Intraoperative tissue identification by mass spectrometric technologies

AbstractMass spectrometric (MS) approaches developed for tissue identification in surgical environments are reviewed. MS Imaging (MSI) techniques enable the direct analysis of human tissue and can be used as an alternative means for margin assessment. While MSI-based approaches were demonstrated to improve the examiner-related variance of the data, the time demand and the cost of these analyses remained high. Furthermore, the necessity of MS expertise for the clinical deployment of these techniques has hindered large-scale clinical testing. The advent of ‘ambient’ MS methods contributed to the application of MSI techniques in this field, however alternative methods have been developed for the direct analysis of tissue samples without sample preparation. One group of methods employs surgical tissue manipulation for ionization while the other one uses minimally invasive probes for sampling prior to ionization. The methods are summarised and compared with regard to the information delivered, turnaround time and tissue identification performance

Precise Hybrid-Actuation Robotic Fiber for Enhanced Cervical Disease Treatment

Treatment for high-grade precancerous cervical lesions and early-stage cancers, mainly affecting women of reproductive age, often involves fertility-sparing treatment methods. Commonly used local treatments for cervical precancers have shown the risk of leaving a positive cancer margin and engendering subsequent complications according to the precision and depth of excision. An intra-operative device that allows the careful excision of the disease while conserving healthy cervical tissue would potentially enhance such treatment. In this study, we developed a polymer-based robotic fiber measuring 150 mm in length and 1.7 mm in diameter, fabricated using a highly scalable fiber drawing technique. This robotic fiber utilizes a hybrid actuation mechanism, combining electrothermal and tendon-driven actuation mechanisms, thus enabling a maximum motion range of 46 mm from its origin with a sub-100 {\mu}m motion precision. We also developed control algorithms for the actuation methods of this robotic fiber, including predefined path control and telemanipulation, enabling coarse positioning of the fiber tip to the target area followed by a precise scan. The combination of a surgical laser fiber with the robotic fiber allows for high-precision surgical ablation. Additionally, we conducted experiments using a cervical phantom that demonstrated the robotic fiber's ability to access and perform high-precision scans, highlighting its potential for cervical disease treatments and improvement of oncological outcomes

Development of high throughput microscope mode secondary ion mass spectrometry imaging

This paper describes the development and initial results from a secondary ion mass spectrometer coupled with microscope mode detection. Stigmatic ion microscope imaging enables us to decouple the primary ion (PI) beam focus from spatial resolution and is a promising route to attaining higher throughput for mass spectrometry imaging (MSI). Using a commercial C60+ PI beam source, we can defocus the PI beam to give uniform intensity across a 2.5 mm2 area. By coupling the beam with a position-sensitive spatial detector, we can achieve mass spectral imaging of positive and negative secondary ions (SIs), which we demonstrate using samples comprising metals and dyes. Our approach involves simultaneous desorption of ions across a large field of view, enabling mass spectral images to be recorded over an area of 2.5 mm2 in a matter of seconds. Our instrument can distinguish spatial features with a resolution of better than 20 μm, and has a mass resolution of >500 at 500 u. There is considerable scope to improve this, and through simulations we estimate the future performance of the instrument

Laser-assisted rapid evaporative ionisation mass spectrometry (LA-REIMS) as a metabolomics platform in cervical cancer screening

Background The introduction of high-risk human papillomavirus (hrHPV) testing as part of primary cervical screening is anticipated to improve sensitivity, but also the number of women who will screen positive. Reflex cytology is the preferred triage test in most settings but has limitations including moderate diagnostic accuracy, lack of automation, inter-observer variability and the need for clinician-collected sample. Novel, objective and cost-effective approaches are needed. Methods In this study, we assessed the potential use of an automated metabolomic robotic platform, employing the principle of laser-assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS) in cervical cancer screening. Findings In a population of 130 women, LA-REIMS achieved 94% sensitivity and 83% specificity (AUC: 91.6%) in distinguishing women testing positive (n = 65) or negative (n = 65) for hrHPV. We performed further analysis according to disease severity with LA-REIMS achieving sensitivity and specificity of 91% and 73% respectively (AUC: 86.7%) in discriminating normal from high-grade pre-invasive disease. Interpretation This automated high-throughput technology holds promise as a low-cost and rapid test for cervical cancer screening and triage. The use of platforms like LA-REIMS has the potential to further improve the accuracy and efficiency of the current national screening programme. Funding Work was funded by the MRC Imperial Confidence in Concept Scheme, Imperial College Healthcare Charity, British Society for Colposcopy and Cervical Pathology, National Research Development and Innovation Office of Hungary, Waters corporation and NIHR BRC

Shotgun Lipidomic Profiling of the NCI60 Cell Line Panel Using Rapid Evaporative Ionization Mass Spectrometry

