Introduction: Anastomotic leakage after gastrointestinal surgery has a high impact on patient's quality of life and its origin is associated with inadequate perfusion. Imaging photoplethysmography (iPPG) is a noninvasive imaging technique that measures blood-volume changes in the microvascular tissue bed and detects changes in tissue perfusion. Materials and methods: Intraoperative iPPG imaging was performed in 29 patients undergoing an open segment resection of the small intestine or colon. During each surgery, imaging was performed on fully perfused (true positives) and ischemic intestines (true negatives) and the anastomosis (unknowns). Imaging consisted of a 30-s video from which perfusion maps were extracted, providing detailed information about blood flow within the intestine microvasculature. To detect the predictive capabilities of iPPG, true positive and true negative perfusion conditions were used to develop two different perfusion classification methods. Results: iPPG-derived perfusion parameters were highly correlated with perfusion—perfused or ischemic—in intestinal tissues. A perfusion confidence map distinguished perfused and ischemic intestinal tissues with 96% sensitivity and 86% specificity. Anastomosis images were scored as adequately perfused in 86% of cases and 14% inconclusive. The cubic-Support Vector Machine achieved 90.9% accuracy and an area under the curve of 96%. No anastomosis-related postoperative complications were encountered in this study. Conclusions: This study shows that noninvasive intraoperative iPPG is suitable for the objective assessment of small intestine and colon anastomotic perfusion. In addition, two perfusion classification methods were developed, providing the first step in an intestinal perfusion prediction model.

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Surgical excision is the golden standard for treatment of intestinal tumors. In this surgical procedure, inadequate perfusion of the anastomosis can lead to postoperative complications, such as anastomotic leakages. Imaging photoplethysmography (iPPG) can potentially provide objective and real-time feedback of the perfusion status of tissues. This feasibility study aims to evaluate an iPPG acquisition system during intestinal surgeries to detect the perfusion levels of the microvasculature tissue bed in different perfusion conditions. This feasibility study assesses three patients that underwent resection of a portion of the small intestine. Data was acquired from fully perfused, non-perfused and anastomosis parts of the intestine during different phases of the surgical procedure. Strategies for limiting motion and noise during acquisition were implemented. iPPG perfusion maps were successfully extracted from the intestine microvasculature, demonstrating that iPPG can be successfully used for detecting perturbations and perfusion changes in intestinal tissues during surgery. This study provides proof of concept for iPPG to detect changes in organ perfusion levels.

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Background and Objectives: In patients with rectal cancer who received neoadjuvant (chemo)radiotherapy, fibrosis is induced in and around the tumor area. As tumors and fibrosis have similar visual and tactile feedback, they are hard to distinguish during surgery. To prevent positive resection margins during surgery and spare healthy tissue, it would be of great benefit to have a real-time tissue classification technology that can be used in vivo. Study Design/Materials and Methods: In this study diffuse reflectance spectroscopy (DRS) was evaluated for real-time tissue classification of tumor and fibrosis. DRS spectra of fibrosis and tumor were obtained on excised rectal specimens. After normalization using the area under the curve, a support vector machine was trained using a 10-fold cross-validation. Results: Using spectra of pure tumor tissue and pure fibrosis tissue, we obtained a mean accuracy of 0.88. This decreased to a mean accuracy of 0.61 when tumor measurements were used in which a layer of healthy tissue, mainly fibrosis, was present between the tumor and the measurement surface. Conclusion: It is possible to distinguish pure fibrosis from pure tumor. However, when the measurements on tumor also involve fibrotic tissue, the classification accuracy decreases. Lasers Surg. Med.

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Neoadjuvant radiotherapy, as part of the conventional treatment of rectal cancer, can induce fibrotic tissue formation around the tumor. This complicates the exact determination of the tumor borders during surgery, which might increase the chance of positive resection margins. In a previous ex vivo study, we distinguished tumor tissue from healthy rectal wall and fat with an accuracy of 0.95, using diffuse reflectance spectroscopy (DRS). Since this study did not include fibrosis, the aim of the current ex vivo study was to examine whether differentiation of tumor and fibrosis with DRS is possible. DRS measurements from freshly resected specimen of 16 patients were obtained. In eight patients fibrosis was measured, in the other eight patients tumor was measured. The measurements were performed using a DRS probe with a source-detector distance of 2 mm. The spectra were obtained in the wavelength range of 450-1600 nm. Classification of the measurements was done using a support vector machine (SVM) and a set of features extracted from the spectra. The SVM was evaluated using an eight-fold cross-validation, which was repeated ten times. For all repetitions, the area under the ROC curve was greater than 0.85 (mean = 0.87, STD = 0.02). The mean sensitivity and specificity were 0.85 (STD = 0.03) and 0.88 (STD = 0.01) respectively. It can be concluded that tumor tissue can be distinguished from fibrosis based on spectral features from DRS measurements. The next step will be to conduct an in vivo study, to verify these results during surgery.@en

