In vivo characterization of colorectal metastases in human liver using diffuse reflectance spectroscopy: toward guidance in oncological procedures

Tissue-probe contact assessment during robotic surgery using single-fiber reflectance spectroscopy

The introduction of robotic surgery has improved minimally invasive surgery, and now robotic surgery is used in several areas of surgical oncology. Several optical techniques can be used to discriminate cancer from healthy tissue based on their optical properties. These technologies can also be employed with a small fiber-optic probe during minimally invasive surgery; however, for acquiring reliable measurements, some optical techniques require the fiber-optic probe to be in direct contact with the tissue. The lack of tactile feedback in robotic surgery makes assessing tissue-probe contact suitable for optical contact measurements challenging for the surgeon. In this study, we investigated the use of single fiber reflectance (SFR) to determine tissue-probe contact adequately. A machine learning-based algorithm was developed to classify if direct tissue-probe contact was present during the measurement in an ex-vivo tissue setup. Using this classification algorithm, an average accuracy of 93.9% was achieved for assessing probe-tissue contact, suggesting that this technique can be utilized to assess tissue-probe contact in an in vivo clinical setting.

Enhancing Intraoperative Tissue Identification: Investigating a Smart Electrosurgical Knife's Functionality During Electrosurgery

OBJECTIVE

Detecting the cancerous growth margin and achieving a negative margin is one of the challenges that surgeons face during cancer procedures. A smart electrosurgical knife with integrated optical fibers has been designed previously to enable real-time use of diffuse reflectance spectroscopy for intraoperative margin assessment. In this paper, the thermal effect of the electrosurgical knife on tissue sensing is investigated.

METHODS

Porcine tissues and phantoms were used to investigate the performance of the smart electrosurgical knife after electrosurgery. The fat-to-water content ratio (F/W-ratio) served as the discriminative parameter for distinguishing tissues and tissue mimicking phantoms with varying fat content. The F/W-ratio of tissues and phantoms was measured with the smart electrosurgical knife before and after 14 minutes of electrosurgery. Additionally, a layered porcine tissue and phantom were sliced and measured from top to bottom with the smart electrosurgical knife.

RESULTS

Mapping the thermal activity of the electrosurgical knife's electrode during animal tissue electrosurgery revealed temperatures exceeding 400 °C. Electrosurgery for 14 minutes had no impact on the device's accurate detection of the F/W-ratio. The smart electrosurgical knife enables real-time tissue detection and predicts the fat content of the next layer from 4 mm ahead.

CONCLUSION

The design of the smart electrosurgical knife outlined in this paper demonstrates its potential utility for tissue detection during electrosurgery.

SIGNIFICANCE

In the future, the smart electrosurgical knife could be a valuable intraoperative margin assessment tool, aiding surgeons in detecting tumor borders and achieving negative margins.

Click-on fluorescence detectors: using robotic surgical instruments to characterize molecular tissue aspects

Fluorescence imaging is increasingly being implemented in surgery. One of the drawbacks of its application is the need to switch back-and-forth between fluorescence- and white-light-imaging settings and not being able to dissect safely under fluorescence guidance. The aim of this study was to engineer 'click-on' fluorescence detectors that transform standard robotic instruments into molecular sensing devices that enable the surgeon to detect near-infrared (NIR) fluorescence in a white-light setting. This NIR-fluorescence detector setup was engineered to be press-fitted onto standard forceps instruments of the da Vinci robot. Following system characterization in a phantom setting (i.e., spectral properties, sensitivity and tissue signal attenuation), the performance with regard to different clinical indocyanine green (ICG) indications (e.g., angiography and lymphatic mapping) was determined via robotic surgery in pigs. To evaluate in-human applicability, the setup was also used for ICG-containing lymph node specimens from robotic prostate cancer surgery. The resulting Click-On device allowed for NIR ICG signal identification down to a concentration of 4.77 × 10^-6 mg/ml. The fully assembled system could be introduced through the trocar and grasping, and movement abilities of the instrument were preserved. During surgery, the system allowed for the identification of blood vessels and assessment of vascularization (i.e., bowel, bladder and kidney), as well as localization of pelvic lymph nodes. During human specimen evaluation, it was able to distinguish sentinel from non-sentinel lymph nodes. With this introduction of a NIR-fluorescence Click-On sensing detector, a next step is made towards using surgical instruments in the characterization of molecular tissue aspects.

