Hepatic arterial infusion pump chemotherapy combined with systemic chemotherapy for borderline resectable and unresectable colorectal liver metastases: phase II feasibility study

BACKGROUND

Hepatic arterial infusion pump chemotherapy combined with systemic chemotherapy (HAIP-SYS) for liver-only colorectal liver metastases (CRLMs) has shown promising results but has not been adopted worldwide. This study evaluated the feasibility of HAIP-SYS in the Netherlands.

METHODS

This was a single-arm phase II study of patients with CRLMs who received HAIP-SYS consisting of floxuridine with concomitant systemic FOLFOX or FOLFIRI. Main inclusion and exclusion criteria were borderline resectable or unresectable liver-only metastases, suitable arterial anatomy and no previous local treatment. Patients underwent laparotomy for pump implantation and primary tumour resection if in situ. Primary end point was feasibility, defined as ≥70% of patients completing two cycles of HAIP-SYS. Sample size calculations led to 31 patients. Secondary outcomes included safety and tumour response.

RESULTS

Thirty-one patients with median 13 CRLMs (i.q.r. 6-23) were included. Twenty-eight patients (90%) received two HAIP-SYS cycles. Three patients did not get two cycles due to extrahepatic disease at pump placement, definitive pathology of a recto-sigmoidal squamous cell carcinoma, and progressive disease. Five patients experienced grade 3 surgical or pump device-related complications (16%) and 11 patients experienced grade ≥3 chemotherapy toxicity (38%). At first radiological evaluation, disease control rate was 83% (24/29 patients) and hepatic disease control rate 93% (27/29 patients). At 6 months, 19 patients (66%) had experienced grade ≥3 chemotherapy toxicity and the disease control rate was 79%.

CONCLUSION

HAIP-SYS for borderline resectable and unresectable CRLMs was feasible and safe in the Netherlands. This has led to a successive multicentre phase III randomized trial investigating oncological benefit (EUDRA-CT 2023-506194-35-00). Current trial registration number: clinicaltrials.gov (NCT04552093).

Spatial and Spectral Reconstruction of Breast Lumpectomy Hyperspectral Images

(1) Background: Hyperspectral imaging has emerged as a promising margin assessment technique for breast-conserving surgery. However, to be implicated intraoperatively, it should be both fast and capable of yielding high-quality images to provide accurate guidance and decision-making throughout the surgery. As there exists a trade-off between image quality and data acquisition time, higher resolution images come at the cost of longer acquisition times and vice versa. (2) Methods: Therefore, in this study, we introduce a deep learning spatial-spectral reconstruction framework to obtain a high-resolution hyperspectral image from a low-resolution hyperspectral image combined with a high-resolution RGB image as input. (3) Results: Using the framework, we demonstrate the ability to perform a fast data acquisition during surgery while maintaining a high image quality, even in complex scenarios where challenges arise, such as blur due to motion artifacts, dead pixels on the camera sensor, noise from the sensor's reduced sensitivity at spectral extremities, and specular reflections caused by smooth surface areas of the tissue. (4) Conclusion: This gives the opportunity to facilitate an accurate margin assessment through intraoperative hyperspectral imaging.

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 intra-operative guidance, contributing to more accurate STS resections.

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

The validation of newly developed optical tissue-sensing techniques for tumor detection during cancer surgery requires an accurate correlation with the histological results. Additionally, such an 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 the histopathology results is proposed and validated on a case study. The proposed framework provides a more-robust and accurate method for the tracking and validation of optical tissue-sensing techniques, which saves time and resources compared to the available conventional techniques.

The influence of the da Vinci surgical robot on electromagnetic tracking in a clinical environment

Robot-assisted surgery is increasingly used in surgery for cancer. Reduced overview and loss of anatomical orientation are challenges that might be solved with image-guided surgical navigation using electromagnetic tracking (EMT). However, the robot's presence may distort the electromagnetic field, affecting EMT accuracy. The aim of this study was to evaluate the robot's influence on EMT accuracy. For this purpose, two different electromagnetic field generators were used inside a clinical surgical environment: a table top field generator (TTFG) and a planar field generator (PFG). The position and orientation of sensors within the electromagnetic field were measured using an accurate in-house developed 3D board. Baseline accuracy was measured without the robot, followed by stepwise introduction of potential distortion sources (robot and robotic instruments). The absolute accuracy was determined within the entire 3D board and in the clinical working volume. For the baseline setup, median errors in the entire tracking volume within the 3D board were 0.9 mm and 0.3° (TTFG), and 1.1 mm and 0.4° (PFG). Adding the robot and instruments did not affect the TTFG's position accuracy (p = 0.60), while the PFG's accuracies decreased to 1.5 mm and 0.7° (p < 0.001). For both field generators, when adding robot and instruments, accuracies inside the clinical working volume were higher compared to the entire tracking 3D board volume, 0.7 mm and 0.3° (TTFG), and 1.1 mm and 0.7° (PFG). Introduction of a surgical robot and robotic instruments shows limited distortion of the EMT field, allowing sufficient accuracy for surgical navigation in robotic procedures.

Ultrasound guidance in navigated liver surgery: toward deep-learning enhanced compensation of deformation and organ motion

PURPOSE

Accuracy of image-guided liver surgery is challenged by deformation of the liver during the procedure. This study aims at improving navigation accuracy by using intraoperative deep learning segmentation and nonrigid registration of hepatic vasculature from ultrasound (US) images to compensate for changes in liver position and deformation.

METHODS

This was a single-center prospective study of patients with liver metastases from any origin. Electromagnetic tracking was used to follow US and liver movement. A preoperative 3D model of the liver, including liver lesions, and hepatic and portal vasculature, was registered with the intraoperative organ position. Hepatic vasculature was segmented using a reduced 3D U-Net and registered to preoperative imaging after initial alignment followed by nonrigid registration. Accuracy was assessed as Euclidean distance between the tumor center imaged in the intraoperative US and the registered preoperative image.

