-derived radiomics models for diagnosis, aggressiveness, and prognosis evaluation in prostate cancer

  2023cites this paper
• MRI-based nomograms and radiomics in presurgical prediction of extraprostatic extension in prostate cancer: a systematic review

  2023cites this paper
• Using intratumor heterogeneity of immunohistochemistry biomarkers to classify laryngeal and hypopharyngeal tumors based on histological features.

  2023cites this paper
• Integrating CT-based radiomic model with clinical features improves long-term prognostication in high-risk prostate cancer

  2023cites this paper
• Textural Features of MR Images Correlate with an Increased Risk of Clinically Significant Cancer in Patients with High PSA Levels

  2023cites this paper
• Predicting risk of metastases and recurrence in soft-tissue sarcomas via Radiomics and Formal Methods

  2023cites this paper
• Radiogenomics Reveals Correlation between Quantitative Texture Radiomic Features of Biparametric MRI and Hypoxia-Related Gene Expression in Men with Localised Prostate Cancer

  2023cites this paper
• The Use of MRI-Derived Radiomic Models in Prostate Cancer Risk Stratification: A Critical Review of Contemporary Literature

  2023cites this paper
• Beyond diagnosis: is there a role for radiomics in prostate cancer management?

  2023cites this paper
• Incremental prognostic value of ADC histogram analysis in patients with high-risk prostate cancer receiving adjuvant hormonal therapy after radical prostatectomy

  2023cites this paper
• Predicting effectiveness of anti-VEGF injection through self-supervised learning in OCT images.

  2023cites this paper
• Image quality and whole-lesion histogram and texture analysis of diffusion-weighted imaging of breast MRI based on advanced ZOOMit and simultaneous multislice readout-segmented echo-planar imaging

  2022cites this paper
• The latest application progress of radiomics in prediction and diagnosis of liver diseases

  2022cites this paper
• Performance of Machine Learning Methods Based on Multi-Sequence Textural Parameters Using Magnetic Resonance Imaging and Clinical Information to Differentiate Malignant and Benign Soft Tissue Tumors.

  2022cites this paper
• Prostate Surface Distension and Tumor Texture Descriptors From Pre-Treatment MRI Are Associated With Biochemical Recurrence Following Radical Prostatectomy: Preliminary Findings

  2022cites this paper
• Noninvasive Method for Predicting the Expression of Ki67 and Prognosis in Non-Small-Cell Lung Cancer Patients: Radiomics

  2022cites this paper
• Development of a radiomic-clinical nomogram for prediction of survival in patients with serous ovarian cancer.

  2022cites this paper
• Multiparametric MRI-based radiomics model to predict pelvic lymph node invasion for patients with prostate cancer

  2022cites this paper
• Predicting the impact of standard and hypofractionated schedules in prostate cancer radiotherapy with a mechanistic model

  2022cites this paper
• Radiomics-based prognosis classification for high-risk prostate cancer treated with radiotherapy

  2022cites this paper
• Repeatability, robustness, and reproducibility of texture features on 3 Tesla liver MRI.

  2022cites this paper
• MRI radiomics predicts progression-free survival in prostate cancer

  2022cites this paper
• Changes in Magnetic Resonance Imaging Radiomic Features in Response to Androgen Deprivation Therapy in Patients with Intermediate- and High-risk Prostate Cancer.

  2022cites this paper
• Integrative Machine Learning Prediction of Prostate Biopsy Results From Negative Multiparametric MRI

  2021cites this paper
• Radiomics and Digital Image Texture Analysis in Oncology (Review)

  2021cites this paper
• Comparison of MRI features in lipid-rich and lipid-poor adrenal adenomas using subjective and quantitative analysis

  2021cites this paper
• Artificial intelligence and imaging biomarkers for prostate radiation therapy during and after treatment.

  2021cites this paper
• The diagnostic value of a non-contrast computed tomography scan-based radiomics model for acute aortic dissection

  2021cites this paper
• Mechanistic Simulation of Tumor Response Outperforms Radiomics Predicting Recurrence in Prostate Cancer Radiotherapy

  2021cites this paper
• Value of MRI texture analysis for predicting new Gleason grade group.

  2021cites this paper
• Towards a Reduced In Silico Model Predicting Biochemical Recurrence After Radiotherapy in Prostate Cancer

  2021cites this paper
• Utility of T2-weighted MRI texture analysis in assessment of peripheral zone prostate cancer aggressiveness: a single-arm, multicenter study

  2021cites this paper
• MRI in prostate cancer radiology: what is currently known?

  2021cites this paper
• State of the art of radiomic analysis in the clinical management of prostate cancer: a systematic review.

