Broadband hyperspectral imaging for breast tumor detection using spectral and spatial information

Complete tumor removal during breast-conserving surgery remains challenging due to the lack of optimal intraoperative margin assessment techniques. Here, we use hyperspectral imaging for tumor detection in fresh breast tissue. We evaluated different wavelength ranges and two classification algorithms; a pixel-wise classification algorithm and a convolutional neural network that combines spectral and spatial information. The highest classification performance was obtained using the full wavelength range (450-1650nm). Adding spatial information mainly improved the differentiation of tissue classes within the malignant and healthy classes. High sensitivity and specificity were accomplished, which offers potential for hyperspectral imaging as a margin assessment technique to improve surgical outcome. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreemen

Method for coregistration of optical measurements of breast tissue with histopathology : the importance of accounting for tissue deformations

For the validation of optical diagnostic technologies, experimental results need to be benchmarked against the gold standard. Currently, the gold standard for tissue characterization is assessment of hematoxylin and eosin (H&E)-stained sections by a pathologist. When processing tissue into H&E sections, the shape of the tissue deforms with respect to the initial shape when it was optically measured. We demonstrate the importance of accounting for these tissue deformations when correlating optical measurement with routinely acquired histopathology. We propose a method to register the tissue in the H&E sections to the optical measurements, which corrects for these tissue deformations. We compare the registered H&E sections to H&E sections that were registered with an algorithm that does not account for tissue deformations by evaluating both the shape and the composition of the tissue and using microcomputer tomography data as an independent measure. The proposed method, which did account for tissue deformations, was more accurate than the method that did not account for tissue deformations. These results emphasize the need for a registration method that accounts for tissue deformations, such as the method presented in this study, which can aid in validating optical techniques for clinical use. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License

Point Projection Mapping System for Tracking, Registering, Labeling and Validating Optical Tissue Measurements

Validation of newly developed optical tissue sensing techniques for tumor detection during cancer surgery requires an accurate correlation with histological results. Additionally, such accurate correlation facilitates precise data labeling for developing high-performance machine-learning tissue classification models. In this paper, a newly developed Point Projection Mapping system will be introduced, which allows non-destructive tracking of the measurement locations on tissue specimens. Additionally, a framework for accurate registration, validation, and labeling with histopathology results is proposed and validated on a case study. The proposed framework provides a more robust and accurate method for tracking and validation of optical tissue sensing techniques, which saves time and resources compared to conventional techniques available

Toward the use of diffuse reflection spectroscopy for intra-operative tissue discrimination during sarcoma surgery

Significance: Accurately distinguishing tumor tissue from normal tissue is crucial to achieve complete resections during soft tissue sarcoma (STS) surgery while preserving critical structures. Incomplete tumor resections are associated with an increased risk of local recurrence and worse patient prognosis. Aim: We evaluate the performance of diffuse reflectance spectroscopy (DRS) to distinguish tumor tissue from healthy tissue in STSs. Approach: DRS spectra were acquired from different tissue types on multiple locations in 20 freshly excised sarcoma specimens. A k -nearest neighbors classification model was trained to predict the tissue types of the measured locations, using binary and multiclass approaches. Results: Tumor tissue could be distinguished from healthy tissue with a classification accuracy of 0.90, sensitivity of 0.88, and specificity of 0.93 when well-differentiated liposarcomas were included. Excluding this subtype, the classification performance increased to an accuracy of 0.93, sensitivity of 0.94, and specificity of 0.93. The developed model showed a consistent performance over different histological subtypes and tumor locations. Conclusions: Automatic tissue discrimination using DRS enables real-time intraoperative guidance, contributing to more accurate STS resections.</p

Hepatic vessel segmentation using a reduced filter 3D U-Net in ultrasound imaging

Accurate hepatic vessel segmentation on ultrasound (US) images can be an important tool in the planning and execution of surgery, however proves to be a challenging task due to noise and speckle. Our method comprises a reduced filter 3D U-Net implementation to automatically detect hepatic vasculature in 3D US volumes. A comparison is made between volumes acquired with a 3D probe and stacked 2D US images based on electromagnetic tracking. Experiments are conducted on 67 scans, where 45 are used in training, 12 in validation and 10 in testing. This network architecture yields Dice scores of 0.740 and 0.781 for 3D and stacked 2D volumes respectively, comparing promising to literature and inter-observer performance (Dice = 0.879).Comment: 3 pages, conference extended abstract. MIDL 2019 [arXiv:1907.08612

Randomized controlled trial comparing magnetic marker localization (MaMaLoc) with wire-guided localization in the treatment of early-stage breast cancer

Wire-guided localization (WGL) is the standard of care in the surgical treatment of nonpalpable breast tumors. In this study, we compare the use of a new magnetic marker localization (MaMaLoc) technique to WGL in the treatment of early-stage breast cancer patients. Open-label, single-center, randomized controlled trial comparing MaMaLoc (intervention) to WGL (control) in women with early-stage breast cancer. Primary outcome was surgical usability measured using the System Usability Scale (SUS, 0-100 score). Secondary outcomes were patient reported, clinical, and pathological outcomes such as retrieval rate, operative time, resected specimen weight, margin status, and reoperation rate. Thirty-two patients were analyzed in the MaMaLoc group and 35 in the WGL group. Patient and tumor characteristics were comparable between groups. No in situ complications occurred. Retrieval rate was 100% in both groups. Surgical usability was higher for MaMaLoc: 70.2 ± 8.9 vs. 58.1 ± 9.1, p < 0.001. Patients reported higher overall satisfaction with MaMaLoc (median score 5/5) versus WGL (score 4/5), p < 0.001. The use of magnetic marker localization (MaMaLoc) for early-stage breast cancer is effective and has higher surgical usability than standard WGL

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

Most Patients with Colorectal Tumors at Young Age Do Not Visit a Cancer Genetics Clinic

Contains fulltext : 70595.pdf (publisher's version ) (Open Access)PURPOSE: This study examined the referral process for genetic counseling at a cancer genetics clinic in patients with colorectal cancer and to search for determinants of variation in this referral process. METHODS: Patients who were recently diagnosed with colorectal cancer at a young age or multiple cancers associated with Lynch syndrome, hereditary nonpolyposis colorectal cancer, (N = 119) were selected from PALGA, the nationwide network and registry of histopathology and cytopathology in the Netherlands. In a retrospective analysis, we examined whether these patients visited a cancer genetics clinic and identified determinants for referral to such a clinic. Factors of patients, professional practice, and hospital setting were explored with logistic regression modeling. RESULTS: Thirty-six (30 percent) patients visited a cancer genetics clinic. Seventy percent of patients whom the surgeon referred to a cancer genetics clinic decided to visit such a clinic. Analysis of determinants showed that patients with whom the surgeon discussed referral and that were treated in a teaching hospital were more likely to visit a cancer genetics clinic. CONCLUSION: The referral process is not optimally carried out. To deliver optimal care for patients suspected of hereditary colorectal cancer, this process must be improved with interventions focusing on patient referral by surgeons and raising awareness in nonteaching hospitals