RESULTS

Median target registration error (TRE) after initial alignment was 11.6 mm in 25 procedures and improved to 6.9 mm after nonrigid registration (p = 0.0076). The number of TREs above 10 mm halved from 16 to 8 after nonrigid registration. In 9 cases, registration was performed twice after failure of the first attempt. The first registration cycle was completed in median 11 min (8:00-18:45 min) and a second in 5 min (2:30-10:20 min).

CONCLUSION

This novel registration workflow using automatic vascular detection and nonrigid registration allows to accurately localize liver lesions. Further automation in the workflow is required in initial alignment and classification accuracy.

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.

Feasibility of tracked ultrasound registration for pelvic-abdominal tumor navigation: a patient study

PURPOSE

Surgical navigation techniques can guide surgeons in localizing pelvic-abdominal malignancies. For abdominal navigation, accurate patient registration is crucial and is generally performed using an intra-operative cone-beam CT (CBCT). However, this method causes 15-min surgical preparation workflow interruption and radiation exposure, and more importantly, it cannot be repeated during surgery to compensate for large patient movement. As an alternative, the accuracy and feasibility of tracked ultrasound (US) registration are assessed in this patient study.

METHODS

Patients scheduled for surgical navigation during laparotomy of pelvic-abdominal malignancies were prospectively included. In the operating room, two percutaneous tracked US scans of the pelvic bone were acquired: one in supine and one in Trendelenburg patient position. Postoperatively, the bone surface was semiautomatically segmented from US images and registered to the bone surface on the preoperative CT scan. The US registration accuracy was computed using the CBCT registration as a reference and acquisition times were compared. Additionally, both US measurements were compared to quantify the registration error caused by patient movement into Trendelenburg.

RESULTS

In total, 18 patients were included and analyzed. US registration resulted in a mean surface registration error of 1.2 ± 0.2 mm and a mean target registration error of 3.3 ± 1.4 mm. US acquisitions were 4 × faster than the CBCT scans (two-sample t-test P < 0.05) and could even be performed during standard patient preparation before skin incision. Patient repositioning in Trendelenburg caused a mean target registration error of 7.7 ± 3.3 mm, mainly in cranial direction.

CONCLUSION

US registration based on the pelvic bone is accurate, fast and feasible for surgical navigation. Further optimization of the bone segmentation algorithm will allow for real-time registration in the clinical workflow. In the end, this would allow intra-operative US registration to correct for large patient movement.

TRIAL REGISTRATION

This study is registered in ClinicalTrials.gov (NCT05637359).

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.

Microcamera Visualisation System to Overcome Specular Reflections for Tissue Imaging

In vivo tissue imaging is an essential tool for medical diagnosis, surgical guidance, and treatment. However, specular reflections caused by glossy tissue surfaces can significantly degrade image quality and hinder the accuracy of imaging systems. In this work, we further the miniaturisation of specular reflection reduction techniques using micro cameras, which have the potential to act as intra-operative supportive tools for clinicians. In order to remove these specular reflections, two small form factor camera probes, handheld at 10 mm footprint and miniaturisable to 2.3 mm, are developed using different modalities, with line-of-sight to further miniaturisation. (1) The sample is illuminated via multi-flash technique from four different positions, causing a shift in reflections which are then filtered out in a post-processing image reconstruction step. (2) The cross-polarisation technique integrates orthogonal polarisers onto the tip of the illumination fibres and camera, respectively, to filter out the polarisation maintaining reflections. These form part of a portable imaging system that is capable of rapid image acquisition using different illumination wavelengths, and employs techniques that lend themselves well to further footprint reduction. We demonstrate the efficacy of the proposed system with validating experiments on tissue-mimicking phantoms with high surface reflection, as well as on excised human breast tissue. We show that both methods can provide clear and detailed images of tissue structures along with the effective removal of distortion or artefacts caused by specular reflections. Our results suggest that the proposed system can improve the image quality of miniature in vivo tissue imaging systems and reveal underlying feature information at depth, for both human and machine observers, leading to better diagnosis and treatment outcomes.

Tissue Classification of Breast Cancer by Hyperspectral Unmixing

(1) Background: Assessing the resection margins during breast-conserving surgery is an important clinical need to minimize the risk of recurrent breast cancer. However, currently there is no technique that can provide real-time feedback to aid surgeons in the margin assessment. Hyperspectral imaging has the potential to overcome this problem. To classify resection margins with this technique, a tissue discrimination model should be developed, which requires a dataset with accurate ground-truth labels. However, establishing such a dataset for resection specimens is difficult. (2) Methods: In this study, we therefore propose a novel approach based on hyperspectral unmixing to determine which pixels within hyperspectral images should be assigned to the ground-truth labels from histopathology. Subsequently, we use this hyperspectral-unmixing-based approach to develop a tissue discrimination model on the presence of tumor tissue within the resection margins of ex vivo breast lumpectomy specimens. (3) Results: In total, 372 measured locations were included on the lumpectomy resection surface of 189 patients. We achieved a sensitivity of 0.94, specificity of 0.85, accuracy of 0.87, Matthew's correlation coefficient of 0.71, and area under the curve of 0.92. (4) Conclusion: Using this hyperspectral-unmixing-based approach, we demonstrated that the measured locations with hyperspectral imaging on the resection surface of lumpectomy specimens could be classified with excellent performance.

Initial Impact of National CRC Screening on Incidence and Advanced Colorectal Cancer

BACKGROUND AND AIMS

Screening for colorectal cancer (CRC) aims to decrease CRC incidence and mortality. Biennial fecal immunochemical test screening started in the Netherlands in 2014 for individuals 55-75 years of age. This study investigated the effect of screening on stage-specific incidence, with focus on stage III and IV CRC.

METHODS

Inhabitants diagnosed with CRC in 2009-2018 were included. CRC incidence per stage, year, and detection method (ie, screen-detected vs clinically detected) was evaluated. Patient, tumor, and treatment characteristics, and survival of patients with stage III and IV CRC, were compared according to the detection method.

