{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T18:55:11Z","timestamp":1781636111655,"version":"3.54.5"},"reference-count":10,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T00:00:00Z","timestamp":1771286400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T00:00:00Z","timestamp":1771286400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neurosurg Rev"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Real-time intra-operative brain tumour tissue analysis can reduce turnaround times and enable repeated sampling, enhancing diagnostic accuracy and guiding resection. We investigated the use of an ultra-fast confocal microscopy scanner (Histolog\u00ae, SamanTree Medical SA) for real-time brain tumour tissue diagnosis. This study aims to demonstrate Histolog\u00ae\u2019s diagnostic accuracy in a cohort of brain or spinal cord tumour patients. A single-group, observational study included adult patients undergoing tissue biopsies or tumour debulking surgery. Multiple, freshly excised tissue samples were stained and imaged within 60 seconds using Histolog\u00ae alongside standard diagnostic methods. A Consultant Neuropathologist performed a blinded concordance analysis. Of 47 specimens, 94% produced interpretable images during surgery. Histolog\u00ae images enabled real-time tumour cell identification in all specimens and matched gold standard diagnoses in 68% of cases. Histolog\u00ae demonstrated rapid intraoperative imaging with diagnostic performance for tumour presence that was comparable to existing intraoperative methods in this small cohort, while exact histological concordance was lower (68%). Future studies will explore real-time margin zone analysis and machine learning for automatic diagnosis.<\/jats:p>","DOI":"10.1007\/s10143-025-04083-y","type":"journal-article","created":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T00:41:58Z","timestamp":1771288918000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The feasibility and accuracy of real-time intra-operative confocal tissue diagnosis in brain and spine cancer surgery"],"prefix":"10.1007","volume":"49","author":[{"given":"William S.","family":"Bolton","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oluwaseyi","family":"Adebola","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Piravin K.","family":"Ramakrishnan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dharsshini","family":"Reveendran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vassili","family":"Crispi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Digby","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rohitashwa","family":"Sinha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arundhati","family":"Chakrabarty","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2609-9876","authenticated-orcid":false,"given":"Ryan K.","family":"Mathew","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,17]]},"reference":[{"issue":"8","key":"4083_CR1","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1093\/neuonc\/noab106","volume":"23","author":"DN Louis","year":"2021","unstructured":"Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D et al (2021) The 2021 WHO classification of tumors of the central nervous system: a summary. 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BJU Int 127(6):676\u2013686","journal-title":"BJU Int"},{"key":"4083_CR6","volume":"4","author":"AH Nguyen","year":"2023","unstructured":"Nguyen AH, Algoe M, Nap M, van Kemenade FJ (2023) Selection of FFPE blocks with confocal microscope to reduce routine workload in pathology department. Int Clin Img Med Rew 4:1150","journal-title":"Int Clin Img Med Rew"},{"issue":"4","key":"4083_CR7","doi-asserted-by":"publisher","first-page":"686","DOI":"10.1038\/s41416-020-01122-x","volume":"124","author":"A Echle","year":"2021","unstructured":"Echle A, Rindtorff N, Brinker T, Luedde T, Pearson A, Kather J (2021) Deep learning in cancer pathology: a new generation of clinical biomarkers. 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In line with UK Health Research Authority (HRA) guidance, the work was judged to assess and optimise an existing service without altering patient care pathways or randomising patients to different interventions and therefore did not require NHS Research Ethics Committee review. All patients had already provided written consent for the use of surplus resected tissue for research and education.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical considerations"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Clinical trial number"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}}],"article-number":"228"}}