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Comparative Study
. 2021 Mar 1;94(1119):20201174.
doi: 10.1259/bjr.20201174. Epub 2021 Jan 28.

Prostate cancer GTV delineation with biparametric MRI and 68Ga-PSMA-PET: comparison of expert contours and semi-automated methods

Nathan Hearn  1   2   3 , John Blazak  4 , Philip Vivian  4 , Dinesh Vignarajah  1   2 , Katelyn Cahill  1 , Daisy Atwell  1   2   3 , Jim Lagopoulos  3   5 , Myo Min  1   2   3
Affiliations
Comparative Study

Prostate cancer GTV delineation with biparametric MRI and 68Ga-PSMA-PET: comparison of expert contours and semi-automated methods

Nathan Hearn et al. Br J Radiol. .

Abstract

Objective: The optimal method for delineation of dominant intraprostatic lesions (DIL) for targeted radiotherapy dose escalation is unclear. This study evaluated interobserver and intermodality variability of delineations on biparametric MRI (bpMRI), consisting of T2 weighted (T2W) and diffusion-weighted (DWI) sequences, and 68Ga-PSMA-PET/CT; and compared manually delineated GTV contours with semi-automated segmentations based on quantitative thresholding of intraprostatic apparent diffusion coefficient (ADC) and standardised uptake values (SUV).

Methods: 16 patients who had bpMRI and PSMA-PET scanning performed prior to any treatment were eligible for inclusion. Four observers (two radiation oncologists, two radiologists) manually delineated the DIL on: (1) bpMRI (GTVMRI), (2) PSMA-PET (GTVPSMA) and (3) co-registered bpMRI/PSMA-PET (GTVFused) in separate sittings. Interobserver, intermodality and semi-automated comparisons were evaluated against consensus Simultaneous Truth and Performance Level Estimation (STAPLE) volumes, created from the relevant manual delineations of all observers with equal weighting. Comparisons included the Dice Similarity Coefficient (DSC), mean distance to agreement (MDA) and other metrics.

Results: Interobserver agreement was significantly higher (p < 0.05) for GTVPSMA (DSC: 0.822, MDA: 1.12 mm) and GTVFused (DSC: 0.787, MDA: 1.34 mm) than for GTVMRI (DSC: 0.705, MDA 2.44 mm). Intermodality agreement between GTVMRI and GTVPSMA was low (DSC: 0.440, MDA: 4.64 mm). Agreement between semi-automated volumes and consensus GTV was low for MRI (DSC: 0.370, MDA: 8.16 mm) and significantly higher for PSMA-PET (0.571, MDA: 4.45 mm, p < 0.05).

Conclusion: 68Ga-PSMA-PET appears to improve interobserver consistency of DIL localisation vs bpMRI and may be more viable for simple quantitative delineation approaches; however, more sophisticated approaches to semi-automatic delineation factoring for patient- and disease-related heterogeneity are likely required.

Advances in knowledge: This is the first study to evaluate the interobserver variability of prostate GTV delineations with co-registered bpMRI and 68Ga-PSMA-PET.

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Figures

Figure 1.
Figure 1.
Study eligibility assessment. PET, positron emission tomography; PSMA, prostate specific membrane antigen.
Figure 2.
Figure 2.
Axial image examples of GTV delineation on bpMRI (A-B), PET/CT (C) and Fused bpMRI/PET (D) sessions. Red: STAPLE GTVMRI; green: STAPLE GTVPSMA; cyan: GTVFused. GTV, gross tumour volume; PET, positron emission tomography; STAPLE, Simultaneous Truth and Performance Level Estimation.
Figure 3.
Figure 3.
Boxplot of contour volumes per modality and per observer. Rad: radiologist; RO: radiation oncologist; STAPLE: consensus volume via STAPLE algorithm with equal weighting for all observers. STAPLE, Simultaneous Truth and Performance Level Estimation.
Figure 4.
Figure 4.
Interobserver (a–e) and intermodality variability (f) of GTV contours completed on MRI, PSMA and Fused imaging sets. Boxplots of (a) DSC and (b) JI; Bland–Altman plots with mean and 95% limits of agreement for observer–STAPLE comparisons on (c) MRI, (d) PSMA-PET, and (e) Fused contouring tasks; and (f) intermodality comparison between MRI and PSMA contours for each observer. DSC, Dice Similarity Coefficient; GTV, gross tumour volume; JI, Jaccard Index; PET, positron emission tomography; PSMA, prostate specific membrane antigen; STAPLE, Simultaneous Truth and Performance Level Estimation.
Figure 5.
Figure 5.
Examples of favourable (a–c) and unfavourable (d–f) cases of semi-automated delineations and corresponding STAPLE consensus volumes. (a, b), (d, e) axial views of STAPLE GTVMRI (red) and Auto-GTVMRI (shaded green); (c) axial and (f) sagittal views of STAPLE GTVPSMA (green) and Auto-GTVPSMA (shaded cyan). GTV, gross tumour volume; PSMA, prostate specific membrane antigen; STAPLE, Simultaneous Truth and Performance Level Estimation.
Figure 6.
Figure 6.
Summary boxplot of semi-automated contours generated through whole prostate volume thresholding according to ADC (Auto-GTVMRI), %SUVmax (Auto-GTVPSMA) and their Boolean union and intersections (Auto-GTVuni, Auto-GTVint). (a) DSC, (b) JI, (c) HDmax and (d) MDA calculated against the corresponding manually delineated STAPLE volume (GTVFused used for both union and intersection comparisons). GTV, gross tumour volume; JI, Jaccard Index; PET, positron emission tomography; PSMA, prostate specific membrane antigen; STAPLE, Simultaneous Truth and Performance Level Estimation.
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