@article {Janssen2020a, title = {Navigated tissue characterization during skin cancer surgery}, journal = {Int J Comput Assist Radiol Surg}, year = {In Press}, month = {05/2020}, abstract = {

Purpose:\ Basal cell carcinoma (BCC) is the most commonly diagnosed skin cancer and is treated by surgical resection. Incomplete tumor removal requires surgical revision, leading to significant healthcare costs and impaired cosmesis. We investigated the clinical feasibility of a surgical navigation system for BCC surgery, based on molecular tissue characterization using rapid evaporative ionization mass spectrometry (REIMS).

Methods:\ REIMS enables direct tissue characterization by analysis of cell-specific molecules present within surgical smoke, produced during electrocautery tissue resection. A tissue characterization model was built by acquiring REIMS spectra of BCC, healthy skin and fat from ex vivo skin cancer specimens. This model was used for tissue characterization during navigated skin cancer surgery. Navigation was enabled by optical tracking and real-time visualization of the cautery relative to a contoured resection volume. The surgical smoke was aspirated into a mass spectrometer and directly analyzed with REIMS. Classified BCC was annotated at the real-time position of the cautery. Feasibility of the navigation system, and tissue classification accuracy for ex vivo and intraoperative surgery were evaluated.

Results:\ Fifty-four fresh excision specimens were used to build the ex vivo model of BCC, normal skin and fat, with 92\% accuracy. While 3 surgeries were successfully navigated without breach of sterility, the intraoperative performance of the ex vivo model was low (\< 50\%). Hypotheses are: (1) the model was trained on heterogeneous mass spectra that did not originate from a single tissue type, (2) during surgery mixed tissue types were resected and thus presented to the model, and (3) the mass spectra were not validated by pathology.

Conclusion:\ REIMS-navigated skin cancer surgery has the potential to detect and localize remaining tumor intraoperatively. Future work will be focused on improving our model by using a precise pencil cautery tip for burning localized tissue types, and having pathology-validated mass spectra.

}, keywords = {Intraoperative surgical resection margin assessment, Model-guided surgery, Optical navigation, Real-time tissue characterization}, doi = {10.1007/s11548-020-02200-4}, url = {https://doi.org/10.1007/s11548-020-02200-4}, author = {Natasja Janssen and Martin Kaufmann and Alice Santilli and Amoon Jamzad and Vanderbeck Kaitlin and Kevin Ren and Tamas Ungi and Parvin Mousavi and John Rudan and Doug McKay and Amy Wang and Gabor Fichtinger} } @article {Fooladgar2022, title = {Uncertainty estimation for margin detection in cancer surgery using mass spectrometry}, journal = {International Journal of Computer Assisted Radiology and Surgery}, year = {2022}, month = {09/2022}, type = {Journal}, doi = {https://doi.org/10.1007/s11548-022-02764-3}, author = {Fahimeh Fooladgar and Amoon Jamzad and Laura Connolly and Alice Santilli and Martin Kaufmann and Kevin Ren and Purang Abolmaesumi and John Rudan and Doug McKay and Gabor Fichtinger and Parvin Mousavi} }