RESULTS

Included were 140,649 CRCs in 136,882 patients. An initial peak of stage I-III CRC diagnoses after initiation of screening was followed by a continuous decrease within screening-eligible ages. Total CRC incidence remained higher than before screening, although stage II and IV CRC incidence decreased below prescreening levels. Screen-detected CRCs were significantly more frequently located in the left-sided colon (stage III; 43.7% vs 30.9%; stage IV: 45.1% vs 36.1%), and the primary tumor resection rate was higher (stage III colon: 99.8% vs 99.0%, rectum: 97.3% vs 89.7%; stage IV colon: 65.4% vs 56.6%, rectum: 47.3% vs 33.5%). Patients with screen-detected stage IV CRC had significantly more often single-organ metastases (74.5% vs 57.0%; P < .001) and more frequently received treatment with curative intent (colon: 41.3% vs 27.4%; rectum: 33.8% vs 24.6%). Overall survival significantly improved for patients with screen-detected CRCs (stage III: P < .001; stage IV: P < .001).

CONCLUSIONS

Five years after the start of a nationwide CRC screening program, a decrease in stage II and IV CRC incidence was observed. Patients with screen-detected stage III and stage IV CRC had less extensive disease and improved survival compared with those with clinically detected CRC.

Diffuse reflection spectroscopy at the fingertip: design and performance of a compact side-firing probe for tissue discrimination during colorectal cancer surgery

Optical technologies are widely used for tissue sensing purposes. However, maneuvering conventional probe designs with flat-tipped fibers in narrow spaces can be challenging, for instance during pelvic colorectal cancer surgery. In this study, a compact side-firing fiber probe was developed for tissue discrimination during colorectal cancer surgery using diffuse reflectance spectroscopy. The optical behavior was compared to flat-tipped fibers using both Monte Carlo simulations and experimental phantom measurements. The tissue classification performance was examined using freshly excised colorectal cancer specimens. Using the developed probe and classification algorithm, an accuracy of 0.92 was achieved for discriminating tumor tissue from healthy tissue.

Comparison of preprocessing techniques to reduce nontissue-related variations in hyperspectral reflectance imaging

SIGNIFICANCE

Hyperspectral reflectance imaging can be used in medicine to identify tissue types, such as tumor tissue. Tissue classification algorithms are developed based on, e.g., machine learning or principle component analysis. For the development of these algorithms, data are generally preprocessed to remove variability in data not related to the tissue itself since this will improve the performance of the classification algorithm. In hyperspectral imaging, the measured spectra are also influenced by reflections from the surface (glare) and height variations within and between tissue samples.

AIM

To compare the ability of different preprocessing algorithms to decrease variations in spectra induced by glare and height differences while maintaining contrast based on differences in optical properties between tissue types.

APPROACH

We compare eight preprocessing algorithms commonly used in medical hyperspectral imaging: standard normal variate, multiplicative scatter correction, min-max normalization, mean centering, area under the curve normalization, single wavelength normalization, first derivative, and second derivative. We investigate conservation of contrast stemming from differences in: blood volume fraction, presence of different absorbers, scatter amplitude, and scatter slope-while correcting for glare and height variations. We use a similarity metric, the overlap coefficient, to quantify contrast between spectra. We also investigate the algorithms for clinical datasets from the colon and breast.

CONCLUSIONS

Preprocessing reduces the overlap due to glare and distance variations. In general, the algorithms standard normal variate, min-max, area under the curve, and single wavelength normalization are the most suitable to preprocess data used to develop a classification algorithm for tissue classification. The type of contrast between tissue types determines which of these four algorithms is most suitable.

Discriminating healthy from tumor tissue in breast lumpectomy specimens using deep learning-based hyperspectral imaging

Achieving an adequate resection margin during breast-conserving surgery remains challenging due to the lack of intraoperative feedback. Here, we evaluated the use of hyperspectral imaging to discriminate healthy tissue from tumor tissue in lumpectomy specimens. We first used a dataset obtained on tissue slices to develop and evaluate three convolutional neural networks. Second, we fine-tuned the networks with lumpectomy data to predict the tissue percentages of the lumpectomy resection surface. A MCC of 0.92 was achieved on the tissue slices and an RMSE of 9% on the lumpectomy resection surface. This shows the potential of hyperspectral imaging to classify the resection margins of lumpectomy specimens.

Use of Image-Guided Surgical Navigation during Resection of Locally Recurrent Rectal Cancer

Surgery for locally recurrent rectal cancer (LRRC) presents several challenges, which is why the percentage of inadequate resections of these tumors is high. In this exploratory study, we evaluate the use of image-guided surgical navigation during resection of LRRC. Patients who were scheduled to undergo surgical resection of LRRC who were deemed by the multidisciplinary team to be at a high risk of inadequate tumor resection were selected to undergo surgical navigation. The risk of inadequate surgery was further determined by the proximity of the tumor to critical anatomical structures. Workflow characteristics of the surgical navigation procedure were evaluated, while the surgical outcome was determined by the status of the resection margin. In total, 20 patients were analyzed. For all procedures, surgical navigation was completed successfully and demonstrated to be accurate, while no complications related to the surgical navigation were discerned. Radical resection was achieved in 14 cases (70%). In five cases (25%), a tumor-positive resection margin (R1) was anticipated during surgery, as extensive radical resection was determined to be compromised. These patients all received intraoperative brachytherapy. In one case (5%), an unexpected R1 resection was performed. Surgical navigation during resection of LRRC is thus safe and feasible and enables accurate surgical guidance.

Layer thickness prediction and tissue classification in two-layered tissue structures using diffuse reflectance spectroscopy

During oncological surgery, it can be challenging to identify the tumor and establish adequate resection margins. This study proposes a new two-layer approach in which diffuse reflectance spectroscopy (DRS) is used to predict the top layer thickness and classify the layers in two-layered phantom and animal tissue. Using wavelet-based and peak-based DRS spectral features, the proposed method could predict the top layer thickness with an accuracy of up to 0.35 mm. In addition, the tissue types of the first and second layers were classified with an accuracy of 0.95 and 0.99. Distinguishing multiple tissue layers during spectral analyses results in a better understanding of more complex tissue structures encountered in surgical practice.

