Rapid diagnosis and tumor margin assessment during pancreatic cancer surgery with the MasSpec Pen technology

Abstract

Intraoperative delineation of tumor margins is critical for effective pancreatic cancer surgery. Yet, intraoperative frozen section analysis of tumor margins is a time-consuming and often challenging procedure that can yield confounding results due to histologic heterogeneity and tissue-processing artifacts. We have previously described the development of the MasSpec Pen technology as a handheld mass spectrometry–based device for nondestructive tissue analysis. Here, we evaluated the usefulness of the MasSpec Pen for intraoperative diagnosis of pancreatic ductal adenocarcinoma based on alterations in the metabolite and lipid profiles in in vivo and ex vivo tissues. We used the MasSpec Pen to analyze 157 banked human tissues, including pancreatic ductal adenocarcinoma, pancreatic, and bile duct tissues. Classification models generated from the molecular data yielded an overall agreement with pathology of 91.5%, sensitivity of 95.5%, and specificity of 89.7% for discriminating normal pancreas from cancer. We built a second classifier to distinguish bile duct from pancreatic cancer, achieving an overall accuracy of 95%, sensitivity of 92%, and specificity of 100%. We then translated the MasSpec Pen to the operative room and predicted on in vivo and ex vivo data acquired during 18 pancreatic surgeries, achieving 93.8% overall agreement with final postoperative pathology reports. Notably, when integrating banked tissue data with intraoperative data, an improved agreement of 100% was achieved. The result obtained demonstrate that the MasSpec Pen provides high predictive performance for tissue diagnosis and compatibility for intraoperative use, suggesting that the technology may be useful to guide surgical decision-making during pancreatic cancer surgeries.

Mass Spectrometry-Based Differentiation of Oral Tongue Squamous Cell Carcinoma and Nontumor Regions With the SpiderMass Technology

“…Three distinct regions on large surfaces of tumors were classified against the pancreatic ductal adenocarcinoma (PADC) and normal tissue. While in high agreement with the histopathological evaluation, difficulties remained for the evaluation of cases with low infiltration of cancer cells [ 48 ]. These examples clearly demonstrate the need for MS analysis in the assessment of surgical margins, but even if all the MS-based technologies demonstrate strong classification performances, improvements are still necessary to enable complete characterization including the percentage of cancer cells present at a specific location.…”

Mass Spectrometry Imaging Spatial Tissue Analysis toward Personalized Medicine

“…Samples collected prospectively were measured using the MasSpec Pen technology, and used for training and testing the least absolute shrinkage and selection operator (lasso) classifiers. The method yielded over 98% agreement with histological evaluation when classifying normal pancreas and PDAC in the training set (78 tissue analyses; PDAC samples with >70% tumor cells) and 78.8% in the validation set (33 tissue analyses; samples with mixed cellularity and low epithelial tumor cell concentration) [ 44 ]. A second lasso classifier was employed to differentiate bile duct ( n = 16) and PDAC ( n = 27) with accuracy of 98% in the training set, and accuracy of 91% in the validation set (bile duct, n = 7; PDCA, n = 17; PDAC invading bile duct, n = 8).…”

Advances in non-invasive biosensing measures to monitor wound healing progression

“…Mass spectrometry has also been used to characterize and quantify the presence of bacterial biofilms, including in human dermal wounds (Charlton et al, 2000;Ashrafi et al, 2018;Achek et al, 2020). In recent years, this technology has been used for the detection of metastatic breast and thyroid cancers, and has been translated into the clinic in a handheld device, the MasSpec Pen System ™ , for real time determination of tumor margins during pancreatic cancer surgery (Zhang et al, 2017;King et al, 2021). This technology may offer physicians a non-invasive, real-time method for analysis of a wound and determination of healing status.…”

“…These technologies may potentially lead to a transformative wound healing approach that can expedite recovery, eliminate incomplete healing with scarring, and reduce the risks of infection and limb amputations (Zhang et al, 2021). In addition, the ability to real-time monitor the wound status without continuous screenings by medical professionals, may result in substantially reduced treatment cost and facilitate clinicians in more precisely tracking the healing process of the patients, enabling developments of personalized and predictive care.…”