  2021cites this paper
• Multiparametric MRI and Radiomics in Prostate Cancer: A Review of the Current Literature

  2021cites this paper
• Treatment evaluation and prognosis prediction using radiomics in clinical practice

  2021cites this paper
• Target Heterogeneity in Oncology: The Best Predictor for Differential Response to Radioligand Therapy in Neuroendocrine Tumors and Prostate Cancer

  2021cites this paper
• Primary clinical study of radiomics for diagnosing simple bone cyst of the jaw.

  2021cites this paper
• The clinical guiding value of a radiomics model for androgen deprivation therapy for prostate cancer

  2021cites this paper
• Applications of radiomics in genitourinary tumors.

  2020cites this paper
• Brain Tumors

  2020cites this paper
• Can clinical radiomics nomogram based on 3D multiparametric MRI features and clinical characteristics estimate early recurrence of pelvic chondrosarcoma?

  2020cites this paper
• Combining molecular and imaging metrics in cancer: radiogenomics

  2020cites this paper
• T2w-MRI signal normalization affects radiomics features reproducibility.

  2020cites this paper
• Magnetic resonance radiomics for prediction of extraprostatic extension in non-favorable intermediate- and high-risk prostate cancer patients

  2020cites this paper
• Radiomics Based on MRI as a Biomarker to Guide Therapy by Predicting Upgrading of Prostate Cancer From Biopsy to Radical Prostatectomy

  2020cites this paper
• Multicentre Evaluation of MRI-based Radiomics Features: A Phantom Study.

  2020cites this paper
• Radiomics of Multiparametric MRI to Predict Biochemical Recurrence of Localized Prostate Cancer After Radiation Therapy

  2020cites this paper
• Quantitative Prostate MRI

  2020cites this paper
• Machine and deep learning methods for radiomics.

  2020cites this paper
• Outcome prediction of head and neck squamous cell carcinoma by MRI radiomic signatures

  2020cites this paper
• Prostate MRI radiomics: A systematic review and radiomic quality score assessment.

  2020cites this paper
• Radiomics Based on Multiparametric Magnetic Resonance Imaging to Predict Extraprostatic Extension of Prostate Cancer

  2020cites this paper
• MR Imaging Texture Analysis in the Abdomen and Pelvis.

  2020cites this paper
• Standardization of CT radiomics features for multi-center analysis: impact of software settings and parameters

  2020cites this paper
• Review of the Role of Radiomics in Tumour Risk Classification and Prognosis of Cancer

  2020cites this paper
• Cone-beam computed tomography-based radiomics in prostate cancer: a mono-institutional study

  2020cites this paper
• Positron Emission Tomography for Response Evaluation in Microenvironment-Targeted Anti-Cancer Therapy

  2020cites this paper
• MRI Morphometry in Brain Tumors: Challenges and Opportunities in Expert, Radiomic, and Deep-Learning-Based Analyses

  2020cites this paper
• Mini review: Personalization of the radiation therapy management of prostate cancer using MRI-based radiomics.

  2020cites this paper
• Value of MRI texture analysis for predicting high-grade prostate cancer.

  2020cites this paper
• Identifying Cross-Scale Associations between Radiomic and Pathomic Signatures of Non-Small Cell Lung Cancer Subtypes: Preliminary Results

  2020cites this paper
• Utility of T2-weighted MRI to Differentiate Adrenal Metastases from Lipid-Poor Adrenal Adenomas.

  2020cites this paper
• A novel imaging based Nomogram for predicting post-surgical biochemical recurrence and adverse pathology of prostate cancer from pre-operative bi-parametric MRI

  2020influential citation
• MRI texture analysis in the abdomen and pelvis

  2020cites this paper
• a pilot study on dosimetric and radiomics analysis of urethral strictures following HDr brachytherapy as monotherapy for localized prostate cancer

  2020cites this paper
• Multicenter evaluation of MRI-based radiomic features A Phantom Study

  2020cites this paper
• Texture analysis of magnetic resonance images of the human placenta throughout gestation: A feasibility study

  2019cites this paper
• T2‐based MRI Delta‐radiomics improve response prediction in soft‐tissue sarcomas treated by neoadjuvant chemotherapy.

  2019cites this paper
• Machine Learning to Differentiate T2-Weighted Hyperintense Uterine Leiomyomas from Uterine Sarcomas by Utilizing Multiparametric Magnetic Resonance Quantitative Imaging Features.

  2019cites this paper
• Prostate cancer classification with multiparametric MRI transfer learning model

  2019cites this paper
• The value of MR textural analysis in prostate cancer.

  2019cites this paper
• Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer

  2019cites this paper
• Radiomics in Cancer Radiotherapy: a Review

  2019cites this paper
• Genomics and radiomics: Tools to see the unseen to personalize radiation therapy

  2019cites this paper