Nationwide registry study on trends in localization techniques and reoperation rates in non-palpable ductal carcinoma in situ and invasive breast cancer

BACKGROUND

There is a transition from wire-guided localization (WGL) of non-palpable breast cancer to other localization techniques. Multiple prospective studies have sought to establish superior clinical outcomes for radioactive-seed localization (RSL), but consistent and congruent evidence is missing.

METHODS

In this study, female patients with breast cancer operated with breast-conserving surgery after tumour localization of a non-palpable breast cancer or ductal carcinoma in situ (DCIS) were included. The cohort was identified from the nationwide Netherlands Breast Cancer Audit conducted between 2013 and 2018. Trends in localization techniques were analysed. Univariable and multivariable analyses were performed to assess the association between the localization technique and the probability of a reoperation.

RESULTS

A total of 28 370 patients were included in the study cohort. The use of RSL increased from 15.7 to 61.1 per cent during the study years, while WGL decreased from 75.4 to 31.6 per cent. The localization technique used (RSL versus WGL) was not significantly associated with the odds of a reoperation, regardless of whether the lesion was DCIS (odds ratio 0.96 (95 per cent c.i. 0.89 to 1.03; P = 0.281)) or invasive breast cancer (OR 1.02 (95 per cent c.i. 0.96 to 1.10; P = 0.518)).

CONCLUSION

RSL is rapidly replacing WGL as the preoperative localization technique in breast surgery. This large nationwide registry study found no association between the type of localization technique and the odds of having a reoperation, thus confirming the results of previous prospective cohort studies.

Surgical navigation for challenging recurrent or pretreated intra-abdominal and pelvic soft tissue sarcomas

BACKGROUND

This study assessed whether electromagnetic navigation can be of added value during resection of recurrent or post-therapy intra-abdominal/pelvic soft tissue sarcomas (STS) in challenging locations.

MATERIALS AND METHODS

Patients were included in a prospective navigation study. A pre-operatively 3D roadmap was made and tracked using electromagnetic reference markers. During the operation, an electromagnetic pointer was used for the localization of the tumor/critical anatomical structures. The primary endpoint was feasibility, secondary outcomes were safety and usability.

RESULTS

Nine patients with a total of 12 tumors were included, 7 patients with locally recurrent sarcoma. Three patients received neoadjuvant radiotherapy and three other patients received neoadjuvant systemic treatment. The median tumor size was 4.6 cm (2.4-10.4). The majority of distances from tumor to critical anatomical structures was <0.5 cm. The tumors were localized using the navigation system without technical or safety issues. Despite the challenging nature of these resections, 89% were R0 resections, with a median blood loss of 100 ml (20-1050) and one incident of vascular damage. Based on the survey, surgeons stated navigation resulted in shorter surgery time and made the resections easier.

CONCLUSION

Electromagnetic navigation facilitates resections of challenging lower intra-abdominal/pelvic STS and might be of added value.

Technical note: Validation of 3D ultrasound for image registration during oncological liver surgery

PURPOSE

Registration of pre- and intraoperative images is a crucial step of surgical liver navigation, where rigid registration of vessel centerlines is currently commonly used. When using 3D ultrasound (US), accuracy during navigation might be influenced by the size of the intraoperative US volume, yet the relationship between registration accuracy and US volume size is understudied. In this study, we specify an optimal 3D US volume size for registration using varying volumes of liver vasculature. While previous studies measured accuracy at registered fiducials, in this work, accuracy is determined at the target lesion which is clinically the most relevant structure.

METHODS

Three-dimensional US volumes were acquired in 14 patients after laparotomy and liver mobilization. Manual segmentation of vasculature and centerline extraction was performed. Intraoperative and preoperative vasculature centerlines were registered with coherent point drift, using different sub-volumes (sphere with radius r = 30, 40, …, 120 mm). Accuracy was measured by fiducial registration error (FRE) between vessel centerlines and target registration error (TRE) at the center of the target lesion.

RESULTS

The lowest FRE for vessel registration was reached with r = 50 mm (6.5 ± 2.5 mm), the highest with r = 120 mm (7.1 ± 2.1 mm). Clinical accuracy at the target lesion, resulted most accurate (TRE = 8.8 ± 5.0 mm) in sub-volumes with a radius of 50 mm. Smaller US sub-volumes resulted in lower average TREs when compared to larger US sub-volumes (Pearson's correlation coefficient R = 0.91, p < 0.001).

CONCLUSION

Our results indicate that there is a linear correlation between US volume size and registration accuracy at the tumor. Volumes with radii of 50 mm around the target lesion yield higher accuracy (p < 0.05) (Trial number IRBd18032, 11 September 2018).

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.

Optical tissue measurements of invasive carcinoma and ductal carcinoma in situ for surgical guidance

Background

Although the incidence of positive resection margins in breast-conserving surgery has decreased, both incomplete resection and unnecessary large resections still occur. This is especially the case in the surgical treatment of ductal carcinoma in situ (DCIS). Diffuse reflectance spectroscopy (DRS), an optical technology based on light tissue interactions, can potentially characterize tissue during surgery thereby guiding the surgeon intraoperatively. DRS has shown to be able to discriminate pure healthy breast tissue from pure invasive carcinoma (IC) but limited research has been done on (1) the actual optical characteristics of DCIS and (2) the ability of DRS to characterize measurements that are a mixture of tissue types.

Methods

In this study, DRS spectra were acquired from 107 breast specimens from 107 patients with proven IC and/or DCIS (1488 measurement locations). With a generalized estimating equation model, the differences between the DRS spectra of locations with DCIS and IC and only healthy tissue were compared to see if there were significant differences between these spectra. Subsequently, different classification models were developed to be able to predict if the DRS spectrum of a measurement location represented a measurement location with “healthy” or “malignant” tissue. In the development and testing of the models, different definitions for “healthy” and “malignant” were used. This allowed varying the level of homogeneity in the train and test data.

Results

It was found that the optical characteristics of IC and DCIS were similar. Regarding the classification of tissue with a mixture of tissue types, it was found that using mixed measurement locations in the development of the classification models did not tremendously improve the accuracy of the classification of other measurement locations with a mixture of tissue types. The evaluated classification models were able to classify measurement locations with > 5% malignant cells with a Matthews correlation coefficient of 0.41 or 0.40. Some models showed better sensitivity whereas others had better specificity.

