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Ultrasound-guided targeted biopsies of CT-based radiomic tumour habitats: technical development and initial experience in metastatic ovarian cancer.

Accepted version
Peer-reviewed

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Type

Article

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Authors

Beer, Lucian 
Martin-Gonzalez, Paula 
Delgado-Ortet, Maria 
Reinius, Marika 
Rundo, Leonardo 

Abstract

PURPOSE: To develop a precision tissue sampling technique that uses computed tomography (CT)-based radiomic tumour habitats for ultrasound (US)-guided targeted biopsies that can be integrated in the clinical workflow of patients with high-grade serous ovarian cancer (HGSOC). METHODS: Six patients with suspected HGSOC scheduled for US-guided biopsy before starting neoadjuvant chemotherapy were included in this prospective study from September 2019 to February 2020. The tumour segmentation was performed manually on the pre-biopsy contrast-enhanced CT scan. Spatial radiomic maps were used to identify tumour areas with similar or distinct radiomic patterns, and tumour habitats were identified using the Gaussian mixture modelling. CT images with superimposed habitat maps were co-registered with US images by means of a landmark-based rigid registration method for US-guided targeted biopsies. The dice similarity coefficient (DSC) was used to assess the tumour-specific CT/US fusion accuracy. RESULTS: We successfully co-registered CT-based radiomic tumour habitats with US images in all patients. The median time between CT scan and biopsy was 21 days (range 7-30 days). The median DSC for tumour-specific CT/US fusion accuracy was 0.53 (range 0.79 to 0.37). The CT/US fusion accuracy was high for the larger pelvic tumours (DSC: 0.76-0.79) while it was lower for the smaller omental metastases (DSC: 0.37-0.53). CONCLUSION: We developed a precision tissue sampling technique that uses radiomic habitats to guide in vivo biopsies using CT/US fusion and that can be seamlessly integrated in the clinical routine for patients with HGSOC. KEY POINTS: • We developed a prevision tissue sampling technique that co-registers CT-based radiomics-based tumour habitats with US images. • The CT/US fusion accuracy was high for the larger pelvic tumours (DSC: 0.76-0.79) while it was lower for the smaller omental metastases (DSC: 0.37-0.53).

Description

Keywords

Computed tomography, Ovarian neoplasms, Radiomics, Ecosystem, Female, Humans, Ovarian Neoplasms, Prospective Studies, Tomography, X-Ray Computed, Ultrasonography, Interventional

Journal Title

Eur Radiol

Conference Name

Journal ISSN

0938-7994
1432-1084

Volume Title

31

Publisher

Springer Science and Business Media LLC

Rights

All rights reserved
Sponsorship
Cancer Research UK (C14303/A17197)
Mark Foundation for Cancer Research US Ltd (Unknown)
Cancer Research UK (C96/A25177)
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (766030)
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 766030, the Cancer Research UK Cambridge Institute with core grant C14303/A17197, the Mark Foundation for Cancer Research and Cancer Research UK Cambridge Centre [C9685/A25177].