Literature DB >> 30900614

Magnetic resonance imaging radiomic feature analysis of radiation-induced femoral head changes in prostate cancer radiotherapy.

Hamid Abdollahi1, Seied Rabi Mahdavi2, Isaac Shiri3, Bahram Mofid4, Mohsen Bakhshandeh5, Kazem Rahmani6.   

Abstract

BACKGROUND AND
PURPOSE: As a feasible approach, radiotherapy has a great role in prostate cancer (Pca) management. However, Pca patients have an increased risk of femoral head damages including fractures after radiotherapy. The mechanisms of these complications are unknown and time of manifestations is too long; however, they may be predicted by early imaging. The main purpose of this study was to assess the early changes in femoral heads in Pca patients treated with intensity-modulated radiation therapy (IMRT) using multiparametric magnetic resonance imaging (mpMRI) radiomic feature analysis.
MATERIALS AND METHODS: Thirty Pca patients treated with IMRT were included in the study. All patients underwent two mpMRI pre- and postradiotherapy. Thirty-four robust radiomic features were extracted from T1, T2, and apparent diffusion coefficient (ADC) obtained from diffusion-weighted images. Wilcoxon signed-rank test was performed to assess the significance of the change in the mean T1, T2, and ADC radiomic features postradiotherapy relative to preradiotherapy values. The percentage change values were normalized based on the natural logarithm base ten. Features were also ranked based on their median changes.
RESULTS: Sixty femoral heads were analyzed. All radiomic features have undergone changes. Significant postradiotherapy radiomic feature changes were observed in 20 and 5 T1- and T2-weighted radiomic features, respectively (P < 0.05). ADC features did not vary significantly postradiotherapy. The mean radiation dose received by femoral heads was 40 Gy. No fractures were observed within the follow-up time. Different features were found as high ranked among T1, T2, and ADC images.
CONCLUSION: Early structural change analysis using radiomic features may contribute to predict postradiotherapy fracture in Pca patients. These features can be identified as being potentially important imaging biomarkers for predicting radiotherapy-induced femoral changes.

Entities:  

Keywords:  Feature changes; femoral head; magnetic resonance imaging; prostate cancer; radiomics; radiotherapy

Mesh:

Year:  2019        PMID: 30900614     DOI: 10.4103/jcrt.JCRT_172_18

Source DB:  PubMed          Journal:  J Cancer Res Ther        ISSN: 1998-4138            Impact factor:   1.805


  6 in total

1.  CT imaging markers to improve radiation toxicity prediction in prostate cancer radiotherapy by stacking regression algorithm.

Authors:  Shayan Mostafaei; Hamid Abdollahi; Shiva Kazempour Dehkordi; Isaac Shiri; Abolfazl Razzaghdoust; Seyed Hamid Zoljalali Moghaddam; Afshin Saadipoor; Fereshteh Koosha; Susan Cheraghi; Seied Rabi Mahdavi
Journal:  Radiol Med       Date:  2019-09-24       Impact factor: 3.469

Review 2.  Imaging for Response Assessment in Radiation Oncology: Current and Emerging Techniques.

Authors:  Sonja Stieb; Kendall Kiser; Lisanne van Dijk; Nadia Roxanne Livingstone; Hesham Elhalawani; Baher Elgohari; Brigid McDonald; Juan Ventura; Abdallah Sherif Radwan Mohamed; Clifton David Fuller
Journal:  Hematol Oncol Clin North Am       Date:  2019-10-31       Impact factor: 3.722

3.  Prediction of femoral osteoporosis using machine-learning analysis with radiomics features and abdomen-pelvic CT: A retrospective single center preliminary study.

Authors:  Hyun Kyung Lim; Hong Il Ha; Sun-Young Park; Junhee Han
Journal:  PLoS One       Date:  2021-03-04       Impact factor: 3.240

4.  Radiographic Texture Reproducibility: The Impact of Different Materials, their Arrangement, and Focal Spot Size.

Authors:  Younes Qasempour; Amirsalar Mohammadi; Mostafa Rezaei; Parisa Pouryazadanpanah; Fatemeh Ziaddini; Alma Borbori; Isaac Shiri; Ghasem Hajianfar; Azam Janati; Sareh Ghasemirad; Hamid Abdollahi
Journal:  J Med Signals Sens       Date:  2020-11-11

Review 5.  Radiomics in prostate cancer: an up-to-date review.

Authors:  Matteo Ferro; Ottavio de Cobelli; Gennaro Musi; Francesco Del Giudice; Giuseppe Carrieri; Gian Maria Busetto; Ugo Giovanni Falagario; Alessandro Sciarra; Martina Maggi; Felice Crocetto; Biagio Barone; Vincenzo Francesco Caputo; Michele Marchioni; Giuseppe Lucarelli; Ciro Imbimbo; Francesco Alessandro Mistretta; Stefano Luzzago; Mihai Dorin Vartolomei; Luigi Cormio; Riccardo Autorino; Octavian Sabin Tătaru
Journal:  Ther Adv Urol       Date:  2022-07-04

Review 6.  Radiomics in prostate cancer imaging for a personalized treatment approach - current aspects of methodology and a systematic review on validated studies.

Authors:  Simon K B Spohn; Alisa S Bettermann; Fabian Bamberg; Matthias Benndorf; Michael Mix; Nils H Nicolay; Tobias Fechter; Tobias Hölscher; Radu Grosu; Arturo Chiti; Anca L Grosu; Constantinos Zamboglou
Journal:  Theranostics       Date:  2021-07-06       Impact factor: 11.556

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.