Conclusion

The results suggest that DRS has the potential to detect malignant tissue, including DCIS, in healthy breast tissue and could thus be helpful for surgical guidance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01436-5.

[Wearing surgical masks in the operation theatre: yes or no?]

OBJECTIVE

In the Netherlands, the surgical mask is part of the standard surgical attire even for the non-sterile personnel in the operation theatre. Solid evidence on the effect on postoperative infection rates is missing. Due to a national scarcity in surgical masks during the first wave of the COVID-19 crisis the usage of these masks was decreased. In our tertiary referral centre for Surgical Oncology, this led to the decision that, for a period of ten weeks, the surgical masks were only being used by the sterile surgical team and not by non-sterile operation theatre personnel. This retrospective study evaluates the influence of this intervention in terms of postoperative wound infection rates.

DESIGN

Retrospective cohort study.

METHOD

Consecutive patients undergoing surgery during the first COVID-19 wave (2-3-2020 until 11-05-2020) were compared with patients undergoing surgery in the same period a year earlier. Patients undergoing surgery for soft-tissue malignancies were included. Intra-abdominal surgery was excluded. Primary outcome measurement was wound infection rate within 30 days following surgery. Secondary, a cost reduction analysis was made.

RESULTS

In the COVID-19 wave, a total of 219 patients underwent surgery for soft-tissue malignancies, compared to 241 a year earlier. The incidence of postoperative wound infection was 58/460 (12.6%) for the total cohort. There was no difference in infection rate between the COVID-19 period and the same period in 2019; 25/219 (11,4%; 95% CI: 7,8-16,4)) vs. 33/241 (13,7%; 95% CI: 9,8-18,6), p = 0,46) respectively. During the COVID-19 wave, a total of 6.400 of surgical masks were used by the personnel in the operation theatre complex, compared to a total of 11.000 in the same period in 2019. This resulted in a reduction of 42% in usage of surgical masks.

CONCLUSION

Based on this mono-centric, explorative retrospective cohort study, it seems that omitting the surgical mask for the non-sterile operation theatre personnel does not influence the postoperative wound infection rate. Despite the fact that our sample size is small, the impressive reduction in usage of 42% demands further research initiatives on a larger scale.

Assessment of the deep resection margin during oral cancer surgery: A systematic review

The main challenge for radical resection in oral cancer surgery is to obtain adequate resection margins. Especially the deep margin, which can only be estimated based on palpation during surgery, is often reported inadequate. To increase the percentage of radical resections, there is a need for a quick, easy, minimal invasive method, which assesses the deep resection margin without interrupting or prolonging surgery. This systematic review provides an overview of technologies that are currently being studied with the aim of fulfilling this demand. A literature search was conducted through the databases Medline, Embase and the Cochrane Library. A total of 62 studies were included. The results were categorized according to the type of technique: 'Frozen Section Analysis', 'Fluorescence', 'Optical Imaging', 'Conventional imaging techniques', and 'Cytological assessment'. This systematic review gives for each technique an overview of the reported performance (accuracy, sensitivity, specificity, positive predictive value, negative predictive value, or a different outcome measure), acquisition time, and sampling depth. At the moment, the most prevailing technique remains frozen section analysis. In the search for other assessment methods to evaluate the deep resection margin, some technologies are very promising for future use when effectiveness has been shown in larger trials, e.g., fluorescence (real-time, sampling depth up to 6 mm) or optical techniques such as hyperspectral imaging (real-time, sampling depth few mm) for microscopic margin assessment and ultrasound (less than 10 min, sampling depth several cm) for assessment on a macroscopic scale.

Tongue Tumor Detection in Hyperspectral Images Using Deep Learning Semantic Segmentation

OBJECTIVE

The utilization of hyperspectral imaging (HSI) in real-time tumor segmentation during a surgery have recently received much attention, but it remains a very challenging task.

METHODS

In this work, we propose semantic segmentation methods, and compare them with other relevant deep learning algorithms for tongue tumor segmentation. To the best of our knowledge, this is the first work using deep learning semantic segmentation for tumor detection in HSI data using channel selection, and accounting for more spatial tissue context, and global comparison between the prediction map, and the annotation per sample. Results, and Conclusion: On a clinical data set with tongue squamous cell carcinoma, our best method obtains very strong results of average dice coefficient, and area under the ROC-curve of [Formula: see text], and [Formula: see text], respectively on the original spatial image size. The results show that a very good performance can be achieved even with a limited amount of data. We demonstrate that important information regarding tumor decision is encoded in various channels, but some channel selection, and filtering is beneficial over the full spectra. Moreover, we use both visual (VIS), and near-infrared (NIR) spectrum, rather than commonly used only VIS spectrum; although VIS spectrum is generally of higher significance, we demonstrate NIR spectrum is crucial for tumor capturing in some cases.

SIGNIFICANCE

The HSI technology augmented with accurate deep learning algorithms has a huge potential to be a promising alternative to digital pathology or a doctors' supportive tool in real-time surgeries.

Electromagnetic surgical navigation in patients undergoing mandibular surgery

The purpose of this study was to evaluate the feasibility of electromagnetic (EM) navigation for guidance on osteotomies in patients undergoing oncologic mandibular surgery. Preoperatively, a 3D rendered model of the mandible was constructed from diagnostic computed tomography (CT) images. Cutting guides and patient specific reconstruction plates were designed and printed for intraoperative use. Intraoperative patient registration was performed using a cone beam CT scan (CBCT). The location of the mandible was tracked with an EM sensor fixated to the mandible. The real-time location of both the mandible and a pointer were displayed on the navigation system. Accuracy measurements were performed by pinpointing four anatomical landmarks and four landmarks on the cutting guide using the pointer on the patient and comparing these locations to the corresponding locations on the CBCT. Differences between actual and virtual locations were expressed as target registration error (TRE). The procedure was performed in eleven patients. TREs were 3.2 ± 1.1 mm and 2.6 ± 1.5 mm using anatomical landmarks and landmarks on the cutting guide, respectively. The navigation procedure added on average half an hour to the duration of the surgery. This is the first study that reports on the accuracy of EM navigation in patients undergoing mandibular surgery.

