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EnglishIn the last decade, multiparametric magnetic resonance imaging (mpMRI) has been expanding its role in prostate cancer detection and characterization. In this work, 19 patients with clinically significant peripheral zone (PZ) tumours were studied. Tumour masks annotated on the whole-mount histology sections were mapped on T2-weighted (T2w) and diffusion-weighted (DW) sequences. Gray-level histograms of tumoral and normal tissue were compared using six first-order texture features. Multivariate analysis of variance (MANOVA) was used to compare group means. Mean intensity signal of ADC showed the highest showed the highest area under the receiver operator characteristics curve (AUC) equal to 0.85. MANOVA analysis revealed that ADC features allows a better separation between normal and cancerous tissue with respect to T2w features (ADC: P = 0.0003, AUC = 0.86; T2w: P = 0.03, AUC = 0.74). MANOVA proved that the combination of T2-weighted and apparent diffusion coefficient (ADC) map features increased the AUC to 0.88. Histogram-based features extracted from invivo mpMRI can help discriminating significant PZ PCa.
Comparison of Histogram-based Textural Features between Cancerous and Normal Prostatic Tissue in Multiparametric Magnetic Resonance Images / De Santi, B.; Salvi, M.; Giannini, V.; Meiburger, K. M.; Marzola, F.; Russo, F.; Bosco, M.; Molinari, F.. - 2020-(2020), pp. 1671-1674. ((Intervento presentato al convegno 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 tenutosi a can nel 2020 [10.1109/EMBC44109.2020.9176307].
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| Titolo: | Comparison of Histogram-based Textural Features between Cancerous and Normal Prostatic Tissue in Multiparametric Magnetic Resonance Images | |
| Autori: | ||
| Data di pubblicazione: | 2020 | |
| Serie: | ||
| Abstract: | In the last decade, multiparametric magnetic resonance imaging (mpMRI) has been expanding its rol...e in prostate cancer detection and characterization. In this work, 19 patients with clinically significant peripheral zone (PZ) tumours were studied. Tumour masks annotated on the whole-mount histology sections were mapped on T2-weighted (T2w) and diffusion-weighted (DW) sequences. Gray-level histograms of tumoral and normal tissue were compared using six first-order texture features. Multivariate analysis of variance (MANOVA) was used to compare group means. Mean intensity signal of ADC showed the highest showed the highest area under the receiver operator characteristics curve (AUC) equal to 0.85. MANOVA analysis revealed that ADC features allows a better separation between normal and cancerous tissue with respect to T2w features (ADC: P = 0.0003, AUC = 0.86; T2w: P = 0.03, AUC = 0.74). MANOVA proved that the combination of T2-weighted and apparent diffusion coefficient (ADC) map features increased the AUC to 0.88. Histogram-based features extracted from invivo mpMRI can help discriminating significant PZ PCa. | |
| ISBN: | 978-1-7281-1990-8 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| 2020_EMBC_MRItexture.pdf | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia | |
| MRItexture.pdf | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
http://hdl.handle.net/11583/2860148
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