First-in-human validation of a DROP-IN β-probe for robotic radioguided surgery: defining optimal signal-to-background discrimination algorithm

Francesco Collamati; Silvio Morganti; Matthias N van Oosterom; Lorenzo Campana; Francesco Ceci; Stefano Luzzago; Carlo Mancini-Terracciano; Riccardo Mirabelli; Gennaro Musi; Francesca Nicolanti; Ilaria Orsi; Fijs W B van Leeuwen; Riccardo Faccini

doi:10.1007/s00259-024-06653-6

First-in-human validation of a DROP-IN β-probe for robotic radioguided surgery: defining optimal signal-to-background discrimination algorithm

Eur J Nucl Med Mol Imaging. 2024 Feb 20. doi: 10.1007/s00259-024-06653-6. Online ahead of print.

Authors

Francesco Collamati¹, Silvio Morganti¹, Matthias N van Oosterom², Lorenzo Campana^{1

3}, Francesco Ceci^{4

5}, Stefano Luzzago^{5

6}, Carlo Mancini-Terracciano^{1

7}, Riccardo Mirabelli^{8

9}, Gennaro Musi^{5

6}, Francesca Nicolanti^{1

7}, Ilaria Orsi^{1

7}, Fijs W B van Leeuwen², Riccardo Faccini^{1

7}

Affiliations

¹ National Institute of Nuclear Physics (INFN), Section of Rome, Rome, Italy.
² Interventional Molecular Imaging Laboratory, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
³ Department of Scienze di Base e Applicate per l'Ingegneria (SBAI), Sapienza University of Rome, Rome, Italy.
⁴ Division of Nuclear Medicine, IEO, European Institute of Oncology IRCCS, Milan, Italy.
⁵ Department of Oncology and Hematology-Oncology, University of Milan, Milan, Italy.
⁶ Department of Urology, IEO European Institute of Oncology, IRCCS, Milan, Italy.
⁷ Department of Physics, Sapienza University of Rome, Rome, Italy.
⁸ National Institute of Nuclear Physics (INFN), Section of Rome, Rome, Italy. riccardo.mirabelli@uniroma1.it.
⁹ Department of Scienze di Base e Applicate per l'Ingegneria (SBAI), Sapienza University of Rome, Rome, Italy. riccardo.mirabelli@uniroma1.it.

PMID: 38376805
DOI: 10.1007/s00259-024-06653-6

Abstract

Purpose: In radioguided surgery (RGS), radiopharmaceuticals are used to generate preoperative roadmaps (e.g., PET/CT) and to facilitate intraoperative tracing of tracer avid lesions. Within RGS, there is a push toward the use of receptor-targeted radiopharmaceuticals, a trend that also has to align with the surgical move toward minimal invasive robotic surgery. Building on our initial ex vivo evaluation, this study investigates the clinical translation of a DROP-IN β probe in robotic PSMA-guided prostate cancer surgery.

Methods: A clinical-grade DROP-IN β probe was developed to support the detection of PET radioisotopes (e.g., ⁶⁸ Ga). The prototype was evaluated in 7 primary prostate cancer patients, having at least 1 lymph node metastases visible on PSMA-PET. Patients were scheduled for radical prostatectomy combined with extended pelvic lymph node dissection. At the beginning of surgery, patients were injected with 1.1 MBq/kg of [⁶⁸Ga]Ga-PSMA. The β probe was used to trace PSMA-expressing lymph nodes in vivo. To support intraoperative decision-making, a statistical software algorithm was defined and optimized on this dataset to help the surgeon discriminate between probe signals coming from tumors and healthy tissue.

Results: The DROP-IN β probe helped provide the surgeon with autonomous and highly maneuverable tracer detection. A total of 66 samples (i.e., lymph node specimens) were analyzed in vivo, of which 31 (47%) were found to be malignant. After optimization of the signal cutoff algorithm, we found a probe detection rate of 78% of the PSMA-PET-positive samples, a sensitivity of 76%, and a specificity of 93%, as compared to pathologic evaluation.

Conclusion: This study shows the first-in-human use of a DROP-IN β probe, supporting the integration of β radio guidance and robotic surgery. The achieved competitive sensitivity and specificity help open the world of robotic RGS to a whole new range of radiopharmaceuticals.

Keywords: Image-guided surgery; Molecular imaging; PET; Prostate cancer; Robotic surgery; β radioguided surgery.

Abstract

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