Clinical Implementation of In-House Developed MR-Based Patient-Specific 3D Models of Liver Anatomy

Knowledge of patient-specific liver anatomy is key to patient safety during major hepatobiliary surgery. Three-dimensional (3D) models of patient-specific liver anatomy based on diagnostic MRI images can provide essential vascular and biliary anatomical insight during surgery. However, a method for generating these is not yet publicly available. This paper describes how these 3D models of the liver can be generated using open source software, and then subsequently integrated into a sterile surgical environment. The most common image quality aspects that degrade the quality of the 3D models as well possible ways of eliminating these are also discussed. Per patient, a single diagnostic multiphase MRI scan with hepatospecific contrast agent was used for automated segmentation of liver contour, arterial, portal, and venous anatomy, and the biliary tree. Subsequently, lesions were delineated manually. The resulting interactive 3D model could be accessed during surgery on a sterile covered tablet. Up to now, such models have been used in 335 surgical procedures. Their use simplified the surgical treatment of patients with a high number of liver metastases and contributed to the localization of vanished lesions in cases of a radiological complete response to neoadjuvant treatment. They facilitated perioperative verification of the relationship of tumors and the surrounding vascular and biliary anatomy, and eased decision-making before and during surgery.

Nonlinear multispectral imaging for tumor delineation

SIGNIFICANCE

In breast-preserving tumor surgery, the inspection of the excised tissue boundaries for tumor residue is too slow to provide feedback during the surgery. The discovery of positive margins requires a new surgery which is difficult and associated with low success. If the re-excision could be done immediately this is believed to improve the success rate considerably.

AIM

Our aim is for a fast microscopic analysis that can be done directly on the excised tissue in or near the operating theatre.

APPROACH

We demonstrate the combination of three nonlinear imaging techniques at selected wavelengths to delineate tumor boundaries. We use hyperspectral coherent anti-Stokes Raman scattering (CARS), second harmonic generation (SHG), and two-photon excited fluorescence (TPF) on excised patient tissue.

RESULTS

We show the discriminatory power of each of the signals and demonstrate a sensitivity of 0.87 and a specificity of 0.95 using four CARS wavelengths in combination with SHG and TPF. We verify that the information is independent of sample treatment.

CONCLUSIONS

Nonlinear multispectral imaging can be used to accurately determine tumor boundaries. This demonstration using microscopy in the epi-direction directly on thick tissue slices brings this technology one step closer to clinical implementation.

Association of Image-Guided Navigation With Complete Resection Rate in Patients With Locally Advanced Primary and Recurrent Rectal Cancer: A Nonrandomized Controlled Trial

IMPORTANCE

The percentage of tumor-positive surgical resection margin rates in patients treated for locally advanced primary or recurrent rectal cancer is high. Image-guided navigation may improve complete resection rates.

OBJECTIVE

To ascertain whether image-guided navigation during rectal cancer resection improves complete resection rates compared with surgical procedures without navigation.

DESIGN, SETTING, AND PARTICIPANTS

This prospective single-center nonrandomized controlled trial was conducted at the Netherlands Cancer Institute-Antoni van Leeuwenhoek in Amsterdam, the Netherlands. The prospective or navigation cohort included adult patients with locally advanced primary or recurrent rectal cancer who underwent resection with image-guided navigation between February 1, 2016, and September 30, 2019, at the tertiary referral hospital. Clinical results of this cohort were compared with results of the historical cohort, which was composed of adult patients who received rectal cancer resection without image-guided navigation between January 1, 2009, and December 31, 2015.

INTERVENTION

Rectal cancer resection with image-guided navigation.

MAIN OUTCOMES AND MEASURES

The primary end point was the complete resection rate, measured by the amount of tumor-negative resection margin rates. Secondary outcomes were safety and usability of the system. Safety was evaluated by the number of navigation system-associated surgical adverse events. Usability was assessed from responses to a questionnaire completed by the participating surgeons after each procedure.

RESULTS

In total, 33 patients with locally advanced or recurrent rectal cancer were included (23 men [69.7%]; median [interquartile range] age at start of treatment, 61 [55.0-69.0] years). With image-guided navigation, a radical resection (R0) was achieved in 13 of 14 patients (92.9%; 95% CI, 66.1%-99.8%) after primary resection of locally advanced tumors and in 15 of 19 patients (78.9%; 95% CI, 54.4%-94.0%) after resection of recurrent rectal cancer. No navigation system-associated complications occurred before or during surgical procedures. In the historical cohort, 142 patients who underwent resection without image-guided navigation were included (95 men [66.9%]; median [interquartile range] age at start of treatment, 64 [55.0-70.0] years). In these patients, an R0 resection was accomplished in 85 of 101 patients (84.2%) with locally advanced rectal cancer and in 20 of 41 patients (48.8%) with recurrent rectal cancer. A significant difference was found between the navigation and historical cohorts after recurrent rectal cancer resection (21.1% vs 51.2%; P = .047). For locally advanced primary tumor resection, the difference was not significant (7.1% vs 15.8%; P = .69). Surgeons stated in completed questionnaires that the navigation system improved decisiveness and helped with tumor localization.

CONCLUSIONS AND RELEVANCE

Findings of this study suggest that image-guided navigation used during rectal cancer resection is safe and intuitive and may improve tumor-free resection margin rates in recurrent rectal cancer.

TRIAL REGISTRATION

Netherlands Trial Register Identifier: NTR7184.

