Tumor Segmentation in Colorectal Ultrasound Images Using an Ensemble Transfer Learning Model: Towards Intra-Operative Margin Assessment.

Tumor boundary identification during colorectal cancer surgery can be challenging, and incomplete tumor removal occurs in approximately 10% of the patients operated for advanced rectal cancer. In this paper, a deep learning framework for automatic tumor segmentation in colorectal ultrasound images was developed, to provide real-time guidance on resection margins using intra-operative ultrasound. A colorectal ultrasound dataset was acquired consisting of 179 images from 74 patients, with ground truth tumor annotations based on histopathology results. To address data scarcity, transfer learning techniques were used to optimize models pre-trained on breast ultrasound data for colorectal ultrasound data. A new custom gradient-based loss function (GWDice) was developed, which emphasizes the clinically relevant top margin of the tumor while training the networks. Lastly, ensemble learning methods were applied to combine tumor segmentation predictions of multiple individual models and further improve the overall tumor segmentation performance. Transfer learning outperformed training from scratch, with an average Dice coefficient over all individual networks of 0.78 compared to 0.68. The new GWDice loss function clearly decreased the average tumor margin prediction error from 1.08 mm to 0.92 mm, without compromising the segmentation of the overall tumor contour. Ensemble learning further improved the Dice coefficient to 0.84 and the tumor margin prediction error to 0.67 mm. Using transfer and ensemble learning strategies, good tumor segmentation performance was achieved despite the relatively small dataset. The developed US segmentation model may contribute to more accurate colorectal tumor resections by providing real-time intra-operative feedback on tumor margins.

Diffuse reflectance spectroscopy for accurate margin assessment in breast-conserving surgeries: importance of an optimal number of fibers.

During breast-conserving surgeries, it remains challenging to accomplish adequate surgical margins. We investigated different numbers of fibers for fiber-optic diffuse reflectance spectroscopy to differentiate tumorous breast tissue from healthy tissue ex vivo up to 2 mm from the margin. Using a machine-learning classification model, the optimal performance was obtained using at least three emitting fibers (Matthew's correlation coefficient (MCC) of 0.73), which was significantly higher compared to the performance of using a single-emitting fiber (MCC of 0.48). The percentage of correctly classified tumor locations varied from 75% to 100% depending on the tumor percentage, the tumor-margin distance and the number of fibers.

Size and depth of residual tumor after neoadjuvant chemoradiotherapy in rectal cancer - implications for the development of new imaging modalities for response assessment.

With the shift towards organ preserving treatment strategies in rectal cancer it has become increasingly important to accurately discriminate between a complete and good clinical response after neoadjuvant chemoradiotherapy (CRT). Standard of care imaging techniques such as CT and MRI are well equipped for initial staging of rectal tumors, but discrimination between a good clinical and complete response remains difficult due to their limited ability to detect small residual vital tumor fragments. To identify new promising imaging techniques that could fill this gap, it is crucial to know the size and invasion depth of residual vital tumor tissue since this determines the requirements with regard to the resolution and imaging depth of potential new optical imaging techniques. We analyzed 198 pathology slides from 30 rectal cancer patients with a Mandard tumor regression grade 2 or 3 after CRT that underwent surgery. For each patient we determined response pattern, size of the largest vital tumor fragment or bulk and the shortest distance from the vital tumor to the luminal surface. The response pattern was shrinkage in 14 patients and fragmentation in 16 patients. For both groups combined, the largest vital tumor fragment per patient was smaller than 1mm for 38% of patients, below 0.2mm for 12% of patients and for one patient as small as 0.06mm. For 29% of patients the vital tumor remnant was present within the first 0.01mm from the luminal surface and for 87% within 0.5mm. Our results explain why it is difficult to differentiate between a good clinical and complete response in rectal cancer patients using endoscopy and MRI, since in many patients submillimeter tumor fragments remain below the luminal surface. To detect residual vital tumor tissue in all patients included in this study a technique with a spatial resolution of 0.06mm and an imaging depth of 8.9mm would have been required. Optical imaging techniques offer the possibility of detecting majority of these cases due to the potential of both high-resolution imaging and enhanced contrast between tissue types. These techniques could thus serve as a complimentary tool to conventional methods for rectal cancer response assessment.

Imaging Photoplethysmography for Noninvasive Anastomotic Perfusion Assessment in Intestinal Surgery.

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.

