Evaluation of hyperspectral imaging (HSI) for the measurement of ischemic conditioning effects of the gastric conduit during esophagectomy.

BACKGROUND: Hyperspectral imaging (HSI) is a relatively new method used in image-guided and precision surgery, which has shown promising results for characterization of tissues and assessment of physiologic tissue parameters. Previous methods used for analysis of preconditioning concepts in patients and animal models have shown several limitations of application. The aim of this study was to evaluate HSI for the measurement of ischemic conditioning effects during esophagectomy. METHODS: Intraoperative hyperspectral images of the gastric tube through the mini-thoracotomy were recorded from n = 22 patients, 14 of whom underwent laparoscopic gastrolysis and ischemic conditioning of the stomach with two-step transthoracic esophagectomy and gastric pull-up with intrathoracic anastomosis after 3-7 days. The tip of the gastric tube (later esophagogastric anastomosis) was measured with HSI. Analysis software provides a RGB image and 4 false color images representing physiologic parameters of the recorded tissue area intraoperatively. These parameters contain tissue oxygenation (StO2), perfusion-(NIR Perfusion Index), organ hemoglobin (OHI), and tissue water index (TWI). RESULTS: Intraoperative HSI of the gastric conduit was possible in all patients and did not prolong the regular operative procedure due to its quick applicability. In particular, the tissue oxygenation of the gastric conduit was significantly higher in patients who underwent ischemic conditioning ([Formula: see text] = 78%; [Formula: see text] = 66%; p = 0.03). CONCLUSIONS: HSI is suitable for contact-free, non-invasive, and intraoperative evaluation of physiological tissue parameters within gastric conduits. Therefore, HSI is a valuable method for evaluating ischemic conditioning effects and may contribute to reduce anastomotic complications. Additional studies are needed to establish normal values and thresholds of the presented parameters for the gastric conduit anastomotic site.

Clinical and functional outcome following robotic Heller-myotomy with partial fundoplication in patients with achalasia.

Robotic-assisted myotomy with partial fundoplication for patients with achalasia has been established as a safe and effective procedure with similar short-term results and lower rates of intraoperative esophageal perforations. Our aim was to investigate a defined patient cohort undergoing robotic-assisted and laparoscopic surgery providing pre- and postoperative symptom score and high-resolution manometry to evaluate the clinical and functional outcome.All patients underwent clinical, endoscopic, radiological and manometric investigation to verify the diagnosis of achalasia. High-resolution manometry was performed preoperatively and 6 months postoperatively and categorized according to the Chicago Classification (v4.0). We used the Eckardt Score to evaluate symptomatic outcome. All patients underwent either robotic-assisted or laparoscopic myotomy with partial anterior fundoplication (180° Dor) using the DaVinci Xi surgical system (Intuitive, Sunnyvale, California, USA). From a total amount of 101 patients, we analyzed the data of 78 (47 robotic and 31 laparoscopic) procedures between 2015 and 2020. All patients showed a significant decrease of the Eckardt Score in the robotic group (median 6 vs. 2) as well as in the laparoscopic group (median 7.5 vs. 3). The postoperative LESP and 4 s-IRP was significantly reduced in all patients in the robotic group [median LESP (mmHg) 34.16 vs. 16.9; median 4 s-IRP (mmHg) 28.85 vs. 14.55], as well as in the laparoscopic group [median LESP (mmHg) 35.34 vs. 17.3; median 4 s-IRP (mmHg) 25.6 vs. 15.9]. There was no significant difference for these parameters between the groups. There was no event of intraoperative esophageal perforation in the robotic cohort, whereas there were 2 in the laparoscopic group. Our data support the safe and effective robotic approach for the surgical treatment of achalasia. Not only the clinical outcome but also the functional results measured by high-resolution manometry are similar to the laparoscopic procedure. Further investigations in larger prospective multicenter studies are needed.

Tissue classification of oncologic esophageal resectates based on hyperspectral data.

PURPOSE: Esophageal carcinoma is the eighth most common cancer worldwide. Esophageal resection with gastric pull-up is a potentially curative therapeutic option. After this procedure, the specimen is examined by the pathologist to confirm complete removal of the cancer. An intraoperative analysis of the resectate would be less time-consuming and therefore improve patient safety. METHODS: Hyperspectral imaging (HSI) is a relatively new modality, which has shown promising results for the detection of tumors. Automatic approaches could support the surgeon in the visualization of tumor margins. Therefore, we evaluated four supervised classification algorithms: random forest, support vector machines (SVM), multilayer perceptron, and k-nearest neighbors to differentiate malignant from healthy tissue based on HSI recordings of esophago-gastric resectates in 11 patients. RESULTS: The best performances were obtained with a cancerous tissue detection of 63% sensitivity and 69% specificity with the SVM. In a leave-one patient-out cross-validation, the classification showed larger performance differences according to the patient data used. In less than 1 s, data classification and visualization was shown. CONCLUSION: In this work, we successfully tested several classification algorithms for the automatic detection of esophageal carcinoma in resected tissue. A larger data set and a combination of several methods would probably increase the performance. Moreover, the implementation of software tools for intraoperative tumor boundary visualization will further support the surgeon during oncologic operations.