Accurate surgical navigation with real-time tumor tracking in cancer surgery

In the past decades, image-guided surgery has evolved rapidly. In procedures with a relatively fixed target area, like neurosurgery and orthopedics, this has led to improved patient outcomes. In cancer surgery, intraoperative guidance could be of great benefit to secure radical resection margins since residual disease is associated with local recurrence and poor survival. However, most tumor lesions are mobile with a constantly changing position. Here, we present an innovative technique for real-time tumor tracking in cancer surgery. In this study, we evaluated the feasibility of real-time tumor tracking during rectal cancer surgery. The application of real-time tumor tracking using an intraoperative navigation system is feasible and safe with a high median target registration accuracy of 3 mm. This technique allows oncological surgeons to obtain real-time accurate information on tumor location, as well as critical anatomical information. This study demonstrates that real-time tumor tracking is feasible and could potentially decrease positive resection margins and improve patient outcome.

A workflow for automated segmentation of the liver surface, hepatic vasculature and biliary tree anatomy from multiphase MR images

Accurate assessment of 3D models of patient-specific anatomy of the liver, including underlying hepatic and biliary tree, is critical for preparation and safe execution of complex liver resections, especially due to high variability of biliary and hepatic artery anatomies. Dynamic MRI with hepatospecific contrast agents is currently the only type of diagnostic imaging that provides all anatomical information required for generation of such a model, yet there is no information in the literature on how the complete 3D model can be generated automatically. In this work, a new automated segmentation workflow for extraction of patient-specific 3D model of the liver, hepatovascular and biliary anatomy from a single multiphase MRI acquisition is developed and quantitatively evaluated. The workflow incorporates course 4D k-means clustering estimation and geodesic active contour refinement of the liver boundary, based on organ's characteristic uptake of gadolinium contrast agents overtime. Subsequently, hepatic vasculature and biliary ducts segmentations are performed using multiscale vesselness filters. The algorithm was evaluated using 15 test datasets of patients with liver malignancies of various histopathological types. It showed good correlation with expert manual segmentation, resulting in an average of 1.76 ± 2.44 mm Hausdorff distance for the liver boundary, and 0.58 ± 0.72 and 1.16 ± 1.98 mm between centrelines of biliary ducts and liver veins, respectively. A workflow for automatic segmentation of the liver, hepatic vasculature and biliary anatomy from a single diagnostic MRI acquisition was developed. This enables automated extraction of 3D models of patient-specific liver anatomy, and may facilitating better perception of organ's anatomy during preparation and execution of liver surgeries. Additionally, it may help to reduce the incidence of intraoperative biliary duct damage due to an unanticipated variation in the anatomy.

Using Diffuse Reflectance Spectroscopy to Distinguish Tumor Tissue From Fibrosis in Rectal Cancer Patients as a Guide to Surgery

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. © 2019 Wiley Periodicals, Inc.

Optimizing algorithm development for tissue classification in colorectal cancer based on diffuse reflectance spectra

Diffuse reflectance spectroscopy can be used in colorectal cancer surgery for tissue classification. The main challenge in the classification task is to separate healthy colorectal wall from tumor tissue. In this study, four normalization techniques, four feature extraction methods and five classifiers are applied to nine datasets, to obtain the optimal method to separate spectra measured on healthy colorectal wall from spectra measured on tumor tissue. All results are compared to the use of the entire non-normalized spectra. It is found that the most optimal classification approach is to apply a feature extraction method on non-normalized spectra combined with support vector machine or neural network classifier.

Influence of neoadjuvant chemotherapy on diffuse reflectance spectra of tissue in breast surgery specimens

Diffuse reflectance spectroscopy (DRS) can discriminate different tissue types based on optical characteristics. Since this technology has the ability to detect tumor tissue, several groups have proposed to use DRS for margin assessment during breast-conserving surgery for breast cancer. Nowadays, an increasing number of patients with breast cancer are being treated by neoadjuvant chemotherapy. Limited research has been published on the influence of neoadjuvant chemotherapy on the optical characteristics of the tissue. Hence, it is unclear whether margin assessment based on DRS is feasible in this specific group of patients. We investigate whether there is an effect of neoadjuvant chemotherapy on optical measurements of breast tissue. To this end, DRS measurements were performed on 92 ex-vivo breast specimens from 92 patients, treated with neoadjuvant chemotherapy and without neoadjuvant chemotherapy. Generalized estimating equation (GEE) models were generated, comparing the measurements of patients with and without neoadjuvant chemotherapy in datasets of different tissue types using a significance level of 5%. As input for the GEE models, either the intensity at a specific wavelength or a fit parameter, derived from the spectrum, was used. In the evaluation of the intensity, no influence of neoadjuvant chemotherapy was found, since none of the wavelengths were significantly different between the measurements with and the measurements without neoadjuvant chemotherapy in any of the datasets. These results were confirmed by the analysis of the fit parameters, which showed a significant difference for the amount of collagen in only one dataset. All other fit parameters were not significant for any of the datasets. These findings may indicate that assessment of the resection margin with DRS is also feasible in the growing population of breast cancer patients who receive neoadjuvant chemotherapy. However, it is possible that we did not detect neoadjuvant chemotherapy effect in the some of the datasets due to the small number of measurements in those datasets.

Imaging depth variations in hyperspectral imaging: Development of a method to detect tumor up to the required tumor-free margin width

Hyperspectral imaging is a promising technique for resection margin assessment during cancer surgery. Thereby, only a specific amount of the tissue below the resection surface, the clinically defined margin width, should be assessed. Since the imaging depth of hyperspectral imaging varies with wavelength and tissue composition, this can have consequences for the clinical use of hyperspectral imaging as margin assessment technique. In this study, a method was developed that allows for hyperspectral analysis of resection margins in breast cancer. This method uses the spectral slope of the diffuse reflectance spectrum at wavelength regions where the imaging depth in tumor and healthy tissue is equal. Thereby, tumor can be discriminated from healthy breast tissue while imaging up to a similar depth as the required tumor-free margin width of 2 mm. Applying this method to hyperspectral images acquired during surgery would allow for robust margin assessment of resected specimens. In this paper, we focused on breast cancer, but the same approach can be applied to develop a method for other types of cancer.

Tissue diagnosis during colorectal cancer surgery using optical sensing: an in vivo study

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.

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 (450-1650 nm). 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.

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.