Imaging PPG for In Vivo Human Tissue Perfusion Assessment during Surgery.

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.

Understanding the Costs of Surgery: A Bottom-Up Cost Analysis of Both a Hybrid Operating Room and Conventional Operating Room.

BACKGROUND: Over the past decade, many hospitals have adopted hybrid operating rooms (ORs). As resources are limited, these ORs have to prove themselves in adding value. Current estimations on standard OR costs show great variety, while cost analyses of hybrid ORs are lacking. Therefore, this study aims to identify the cost drivers of a conventional and hybrid OR and take a first step in evaluating the added value of the hybrid OR. METHODS: A comprehensive bottom-up cost analysis was conducted in five Dutch hospitals taking into account: construction, inventory, personnel and overhead costs by means of interviews and hospital specific data. The costs per minute for both ORs were calculated using the utilization rates of the ORs. Cost drivers were identified by sensitivity analyses. RESULTS: The costs per minute for the conventional OR and the hybrid OR were €9.45 (€8.60-€10.23) and €19.88 (€16.10- €23.07), respectively. Total personnel and total inventory costs had most impact on the conventional OR costs. For the hybrid OR the costs were mostly driven by utilization rate, total inventory and construction costs. The results were incorporated in an open access calculation model to enable adjustment of the input parameters to a specific hospital or country setting. CONCLUSION: This study estimated a cost of €9.45 (€8.60-€10.23) and €19.88 (€16.10-€23.07) for the conventional and hybrid OR, respectively. The main factors influencing the OR costs are: total inventory costs, total construction costs, utilization rate, and total personnel costs. Our analysis can be used as a basis for future research focusing on evaluating value for money of this promising innovative OR. Furthermore, our results can inform surgeons, and decision and policy-makers in hospitals on the adoption and optimal utilization of new (hybrid) ORs.

Toward assessment of resection margins using hyperspectral diffuse reflection imaging (400-1,700 nm) during tongue cancer surgery.

BACKGROUND AND OBJECTIVES: There is a clinical need to assess the resection margins of tongue cancer specimens, intraoperatively. In the current ex vivo study, we evaluated the feasibility of hyperspectral diffuse reflectance imaging (HSI) for distinguishing tumor from the healthy tongue tissue. STUDY DESIGN/MATERIALS AND METHODS: Fresh surgical specimens (n = 14) of squamous cell carcinoma of the tongue were scanned with two hyperspectral cameras that cover the visible and near-infrared spectrum (400-1,700 nm). Each pixel of the hyperspectral image represents a measure of the diffuse optical reflectance. A neural network was used for tissue-type prediction of the hyperspectral images of the visual and near-infrared data sets separately as well as both data sets combined. RESULTS: HSI was able to distinguish tumor from muscle with a good accuracy. The diagnostic performance of both wavelength ranges (sensitivity/specificity of visual and near-infrared were 84%/80% and 77%/77%, respectively) appears to be comparable and there is no additional benefit of combining the two wavelength ranges (sensitivity and specificity were 83%/76%). CONCLUSIONS: HSI has a strong potential for intra-operative assessment of tumor resection margins of squamous cell carcinoma of the tongue. This may optimize surgery, as the entire resection surface can be scanned in a single run and the results can be readily available. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.

Hyperspectral Imaging for Resection Margin Assessment during Cancer Surgery.

PURPOSE: Complete tumor removal during cancer surgery remains challenging due to the lack of accurate techniques for intraoperative margin assessment. This study evaluates the use of hyperspectral imaging for margin assessment by reporting its use in fresh human breast specimens. EXPERIMENTAL DESIGN: Hyperspectral data were first acquired on tissue slices from 18 patients after gross sectioning of the resected breast specimen. This dataset, which contained over 22,000 spectra, was well correlated with histopathology and was used to develop a support vector machine classification algorithm and test the classification performance. In addition, we evaluated hyperspectral imaging in clinical practice by imaging the resection surface of six lumpectomy specimens. With the developed classification algorithm, we determined if hyperspectral imaging could detect malignancies in the resection surface. RESULTS: The diagnostic performance of hyperspectral imaging on the tissue slices was high; invasive carcinoma, ductal carcinoma in situ, connective tissue, and adipose tissue were correctly classified as tumor or healthy tissue with accuracies of 93%, 84%, 70%, and 99%, respectively. These accuracies increased with the size of the area, consisting of one tissue type. The entire resection surface was imaged within 10 minutes, and data analysis was performed fast, without the need of an experienced operator. On the resection surface, hyperspectral imaging detected 19 of 20 malignancies that, according to the available histopathology information, were located within 2 mm of the resection surface. CONCLUSIONS: These findings show the potential of using hyperspectral imaging for margin assessment during breast-conserving surgery to improve surgical outcome.