Background: In colorectal cancer surgery there is a delicate balance between complete removal of the tumor and sparing as much healthy tissue as possible. Especially in rectal cancer, intraoperative tissue recognition could be of great benefit in preventing positive resection margins and sparing as much healthy tissue as possible. To better guide the surgeon, we evaluated the accuracy of diffuse reflectance spectroscopy (DRS) for tissue characterization during colorectal cancer surgery and determined the added value of DRS when compared to clinical judgement. Methods: DRS spectra were obtained from fat, healthy colorectal wall and tumor tissue during colorectal cancer surgery and results were compared to histopathology examination of the measurement locations. All spectra were first normalized at 800 nm, thereafter two support vector machines (SVM) were trained using a tenfold cross-validation. With the first SVM fat was separated from healthy colorectal wall and tumor tissue, the second SVM distinguished healthy colorectal wall from tumor tissue. Results: Patients were included based on preoperative imaging, indicating advanced local stage colorectal cancer. Based on the measurement results of 32 patients, the classification resulted in a mean accuracy for fat, healthy colorectal wall and tumor of 0.92, 0.89 and 0.95 respectively. If the classification threshold was adjusted such that no false negatives were allowed, the percentage of false positive measurement locations by DRS was 25% compared to 69% by clinical judgement. Conclusion: This study shows the potential of DRS for the use of tissue classification during colorectal cancer surgery. Especially the low false positive rate obtained for a false negative rate of zero shows the added value for the surgeons. Trail registration This trail was performed under approval from the internal review board committee (Dutch Trail Register NTR5315), registered on 04/13/2015, https://www.trialregister.nl/trial/5175.

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Background: Careful identification of nerves during head and neck surgery is essential to prevent nerve damage. Currently, nerves are identified based on anatomy and appearance, optionally combined with electromyography (EMG). In challenging cases, nerve damage is reported in up to 50%. Recently, optical techniques, like diffuse reflectance spectroscopy (DRS) and fluorescence spectroscopy (FS) show potential to improve nerve identification. Methods: 212 intra-operative DRS/FS measurements were performed. Small nerve branches (1-3 mm), on near-nerve adipose tissue, muscle and subcutaneous fat were measured during 11 surgical procedures. Tissue identification was based on quantified concentrations of optical absorbers and scattering parameters. Results: Clinically comprehensive parameters showed significant differences (<0.05) between the tissues. Classification using k-Nearest Neighbor resulted in 100% sensitivity and a specificity of 83% (accuracy 91%), for the identification of nerve against surrounding tissues. Conclusions: DRS/FS is a potentially useful intraoperative tool for identification of nerves from adjacent tissues. Level of Evidence: Observational proof of principle study.

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Precise nerve localization is of major importance in both surgery and regional anesthesia. Optically based techniques can identify tissue through differences in optical properties, like absorption and scattering. The aim of this study was to evaluate the potential of optical spectroscopy (diffuse reflectance spectroscopy) for clinical nerve identification in vivo. Eighteen patients (8 male, 10 female, age 53 ± 13 years) undergoing inguinal lymph node resection or resection or a soft tissue tumor in the groin were included to measure the femoral or sciatic nerve and the surrounding tissues. In vivo optical measurements were performed using Diffuse Reflectance Spectroscopy (400–1600 nm) on nerve, near nerve adipose tissue, muscle, and subcutaneous fat using a needle-shaped probe. Model-based analyses were used to derive verified quantitative parameters as concentrations of optical absorbers and several parameters describing scattering. A total of 628 optical spectra were recorded. Measured spectra reveal noticeable tissue specific characteristics. Optical absorption of water, fat, and oxy- and deoxyhemoglobin was manifested in the measured spectra. The parameters water and fat content showed significant differences (P < 0.005) between nerve and all surrounding tissues. Classification using k-Nearest Neighbor based on the derived parameters revealed a sensitivity of 85% and a specificity of 79%, for identifying nerve from surrounding tissues. Diffuse Reflectance Spectroscopy identifies peripheral nerve bundles. The differences found between tissue groups are assignable to the tissue composition and structure.

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Colorectal surgery is the standard treatment for patients with colorectal cancer. To overcome two of the main challenges, the circumferential resection margin and postoperative complications, real-time tissue assessment could be of great benefit during surgery. In this ex vivo study, diffuse reflectance spectroscopy (DRS) was used to differentiate tumor tissue from healthy surrounding tissues in patients with colorectal neoplasia. DRS spectra were obtained from tumor tissue, healthy colon, or rectal wall and fat tissue, for every patient. Data were randomly divided into training (80%) and test (20%) sets. After spectral band selection, the spectra were classified using a quadratic classifier and a linear support vector machine. Of the 38 included patients, 36 had colorectal cancer and 2 had an adenoma. When the classifiers were applied to the test set, colorectal cancer could be discriminated from healthy tissue with an overall accuracy of 0.95 (±0.03). This study demonstrates the possibility to separate colorectal cancer from healthy surrounding tissue by applying DRS. High classification accuracies were obtained both in homogeneous and inhomogeneous tissues. This is a fundamental step toward the development of a tool for real-time in vivo tissue assessment during colorectal surgery.

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