Accuracy of gross tumour volume delineation with [68Ga]-PSMA-PET compared to histopathology for high-risk prostate cancer.


Journal

Acta oncologica (Stockholm, Sweden)
ISSN: 1651-226X
Titre abrégé: Acta Oncol
Pays: Sweden
ID NLM: 8709065

Informations de publication

Date de publication:
23 Jun 2024
Historique:
received: 13 01 2024
accepted: 24 04 2024
medline: 24 6 2024
pubmed: 24 6 2024
entrez: 24 6 2024
Statut: epublish

Résumé

The delineation of intraprostatic lesions is vital for correct delivery of focal radiotherapy boost in patients with prostate cancer (PC). Errors in the delineation could translate into reduced tumour control and potentially increase the side effects. The purpose of this study is to compare PET-based delineation methods with histopathology. The study population consisted of 15 patients with confirmed high-risk PC intended for prostatectomy. [68Ga]-PSMA-PET/MR was performed prior to surgery. Prostate lesions identified in histopathology were transferred to the in vivo [68Ga]-PSMA-PET/MR coordinate system. Four radiation oncologists manually delineated intraprostatic lesions based on PET data. Various semi-automatic segmentation methods were employed, including absolute and relative thresholds, adaptive threshold, and multi-level Otsu threshold. The gross tumour volumes (GTVs) delineated by the oncologists showed a moderate level of interobserver agreement with Dice similarity coefficient (DSC) of 0.68. In comparison with histopathology, manual delineations exhibited the highest median DSC and the lowest false discovery rate (FDR) among all approaches. Among semi-automatic approaches, GTVs generated using standardized uptake value (SUV) thresholds above 4 (SUV > 4) demonstrated the highest median DSC (0.41), with 0.51 median lesion coverage ratio, FDR of 0.66 and the 95th percentile of the Hausdorff distance (HD95%) of 8.22 mm. Manual delineations showed a moderate level of interobserver agreement. Compared to histopathology, manual delineations and SUV > 4 exhibited the highest DSC and the lowest HD95% values. The methods that resulted in a high lesion coverage were associated with a large overestimation of the size of the lesions.

Sections du résumé

BACKGROUND BACKGROUND
The delineation of intraprostatic lesions is vital for correct delivery of focal radiotherapy boost in patients with prostate cancer (PC). Errors in the delineation could translate into reduced tumour control and potentially increase the side effects. The purpose of this study is to compare PET-based delineation methods with histopathology.
MATERIALS AND METHODS METHODS
The study population consisted of 15 patients with confirmed high-risk PC intended for prostatectomy. [68Ga]-PSMA-PET/MR was performed prior to surgery. Prostate lesions identified in histopathology were transferred to the in vivo [68Ga]-PSMA-PET/MR coordinate system. Four radiation oncologists manually delineated intraprostatic lesions based on PET data. Various semi-automatic segmentation methods were employed, including absolute and relative thresholds, adaptive threshold, and multi-level Otsu threshold.
RESULTS RESULTS
The gross tumour volumes (GTVs) delineated by the oncologists showed a moderate level of interobserver agreement with Dice similarity coefficient (DSC) of 0.68. In comparison with histopathology, manual delineations exhibited the highest median DSC and the lowest false discovery rate (FDR) among all approaches. Among semi-automatic approaches, GTVs generated using standardized uptake value (SUV) thresholds above 4 (SUV > 4) demonstrated the highest median DSC (0.41), with 0.51 median lesion coverage ratio, FDR of 0.66 and the 95th percentile of the Hausdorff distance (HD95%) of 8.22 mm.
INTERPRETATION CONCLUSIONS
Manual delineations showed a moderate level of interobserver agreement. Compared to histopathology, manual delineations and SUV > 4 exhibited the highest DSC and the lowest HD95% values. The methods that resulted in a high lesion coverage were associated with a large overestimation of the size of the lesions.

Identifiants

pubmed: 38912830
doi: 10.2340/1651-226X.2024.39041
doi:

Substances chimiques

Gallium Radioisotopes 0
Gallium Isotopes 0
gallium 68 PSMA-11 0
Radiopharmaceuticals 0
Oligopeptides 0
Edetic Acid 9G34HU7RV0

Types de publication

Journal Article Comparative Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

503-510

Auteurs

Maryam Zarei (M)

Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden. maryam.zarei@umu.se.

Elin Wallsten (E)

Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden.

Josefine Grefve (J)

Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden.

Karin Söderkvist (K)

Department of Diagnostics and Intervention, Oncology, Umeå University, Umeå, Sweden.

Adalsteinn Gunnlaugsson (A)

Skane University Hospital, Department of Hematology, Oncology and Radiation Physics, Lund, Sweden.

Kristina Sandgren (K)

Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden.

Joakim Jonsson (J)

Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden.

Angsana Keeratijarut Lindberg (A)

Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden.

Erik Nilsson (E)

Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden.

Anders Bergh (A)

Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden.

Björn Zackrisson (B)

Department of Diagnostics and Intervention, Oncology, Umeå University, Umeå, Sweden.

Mathieu Moreau (M)

Skane University Hospital, Department of Hematology, Oncology and Radiation Physics, Lund, Sweden.

Camilla Thellenberg Karlsson (C)

Department of Diagnostics and Intervention, Oncology, Umeå University, Umeå, Sweden.

Lars E Olsson (LE)

Department of Translational Medicine, Medical Radiation Physics, Lund University, Malmö, Sweden.

Anders Widmark (A)

Department of Diagnostics and Intervention, Oncology, Umeå University, Umeå, Sweden.

Katrine Riklund (K)

Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, Umeå, Sweden.

Lennart Blomqvist (L)

Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden; Department of Molecular Medicine and Surgery, Karolinska Institutet, Solna, Sweden.

Vibeke Berg Loegager (V)

Department of Radiology, Copenhagen University Hospital in Herlev, Herlev, Denmark.

Jan Axelsson (J)

Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden.

Sara N Strandberg (SN)

Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, Umeå, Sweden.

Tufve Nyholm (T)

Department of Diagnostics and Intervention, Biomedical engineering and Radiation Physics, Umeå University, Umeå, Sweden.

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Classifications MeSH