Diffuse reflectance spectroscopy as a tool for real-time tissue assessment during colorectal cancer surgery.

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.

Optical techniques for the intraoperative assessment of nodal status.

The lymphatic system is an important pathway in the metastatic spread of many malignancies and a key prognostic indicator. Nondestructive assessment of the nodal status during surgery could limit the amount of lymph nodes that need to be resected and allow for immediate regional lymphadenectomy during sentinel lymph node biopsy procedures. This review looks into the possibilities of conventional medical imaging methods that are capable of intraoperative nodal assessment and discusses multiple newly developed optical techniques. The physical background behind these techniques is reviewed and a concise overview of their main advantages and disadvantages is provided. These recent innovations show that while the application of optical modalities for intraoperative nodal staging is not yet applied routinely, there is reason enough to expect their introduction in the near future.

Added value of positron emission tomography imaging in the surgical treatment of colorectal liver metastases.

OBJECTIVE: [F-18]-Fluorodeoxyglucose-positron emission tomography (FDG-PET) is used increasingly in the work-up to surgery for patients with potentially resectable colorectal liver metastases. This study evaluates the clinical effectiveness, impact on health care resources and cost-effectiveness of adding FDG-PET to the diagnostic algorithm alongside a randomized clinical trial from a health care perspective. METHODS: In a randomized clinical trial, the net monetary benefit (NMB) of FDG-PET added to conventional diagnostic work-up (CWU) was determined in patients with colorectal liver metastases. Seventy-five patients were included in each arm. Change in clinical management, futile laparotomies, preoperative findings and all relevant health care consumption were prospectively documented during 3 years. To assess health-related quality of life European Quality of Life-5 Dimensions was administered at the time of randomization, 3 and 6 weeks postoperatively, and every 3 months postoperatively for 3 years. Quality-adjusted life years (QALYs) were calculated based on European Quality of Life-5 Dimensions outcomes. RESULTS: In adding FDG-PET, diagnostic performance increased and futile laparotomies were reduced by 38%. Both health-related quality of life and QALYs showed no significant difference between the CWU and PET groups. For CWU and PET groups costs were euro 92,836 and euro 81,776, respectively, accumulated in 3 years after randomization. NMB ranged from euro 1004 to euro 11,060 depending on the monetary value given to a QALY. When costs for chemotherapy were disregarded, costs amounted to euro 15,874 for CWU and euro 18,664 for PET group. CONCLUSION: Additional costs of FDG-PET in the diagnostic work-up of patients with potentially resectable colorectal liver metastases were compensated by a reduction in futile laparotomies. The NMB analysis showed savings over a relevant range of willingness to pay for a QALY.

FDG-PET in colorectal cancer.

[18F]Fluorodeoxyglucose (FDG) positron emission tomography (PET) is a useful imaging tool in the evolving management of patients with colorectal carcinoma. This technique is able to measure and visualize metabolic changes in cancer cells. This feature results in the ability to distinguish viable tumor from scar tissue, in the detection of tumor foci at an earlier stage than possible by conventional anatomic imaging and in the measurement of alterations in tumor metabolism, indicative of tumor response to therapy. Nowadays, FDG-PET plays a pivotal role in staging patients before surgical resection of recurrence and metastases, in the localization of recurrence in patients with an unexplained rise in serum carcinoembryonic antigen and in assessment of residual masses after treatment. In the presurgical evaluation, FDG-PET may be best used in conjunction with anatomic imaging in order to combine the benefits of both anatomical (CT) and functional (PET) information, which leads to significant improvements in preoperative liver staging and preoperative judgment on the feasibility of resection. Integration of FDG-PET into the management algorithm of these categories of patients alters and improves therapeutic management, reduces morbidity due to futile surgery, leads to substantial cost savings and probably also to a better patient outcome. FDG-PET also appears to have great potential in monitoring the success of local ablative therapies soon after intervention and in the prediction and evaluation of response to radiotherapy, systemic therapy, and combinations thereof. This review aims to outline the current and future role of FDG-PET in the field of colorectal cancer.