Maximal resection of tumor while preserving the adjacent healthy tissue is particularly important for larynx surgery, hence precise and rapid intraoperative histology of laryngeal tissue is crucial for providing optimal surgical outcomes. We hypothesized that deep-learning based stimulated Raman scattering (SRS) microscopy could provide automated and accurate diagnosis of laryngeal squamous cell carcinoma on fresh, unprocessed surgical specimens without fixation, sectioning or staining.
Methods: We first compared 80 pairs of adjacent frozen sections imaged with SRS and standard hematoxylin and eosin histology to evaluate their concordance. We then applied SRS imaging on fresh surgical tissues from 45 patients to reveal key diagnostic features, based on which we have constructed a deep learning based model to generate automated histologic results. 18,750 SRS fields of views were used to train and cross-validate our 34-layered residual convolutional neural network, which was used to classify 33 untrained fresh larynx surgical samples into normal and neoplasia. Furthermore, we simulated intraoperative evaluation of resection margins on totally removed larynxes.
Results: We demonstrated near-perfect diagnostic concordance (Cohen's kappa, K > 0.90) between SRS and standard histology as evaluated by three pathologists. And deep-learning based SRS correctly classified 33 independent surgical specimens with 100% accuracy. We also demonstrated that our method could identify tissue neoplasia at the simulated resection margins that appear grossly normal with naked eyes.
Conclusion: Our results indicated that SRS histology integrated with deep learning algorithm provides potential for delivering rapid intraoperative diagnosis that could aid the surgical management of laryngeal cancer.
[1]Fudan Univ, State Key Lab Surface Phys, Shanghai 200433, Peoples R China;
[2]Fudan Univ, Dept Phys, Shanghai 200433, Peoples R China;
[3]Fudan Univ, Human Phenome Inst, Key Lab Micro & Nano Photon Struct, Multiscale Res Inst Complex Syst,Minist Educ, Shanghai 200433, Peoples R China;
[4]Hangzhou Med Coll, Zhejiang Prov Peoples Hosp, Dept Otolaryngol, Peoples Hosp, Hangzhou 310014, Zhejiang, Peoples R China;
[5]Hangzhou Med Coll, Zhejiang Prov Peoples Hosp, Dept Pathol, Peoples Hosp, Hangzhou 310014, Zhejiang, Peoples R China;
[6]Fudan Univ, Huashan Hosp, Dept Neurosurg, Dept Pancreat Surg, Shanghai 200040, Peoples R China;
[7]Fudan Univ, Dept Breast Surg, Shanghai Canc Ctr, Shanghai 200040, Peoples R China;
[8]Shanghai Med Coll, Dept Oncol, Shanghai 200040, Peoples R China;
[9]Fudan Univ, Shanghai 200040, Peoples R China
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