Quantification of Multi-Parametric Magnetic Resonance Imaging Based on Radiomics Analysis for Differentiation of Benign and Malignant Lesions of Prostate

سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 105

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شناسه ملی سند علمی:

JR_JBPE-13-3_005

تاریخ نمایه سازی: 30 دی 1402

چکیده مقاله:

Background: The most common cancer (non-cutaneous) malignancy among men is prostate cancer. Management of prostate cancer, including staging and treatment, playing an important role in decreasing mortality rates. Among all current diagnostic tools, multiparametric MRI (mp-MRI) has shown high potential in localizing and staging prostate cancer. Quantification of mp-MRI helps to decrease the dependency of diagnosis on readers’ opinions.Objective: The aim of this research is to set a method based on quantification of mp-MRI images for discrimination between benign and malignant prostatic lesions with fusion-guided MR imaging/transrectal ultrasonography biopsy as a pathology validation reference.Material and Methods: It is an analytical research that ۲۷ patients underwent the mp-MRI examination, including T۱- and T۲- weighted and diffusion weighted imaging (DWI). Quantification was done by calculating radiomic features from mp-MRI images. Receiver-operating-characteristic curve was done for each feature to evaluate the discriminatory capacity and linear discriminant analysis (LDA) and leave-one-out cross-validation for feature filtering to estimate the sensitivity, specificity and accuracy of the benign and malignant lesion differentiation process is used.Results: An accuracy, sensitivity and specificity of ۹۲.۶%, ۹۵.۲% and ۸۳.۳%, respectively, were achieved from a subset of radiomics features obtained from T۲-weighted images and apparent diffusion coefficient (ADC) maps for distinguishing benign and malignant prostate lesions. Conclusion: Quantification of mp-MRI (T۲-weighted images and ADC-maps) based on radiomics feature has potential to distinguish benign with appropriate accuracy from malignant prostate lesions. This technique is helpful in preventing needless biopsies in patients and provides an assisted diagnosis for classifications of prostate lesions.

کلیدواژه ها:

Prostatic Neoplasms ، Multiparametric Magnetic Resonance Imaging ، Radiomics Fatures ، Quantification analysis

نویسندگان

Soheila Koopaei

Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Institute for Advanced Medical Technologies, Imam Hospital, Tehran, Iran

Anahita Fathi Kazerooni

Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Science Tehran, Iran

Mahyar Ghafoori

Department of Radiology, Hazrat Rasoul Akram University Hospital, Tehran, Iran

Mohammadreza Alviri

Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Science Tehran, Iran

Fakhereh Pashaei

Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Institute for Advanced Medical Technologies, Imam Hospital, Tehran, Iran

Hamidreza Saligheh Rad

Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Institute for Advanced Medical Technologies, Imam Hospital, Tehran, Iran

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  • Ferlay J, Shin HR, Bray F, Forman D, Mathers C, ...
  • Verma S, Rajesh A. A clinically relevant approach to imaging ...
  • Schröder FH. Screening for prostate cancer: current status of ERSPC ...
  • Thompson IM, Ankerst DP, Chi C, Lucia MS, et al. ...
  • Gretzer MB, Partin AW. PSA markers in prostate cancer detection. ...
  • DeSantis C, Ma J, Bryan L, Jemal A. Breast cancer ...
  • Epstein JI, Feng Z, Trock BJ, Pierorazio PM. Upgrading and ...
  • Pokorny MR, De Rooij M, Duncan E, Schröder FH. Prospective ...
  • Phillips R. Stem cells repopulate tumours. Nat Rev Urol. ۲۰۱۵;۱۲(۲):۶۳. ...
  • Bjurlin MA, Carter HB, Schellhammer P, Cookson MS, et al. ...
  • Sanders A, Buchan N. Infection-related hospital admissions after transrectal biopsy ...
  • Utrera NM, Alvarez MB, Polo JM, et al. Infectious complications ...
  • Hoeks CM, Barentsz JO, Hambrock T, Yakar D, Somford DM. ...
  • Panebianco V, Barchetti F, Sciarra A, Ciardi A, et al. ...
  • Weinreb JC, Barentsz JO, Choyke PL, et al. PI-RADS prostate ...
  • Desouza NM, Reinsberg SA, Scurr ED, Brewster JM, Payne GS. ...
  • Elbuluk O, Turkbey B, Choyke P. Prostate Imaging, InInterventional Urology. ...
  • Haider MA, Van Der Kwast TH, Tanguay J, et al. ...
  • Fathi Kazerooni A, Nabil M, Haghighat Khah H, Alviri M, ...
  • You MW, Kim MH, Kim JK, Cho KS. The characteristics ...
  • Abdi H, Zargar H, Goldenberg SL, Walshe T, et al. ...
  • Javali TD, Dwivedi DK, Kumar R, Jagannathan NR, et al. ...
  • Bae H, Yoshida S, Matsuoka Y, Nakajima H, et al. ...
  • Fusco R, Sansone M, Petrillo M, Setola SV, et al. ...
  • Hoang Dinh A, Melodelima C, Souchon R, et al. Quantitative ...
  • Hauth E, Halbritter D, Jaeger H, Hohmuth H, Beer M. ...
  • Khalvati F, Wong A, Haider MA. Automated prostate cancer detection ...
  • نمایش کامل مراجع