| Title |
Diffmap: Enhancement difference map for peripheral prostate zone cancer localization based on functional data analysis and dynamic contrast enhancement MRI |
| Authors |
Surkant, Roman ; Markevičiūtė, Jurgita ; Naruševičiūtė, Ieva ; Trakymas, Mantas ; Treigys, Povilas ; Bernatavičienė, Jolita |
| DOI |
10.3390/electronics15030507 |
| Full Text |
|
| Is Part of |
Electronics.. Basel : MDPI. 2026, vol. 15, iss. 3, art. no. 507, p. [1-15].. eISSN 2079-9292 |
| Keywords [eng] |
cancer localization ; dynamic contrast enhancement ; functional data analysis ; image processing ; image subtraction ; MRI ; peripheral zone ; prostate cancer |
| Abstract [eng] |
Dynamic contrast-enhancement (DCE) modality of MRI is typically considered secondary in prostate cancer (PCa) diagnostics, due to the common interpretation that its diagnostic power is lower than that of other modalities like T2-weighted (T2W) or diffusion-weighted imaging (DWI). To challenge this paradigm, this study introduces a novel concept of a difference map, which relies exclusively on DCE-MRI for the localization of peripheral zone prostate cancer using functional data analysis-based (FDA) signal processing. The proposed workflow uses discrete voxel-level DCE time–signal curves that are transformed into a continuous functional form. First-order derivatives are then used to determine patient-specific time points of greatest enhancement change that adapt to the intrinsic characteristics of each patient, producing diffmaps that highlight regions with pronounced enhancement dynamics, indicative of malignancy. A subsequent normalization step accounts for inter-patient variability, enabling consistent interpretation across subjects and probabilistic PCa localization. The approach is validated on a curated dataset of 20 patients. Evaluation of eight workflow variants is performed using weighted log loss, the best variant achieving a mean log loss of 0.578. This study demonstrates the feasibility and effectiveness of a single-modality, automated, and interpretable approach for peripheral prostate cancer localization based solely on DCE-MRI. |
| Published |
Basel : MDPI |
| Type |
Journal article |
| Language |
English |
| Publication date |
2026 |
| CC license |
|