The future of surgical oncology

Fast moving specialty

Surgical removal of the index node marked using magnetic seed localization to assess response to neoadjuvant immunotherapy in patients with stage III melanoma

This pilot study explored the value of localized index node removal after neoadjuvant immunotherapy in patients with stage III melanoma, for use as a response indicator to guide the extent of completion lymph node dissection. Promising technology.

Hyperspectral imaging for tissue classification, a way toward smart laparoscopic colorectal surgery

In the last decades, laparoscopic surgery has become the gold standard in patients with colorectal cancer. To overcome the drawback of reduced tactile feedback, real-time tissue classification could be of great benefit. In this ex vivo study, hyperspectral imaging (HSI) was used to distinguish tumor tissue from healthy surrounding tissue. A sample of fat, healthy colorectal wall, and tumor tissue was collected per patient and imaged using two hyperspectral cameras, covering the wavelength range from 400 to 1700 nm. The data were randomly divided into a training (75%) and test (25%) set. After feature reduction, a quadratic classifier and support vector machine were used to distinguish the three tissue types. Tissue samples of 32 patients were imaged using both hyperspectral cameras. The accuracy to distinguish the three tissue types using both hyperspectral cameras was 0.88 (STD  =  0.13) on the test dataset. When the accuracy was determined per patient, a mean accuracy of 0.93 (STD  =  0.12) was obtained on the test dataset. This study shows the potential of using HSI in colorectal cancer surgery for fast tissue classification, which could improve clinical outcome. Future research should be focused on imaging entire colon/rectum specimen and the translation of the technique to an intraoperative setting.

Towards the use of diffuse reflectance spectroscopy for real-time in vivo detection of breast cancer during surgery

Background

Breast cancer surgeons struggle with differentiating healthy tissue from cancer at the resection margin during surgery. We report on the feasibility of using diffuse reflectance spectroscopy (DRS) for real-time in vivo tissue characterization.

Methods

Evaluating feasibility of the technology requires a setting in which measurements, imaging and pathology have the best possible correlation. For this purpose an optical biopsy needle was used that had integrated optical fibers at the tip of the needle. This approach enabled the best possible correlation between optical measurement volume and tissue histology. With this optical biopsy needle we acquired real-time DRS data of normal tissue and tumor tissue in 27 patients that underwent an ultrasound guided breast biopsy procedure. Five additional patients were measured in continuous mode in which we obtained DRS measurements along the entire biopsy needle trajectory. We developed and compared three different support vector machine based classification models to classify the DRS measurements.

Results

With DRS malignant tissue could be discriminated from healthy tissue. The classification model that was based on eight selected wavelengths had the highest accuracy and Matthews Correlation Coefficient (MCC) of 0.93 and 0.87, respectively. In three patients that were measured in continuous mode and had malignant tissue in their biopsy specimen, a clear transition was seen in the classified DRS measurements going from healthy tissue to tumor tissue. This transition was not seen in the other two continuously measured patients that had benign tissue in their biopsy specimen.

Conclusions

It was concluded that DRS is feasible for integration in a surgical tool that could assist the breast surgeon in detecting positive resection margins during breast surgery.

Trail registration NIH US National Library of Medicine–clinicaltrails.gov, NCT01730365. Registered: 10/04/2012 https://clinicaltrials.gov/ct2/show/study/NCT01730365

In vivo nerve identification in head and neck surgery using diffuse reflectance spectroscopy

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.

Toward complete oral cavity cancer resection using a handheld diffuse reflectance spectroscopy probe

This ex-vivo study evaluates the feasibility of diffuse reflectance spectroscopy (DRS) for discriminating tumor from healthy tissue, with the aim to develop a technology that can assess resection margins for the presence of tumor cells during oral cavity cancer surgery. Diffuse reflectance spectra were acquired on fresh surgical specimens from 28 patients with oral cavity squamous cell carcinoma. The spectra (400 to 1600 nm) were detected after illuminating tissue with a source fiber at 0.3-, 0.7-, 1.0-, and 2.0-mm distances from a detection fiber, obtaining spectral information from different sampling depths. The spectra were correlated with histopathology. A total of 76 spectra were obtained from tumor tissue and 110 spectra from healthy muscle tissue. The first- and second-order derivatives of the spectra were calculated and a classification algorithm was developed using fivefold cross validation with a linear support vector machine. The best results were obtained by the reflectance measured with a 1-mm source-detector distance (sensitivity, specificity, and accuracy are 89%, 82%, and 86%, respectively). DRS can accurately discriminate tumor from healthy tissue in an ex-vivo setting using a 1-mm source-detector distance. Accurate validation methods are warranted for larger sampling depths to allow for guidance during oral cavity cancer excision.

Tumor Resection Margin Definitions in Breast-Conserving Surgery: Systematic Review and Meta-analysis of the Current Literature

Worldwide, various guidelines recommend what constitutes an adequate margin of excision for invasive breast cancer or for ductal carcinoma-in-situ (DCIS). We evaluated the use of different tumor resection margin guidelines and investigated their impact on positive margin rates (PMR) and reoperation rates (RR). Thirteen guidelines reporting on the extent of a positive margin were reviewed along with 31 studies, published between 2011 and 2016, reporting on a well-defined PMR. Studies were categorized according to the margin definition. Pooled PMR and RR were determined with random-effect models. For invasive breast cancer, most guidelines recommend a positive margin of tumor on ink. However, definitions of reported positive margins in the clinic vary from more than focally positive to the presence of tumor cells within 3 to 5 mm from the resection surface. Within the studies analyzed (59,979 patients), pooled PMRs for invasive breast cancer ranged from 9% to 36% and pooled RRs from 77% to 99%. For DCIS, guidelines vary between no DCIS on the resection surface to DCIS cells found within a distance of 2 mm from the resection edge. Pooled PMRs for DCIS varied from 4% to 23% (840 patients). Given the differences in tumor margin definition between countries worldwide, quality control data expressed as PMR or RR should be interpreted with caution. Furthermore, the overall definition for positive resection margins for both invasive disease and DCIS seems to have become more liberal.

Nerve detection during surgery: optical spectroscopy for peripheral nerve localization

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.

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.