Radiomics Approach to the Detection of Prostate Cancer Using Multiparametric MRI: A Validation Study Using Prostate-Cancer-Tissue-Mimicking Phantoms
Over the last few years, a number of studies have quantified the role of radiomics, dynamic contrast enhancement and standard MRI (T2WI + DWI) in detecting prostate cancer; however, the aim of this paper was to assess the advantage of combining radiomics with other multiparametric magnetic resonance...
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MDPI AG
2022-12-01
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| author | Faisal Alshomrani Basim S. O. Alsaedi Cheng Wei Magdalena Szewczyk-Bieda Stephen Gandy Jennifer Wilson Zhihong Huang Ghulam Nabi |
| author_facet | Faisal Alshomrani Basim S. O. Alsaedi Cheng Wei Magdalena Szewczyk-Bieda Stephen Gandy Jennifer Wilson Zhihong Huang Ghulam Nabi |
| author_sort | Faisal Alshomrani |
| collection | DOAJ |
| description | Over the last few years, a number of studies have quantified the role of radiomics, dynamic contrast enhancement and standard MRI (T2WI + DWI) in detecting prostate cancer; however, the aim of this paper was to assess the advantage of combining radiomics with other multiparametric magnetic resonance imaging (mpMRI) (T2-DWI-DCE) in improving the detection of prostate cancer. This study used 10 prostate-cancer-tissue-mimicking phantoms to obtain preclinical data. We then focused on 46 patients who underwent mpMRI and Transrectal Ultrasound (TRUS) guided biopsy between September 2016 and December 2017. The texture analysis parameters combined with the mpMRI and compared with the histopathology of TRUS biopsy have been assessed statistically by principal component analysis (PCA) and discriminant component analysis (DCA). The prediction model and goodness-of-fit were examined with the Akaike information criterion (AIC) and McFadden pseudo-R-squared. In the PCA, there was a higher separation between cancerous and noncancerous tissue in the preclinical compared with the clinical data. Both AIC and R2 showed an improvement in the model in cancer prediction by adding the radiomics to mpMRI. The discriminant analysis showed an accuracy of cancer prediction of 81% compared with 100% in the pre-clinical phantom data. Combining radiomics with mpMRI showed an improvement in prostate cancer prediction. The ex vivo experiments validated the findings of this study. |
| first_indexed | 2024-03-11T10:06:46Z |
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| id | doaj.art-588c2270dc38456198ababa7b59cf580 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T10:06:46Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-588c2270dc38456198ababa7b59cf5802023-11-16T14:58:54ZengMDPI AGApplied Sciences2076-34172022-12-0113157610.3390/app13010576Radiomics Approach to the Detection of Prostate Cancer Using Multiparametric MRI: A Validation Study Using Prostate-Cancer-Tissue-Mimicking PhantomsFaisal Alshomrani0Basim S. O. Alsaedi1Cheng Wei2Magdalena Szewczyk-Bieda3Stephen Gandy4Jennifer Wilson5Zhihong Huang6Ghulam Nabi7School of Science and Engineering, University of Dundee, Dundee DD1 4HN, UKDepartment of Statistics, University of Tabuk, Tabuk 71491, Saudi ArabiaSchool of Science and Engineering, University of Dundee, Dundee DD1 4HN, UKDepartment of Clinical Radiology, Ninewells Hospital, Dundee DD1 9SY, UKDepartment of Clinical Radiology, Ninewells Hospital, Dundee DD1 9SY, UKDepartment of Clinical Radiology, Ninewells Hospital, Dundee DD1 9SY, UKSchool of Science and Engineering, University of Dundee, Dundee DD1 4HN, UKDivision of Imaging Sciences and Technology, School of Medicine, Ninewells Hospital, University of Dundee, Dundee DD1 9SY, UKOver the last few years, a number of studies have quantified the role of radiomics, dynamic contrast enhancement and standard MRI (T2WI + DWI) in detecting prostate cancer; however, the aim of this paper was to assess the advantage of combining radiomics with other multiparametric magnetic resonance imaging (mpMRI) (T2-DWI-DCE) in improving the detection of prostate cancer. This study used 10 prostate-cancer-tissue-mimicking phantoms to obtain preclinical data. We then focused on 46 patients who underwent mpMRI and Transrectal Ultrasound (TRUS) guided biopsy between September 2016 and December 2017. The texture analysis parameters combined with the mpMRI and compared with the histopathology of TRUS biopsy have been assessed statistically by principal component analysis (PCA) and discriminant component analysis (DCA). The prediction model and goodness-of-fit were examined with the Akaike information criterion (AIC) and McFadden pseudo-R-squared. In the PCA, there was a higher separation between cancerous and noncancerous tissue in the preclinical compared with the clinical data. Both AIC and R2 showed an improvement in the model in cancer prediction by adding the radiomics to mpMRI. The discriminant analysis showed an accuracy of cancer prediction of 81% compared with 100% in the pre-clinical phantom data. Combining radiomics with mpMRI showed an improvement in prostate cancer prediction. The ex vivo experiments validated the findings of this study.https://www.mdpi.com/2076-3417/13/1/576mpMRIprostate cancerradiomicdynamic contrast enhancementtissue-mimicking phantom |
| spellingShingle | Faisal Alshomrani Basim S. O. Alsaedi Cheng Wei Magdalena Szewczyk-Bieda Stephen Gandy Jennifer Wilson Zhihong Huang Ghulam Nabi Radiomics Approach to the Detection of Prostate Cancer Using Multiparametric MRI: A Validation Study Using Prostate-Cancer-Tissue-Mimicking Phantoms Applied Sciences mpMRI prostate cancer radiomic dynamic contrast enhancement tissue-mimicking phantom |
| title | Radiomics Approach to the Detection of Prostate Cancer Using Multiparametric MRI: A Validation Study Using Prostate-Cancer-Tissue-Mimicking Phantoms |
| title_full | Radiomics Approach to the Detection of Prostate Cancer Using Multiparametric MRI: A Validation Study Using Prostate-Cancer-Tissue-Mimicking Phantoms |
| title_fullStr | Radiomics Approach to the Detection of Prostate Cancer Using Multiparametric MRI: A Validation Study Using Prostate-Cancer-Tissue-Mimicking Phantoms |
| title_full_unstemmed | Radiomics Approach to the Detection of Prostate Cancer Using Multiparametric MRI: A Validation Study Using Prostate-Cancer-Tissue-Mimicking Phantoms |
| title_short | Radiomics Approach to the Detection of Prostate Cancer Using Multiparametric MRI: A Validation Study Using Prostate-Cancer-Tissue-Mimicking Phantoms |
| title_sort | radiomics approach to the detection of prostate cancer using multiparametric mri a validation study using prostate cancer tissue mimicking phantoms |
| topic | mpMRI prostate cancer radiomic dynamic contrast enhancement tissue-mimicking phantom |
| url | https://www.mdpi.com/2076-3417/13/1/576 |
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