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Back-table specimen scanning using gantry-free hybrid hSPECT/LiDAR imaging: a feasibility study during PSMA-radioguided surgery

  • Introduction Prostate-specific membrane antigen (PSMA) targeted precision surgery is becoming increasingly popular. However, the relatively low levels of PSMA-receptor expression and background signal can hinder in vivo lesion detection and margin evaluation. Back-table imaging (ex vivo) potentially provides a means to confirm surgical accuracy. For 99mTc-PSMA-radioguided surgery, an innovative gantry-free hybrid imaging technique has recently been proposed, namely handheld single-photon emission computed tomography (hSPECT) combined with light detection and ranging (LiDAR). This study aimed to assess the feasibility and performance of hSPECT/LiDAR in analyzing tissue specimens excised after robotic 99mTc-PSMA-radioguided surgery. Methods We included samples from 5 prostate cancer patients undergoing primary or salvage robot-assisted resection of 99mTc-PSMA-I&S avid lesions that were identified using a drop-in gamma probe. 12 samples (1 prostatic tissue, 1 local recurrence tissue,Introduction Prostate-specific membrane antigen (PSMA) targeted precision surgery is becoming increasingly popular. However, the relatively low levels of PSMA-receptor expression and background signal can hinder in vivo lesion detection and margin evaluation. Back-table imaging (ex vivo) potentially provides a means to confirm surgical accuracy. For 99mTc-PSMA-radioguided surgery, an innovative gantry-free hybrid imaging technique has recently been proposed, namely handheld single-photon emission computed tomography (hSPECT) combined with light detection and ranging (LiDAR). This study aimed to assess the feasibility and performance of hSPECT/LiDAR in analyzing tissue specimens excised after robotic 99mTc-PSMA-radioguided surgery. Methods We included samples from 5 prostate cancer patients undergoing primary or salvage robot-assisted resection of 99mTc-PSMA-I&S avid lesions that were identified using a drop-in gamma probe. 12 samples (1 prostatic tissue, 1 local recurrence tissue, 10 lymph nodes) were analyzed ex vivo using a custom-built specimen tray, including an optical reference tracker for scan registration. LiDAR was used to acquire a surface scan of the specimens, and the 3D OBJ image output was fused with the 3D DICOM of a hSPECT obtained using a handheld gamma camera and DeclipseSPECT tracking system. Results hSPECT/LiDAR imaging provided accurate representation of the 99mTc-PSMA-I&S uptake within the specimens. In 8 samples, it helped to confirm a true positive lesion. In the remaining 4 samples, non-visualization aligned with negative histopathology (true negative). A strong correlation was found between PSMA-hSPECT/LiDAR and PSMA-PET/CT (p < 0.05), but no correlation could be established with PSMA-SPECT/CT (p = 0.515). The count rates fount in the scan correlated to tumor size (p = 0.016) and were not influenced by the overall specimen’s size (p = 0.558). Conclusion We present the technical feasibility of a new 3D hybrid modality (hSPECT/LiDAR) that allows back-table assessment of surgical specimens from the already well validated robotic 99mTc-PSMA-radioguided surgery workflow.show moreshow less

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Metadaten
Author:Giusi Pisano, Matthias N. van Oosterom, Vera A. Ottens, Anne-Claire Berrens, Leon J. Slof, Berkay A. Çakal, Daphne D. D. Rietbergen, Henk G. van der Poel, Pim J. van Leeuwen, Fijs W. B. van Leeuwen
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/124970
ISSN:0930-2794OPAC
ISSN:1432-2218OPAC
Parent Title (English):Surgical Endoscopy
Publisher:Springer Science and Business Media LLC
Type:Article
Language:English
Year of first Publication:2025
Publishing Institution:Universität Augsburg
Release Date:2025/09/10
DOI:https://doi.org/10.1007/s00464-025-12081-w
Institutes:Medizinische Fakultät
Medizinische Fakultät / Universitätsklinikum
Medizinische Fakultät / Lehrstuhl für Diagnostische und Interventionelle Neuroradiologie
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Latest Publications (not yet published in print):Aktuelle Publikationen (noch nicht gedruckt erschienen)
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)