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We have been able to convert the sensor\u2019s numeric readout to tomographic images, so-called robotic-SPECT (\n                      <jats:sub>Robo<\/jats:sub>\n                      SPECT) and investigate how this is impacted by radiopharmaceutical avidities and drop-in scan metrics.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      The gamma sensor readout was registered with its 3D position and orientation, allowing a custom reconstruction algorithm to generate\n                      <jats:sub>Robo<\/jats:sub>\n                      SPECT images. Evaluations occurred in 21 patients; 10 sentinel node procedures (SN; primary prostate cancer) and 11 PSMA-radioguided surgery (recurrent prostate cancer).\n                      <jats:sub>Robo<\/jats:sub>\n                      SPECT findings were related to respective pre- and intra-operative controls, including preoperative PSMA-PET\/CT and\/or SPECT\/CT images and fluorescence detection (SN only).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      <jats:sub>Robo<\/jats:sub>\n                      SPECT proved to be safe and applicable in a range of conditions. In the SN-group, 26 SN-SPECT\/CT lesions were successfully identified with SN-\n                      <jats:sub>Robo<\/jats:sub>\n                      SPECT (100%); 3 were tumor positive (sensitivity 100%). Only 73% of SNs were surgically visible with fluorescence imaging. For the PSMA guided group, the 14 lesions identified on PSMA-PET\/CT were all visualized with PSMA-\n                      <jats:sub>Robo<\/jats:sub>\n                      SPECT (100%); 18 specimens were tumor positive (sensitivity 78% for both PSMA-PET\/CT and PSMA-\n                      <jats:sub>Robo<\/jats:sub>\n                      SPECT). Preoperative PSMA-SPECT\/CT only identified 4 PSMA-lesions (29%). No false positives were seen for\n                      <jats:sub>robo<\/jats:sub>\n                      SPECT and all final resection margins were clean. At 6-months 0% of the SN-patients and 20% of PSMA-patients showed biochemical recurrence.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      <jats:sub>Robo<\/jats:sub>\n                      SPECT provides 3D context that extends the utility of drop-in gamma tracing and assists the alignment between pre- and intra-operative target perception. Here SN-\n                      <jats:sub>Robo<\/jats:sub>\n                      SPECT clearly outperformed fluorescence SN imaging and PSMA-\n                      <jats:sub>Robo<\/jats:sub>\n                      SPECT outperformed preoperative PSMA-SPECT\/CT imaging.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00259-026-07987-z","type":"journal-article","created":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T06:14:30Z","timestamp":1782886470000},"page":"6858-6869","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Redefining robotic image-guidance \u2013 tomographic visualization of lesions during prostate cancer surgery via gantry-free robotic SPECT"],"prefix":"10.1007","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3328-384X","authenticated-orcid":false,"given":"A. 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