Distinguishing tumor from healthy tissue in human liver ex vivo using machine learning and multivariate analysis of diffuse reflectance spectra

The aim of this work was to evaluate the capability of diffuse reflectance spectroscopy to distinguish malignant liver tissues from surrounding tissues and to determine whether an extended wavelength range (450-1550 nm) offers any advantages over using the conventional wavelength range. Furthermore, multivariate analysis combined with a machine learning algorithm, either linear discriminant analysis or the more advanced support vector machine, was used to discriminate between and classify freshly excised human liver specimens from 18 patients. Tumors were distinguished from surrounding liver tissues with a sensitivity of 99%, specificity of 100%, classification rate of 100% and a Matthews correlation coefficient of 100% using the extended wavelength range and a combination of principal component analysis and support vector techniques. The results indicate that this technology may be useful in clinical applications for real-time tissue diagnostics of tumor margins where rapid classification is important.

Tissue-mimicking phantom materials with tunable optical properties suitable for assessment of diffuse reflectance spectroscopy during electrosurgery

Emerging intraoperative tumor margin assessment techniques require the development of more complex and reliable organ phantoms to assess the performance of the technique before its translation into the clinic. In this work, electrically conductive tissue-mimicking materials (TMMs) based on fat, water and agar/gelatin were produced with tunable optical properties. The composition of the phantoms allowed for the assessment of tumor margins using diffuse reflectance spectroscopy, as the fat/water ratio served as a discriminating factor between the healthy and malignant tissue. Moreover, the possibility of using polyvinyl alcohol (PVA) or transglutaminase in combination with fat, water and gelatin for developing TMMs was studied. The diffuse spectral response of the developed phantom materials had a good match with the spectral response of porcine muscle and adipose tissue, as well as in vitro human breast tissue. Using the developed recipe, anatomically relevant heterogeneous breast phantoms representing the optical properties of different layers of the human breast were fabricated using 3D-printed molds. These TMMs can be used for further development of phantoms applicable for simulating the realistic breast conserving surgery workflow in order to evaluate the intraoperative optical-based tumor margin assessment techniques during electrosurgery.

Optical percutaneous needle biopsy of the liver: a pilot animal and clinical study

This paper presents the results of the experiments which were performed using the optical biopsy system specially developed for in vivo tissue classification during the percutaneous needle biopsy (PNB) of the liver. The proposed system includes an optical probe of small diameter acceptable for use in the PNB of the liver. The results of the feasibility studies and actual tests on laboratory mice with inoculated hepatocellular carcinoma and in clinical conditions on patients with liver tumors are presented and discussed. Monte Carlo simulations were carried out to assess the diagnostic volume and to trace the sensing depth. Fluorescence and diffuse reflectance spectroscopy measurements were used to monitor metabolic and morphological changes in tissues. The tissue oxygen saturation was evaluated using a recently developed approach to neural network fitting of diffuse reflectance spectra. The Support Vector Machine Classification was applied to identify intact liver and tumor tissues. Analysis of the obtained results shows the high sensitivity and specificity of the proposed multimodal method. This approach allows to obtain information before the tissue sample is taken, which makes it possible to significantly reduce the number of false-negative biopsies.

State of the Art: Toward Improving Outcomes of Lung and Liver Tumor Biopsies in Clinical Trials-A Multidisciplinary Approach

PURPOSE

National Cancer Institute (NCI)-sponsored clinical trial network studies frequently require biopsy specimens for pharmacodynamic and molecular biomarker analyses, including paired pre- and post-treatment samples. The purpose of this meeting of NCI-sponsored investigators was to identify local institutional standard procedures found to ensure quantitative and qualitative specimen adequacy.

METHODS

NCI convened a conference on best biopsy practices, focusing on the clinical research community. Topics discussed were (1) criteria for specimen adequacy in the personalized medicine era, (2) team-based approaches to ensure specimen adequacy and quality control, and (3) risk considerations relevant to academic and community practitioners and their patients.

RESULTS AND RECOMMENDATIONS

Key recommendations from the convened consensus panel included (1) establishment of infrastructure for multidisciplinary biopsy teams with a formalized information capture process, (2) maintenance of standard operating procedures with regular team review, (3) optimization of tissue collection and yield methodology, (4) incorporation of needle aspiration and other newer techniques, and (5) commitment of stakeholders to use of guideline documents to increase awareness of best biopsy practices, with the goal of universally improving tumor biopsy practices.

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.

Diffuse reflectance spectroscopy of human liver tumor specimens - towards a tissue differentiating optical biopsy needle using light emitting diodes

Significant numbers of liver biopsies fail to yield representative tissue samples. This study was conducted to evaluate the ability of LED-based diffuse reflectance spectroscopy to discriminate tumors from liver parenchyma. Ex vivo spectra were acquired from malignant lesions and liver parenchyma of 32 patients who underwent liver resection using a white light source and several LEDs. Integrated spectra of two combined LEDs with emission peaks at 470 nm and 515 nm were classified with 98.4% sensitivity and 99.2% specificity. The promising results could yield to a simple handheld and cost-efficient tool for real-time tissue differentiation implemented in a biopsy needle.