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. 2023 Dec 14;11(12):3309.
doi: 10.3390/biomedicines11123309.

Inter-Rater Variability of Prostate Lesion Segmentation on Multiparametric Prostate MRI

Affiliations

Inter-Rater Variability of Prostate Lesion Segmentation on Multiparametric Prostate MRI

Thibaut Jeganathan et al. Biomedicines. .

Abstract

Introduction: External radiotherapy is a major treatment for localized prostate cancer (PCa). Dose escalation to the whole prostate gland increases biochemical relapse-free survival but also acute and late toxicities. Dose escalation to the dominant index lesion (DIL) only is of growing interest. It requires a robust delineation of the DIL. In this context, we aimed to evaluate the inter-observer variability of DIL delineation.

Material and methods: Two junior radiologists and a senior radiation oncologist delineated DILs on 64 mpMRIs of patients with histologically confirmed PCa. For each mpMRI and each reader, eight individual DIL segmentations were delineated. These delineations were blindly performed from one another and resulted from the individual analysis of the T2, apparent diffusion coefficient (ADC), b2000, and dynamic contrast enhanced (DCE) sequences, as well as the analysis of combined sequences (T2ADC, T2ADCb2000, T2ADCDCE, and T2ADCb2000DCE). Delineation variability was assessed using the DICE coefficient, Jaccard index, Hausdorff distance measure, and mean distance to agreement.

Results: T2, ADC, T2ADC, b2000, T2 + ADC + b2000, T2 + ADC + DCE, and T2 + ADC + b2000 + DCE sequences obtained DICE coefficients of 0.51, 0.50, 0.54, 0.52, 0.54, 0.55, 0.53, respectively, which are significantly higher than the perfusion sequence alone (0.35, p < 0.001). The analysis of other similarity metrics lead to similar results. The tumor volume and PI-RADS classification were positively correlated with the DICE scores.

Conclusion: Our study showed that the contours of prostatic lesions were more reproducible on certain sequences but confirmed the great variability of prostatic contours with a maximum DICE coefficient calculated at 0.55 (joint analysis of T2, ADC, and perfusion sequences).

Keywords: multiparametric MRI; prostate cancer; segmentation; variability.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Mean of tumor volume delineated for each reader and each sequence. Abbreviations: ADC: Apparent Diffusion Coefficient, DCE: Dynamic Contrast Enhanced.
Figure 2
Figure 2
Inter-reader variability for the definition of the index lesion for each sequence (DICE). Abbreviations: DSC: DICE Similarity Coefficient, ADC: Apparent Diffusion Coefficient, DCE: Dynamic Contrast Enhanced.
Figure 3
Figure 3
Example of tumor delineation on T2 sequence with low and high reproducibility ((a) mean of DICE: 0.31; (b) mean of DICE: 0.75).

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