Rapid evaporative ionization mass spectrometry (REIMS) was used for the rapid mass spectrometric profiling of cancer cell lines. Spectral reproducibility was assessed for three different cell lines, and the extent of interclass differences and intraclass variance was found to allow the identification of these cell lines based on the REIMS data. Subsequently, the NCI60 cell line panel was subjected to REIMS analysis, and the resulting data set was investigated for its distinction of individual cell lines and different tissue types of origin. Information content of REIMS spectral profiles of cell lines were found to be similar to those obtained from mammalian tissues although pronounced differences in relative lipid intensity were observed. Ultimately, REIMS was shown to detect changes in lipid content of cell lines due to mycoplasma infection. The data show that REIMS is an attractive means to study cell lines involving minimal sample preparation and analysis times in the range of seconds. © 2016 American Chemical Society

Evaluation of formalin-fixed and FFPE tissues for spatially resolved metabolomics and drug distribution studies

Fixation of samples is broadly used prior to the histological evaluation of tissue samples. Though recent reports demonstrated the ability to use fixed tissues for mass spectrometry imaging (MSI) based proteomics, glycomics and tumor classification studies, to date comprehensive evaluation of fixation-related effects for spatially resolved metabolomics and drug disposition studies is still missing. In this study we used matrix assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI) MSI to investigate the effect of formalin-fixation and formalin-fixation combined with paraffin embedding on the detectable metabolome including xenobiotics. Formalin fixation was found to cause significant washout of polar molecular species, including inorganic salts, amino acids, organic acids and carnitine species, oxidation of endogenous lipids and formation of reaction products between lipids and fixative ingredients. The slow fixation kinetics under ambient conditions resulted in increased lipid hydrolysis in the tissue core, correlating with the time-dependent progression of the fixation. Paraffin embedding resulted in subsequent partial removal of structural lipids resulting in the distortion of the elucidated biodistributions

Automated Cancer Diagnostics via Analysis of Optical and Chemical Images by Deep and Shallow Learning

Funding Information: The Icelandic Centre for Research, grant no. 174566051 & 207301. The Icelandic Breast Cancer Research Fund, Göngum Saman. CRUK GC, NIHR/Imperial BRC. Dr Jean Alero Thomas Scholarship. Funding Information: Funding: The Icelandic Centre for Research, grant no. 174566051 & 207301. The Icelandic Breast Cancer Research Fund, Göngum Saman. CRUK GC, NIHR/Imperial BRC. Dr Jean Alero Thomas Scholarship. Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Optical microscopy has long been the gold standard to analyse tissue samples for the diagnostics of various diseases, such as cancer. The current diagnostic workflow is time-consuming and labour-intensive, and manual annotation by a qualified pathologist is needed. With the ever-increasing number of tissue blocks and the complexity of molecular diagnostics, new approaches have been developed as complimentary or alternative solutions for the current workflow, such as digital pathology and mass spectrometry imaging (MSI). This study compares the performance of a digital pathology workflow using deep learning for tissue recognition and an MSI approach utilising shallow learning to annotate formalin-fixed and paraffin-embedded (FFPE) breast cancer tissue microarrays (TMAs). Results show that both deep learning algorithms based on conventional optical images and MSI-based shallow learning can provide automated diagnostics with F1-scores higher than 90%, with the latter intrinsically built on biochemical information that can be used for further analysis.Peer reviewe

The surgical intelligent knife distinguishes normal, borderline and malignant gynaecological tissues using rapid evaporative ionisation mass spectrometry (REIMS)

Background Survival from ovarian cancer (OC) is improved with surgery, but surgery can be complex and tumour identification, especially for borderline ovarian tumours (BOT), is challenging. The Rapid Evaporative Ionisation Mass Spectrometric (REIMS) technique reports tissue histology in real-time by analysing aerosolised tissue during electrosurgical dissection. Methods Aerosol produced during diathermy of tissues was sampled with the REIMS interface. Histological diagnosis and mass spectra featuring complex lipid species populated a reference database on which principal component, linear discriminant and leave-one-patient-out cross-validation analyses were performed. Results A total of 198 patients provided 335 tissue samples, yielding 3384 spectra. Cross-validated OC classification vs separate normal tissues was high (97·4% sensitivity, 100% specificity). BOT were readily distinguishable from OC (sensitivity 90.5%, specificity 89.7%). Validation with fresh tissue lead to excellent OC detection (100% accuracy). Histological agreement between iKnife and histopathologist was very good (kappa 0.84, P < 0.001, z = 3.3). Five predominantly phosphatidic acid (PA(36:2)) and phosphatidyl-ethanolamine (PE(34:2)) lipid species were identified as being significantly more abundant in OC compared to normal tissue or BOT (P < 0.001, q < 0.001). Conclusions The REIMS iKnife distinguishes gynaecological tissues by analysing mass-spectrometry-derived lipidomes from tissue diathermy aerosols. Rapid intra-operative gynaecological tissue diagnosis may improve surgical care when histology is unknown, leading to personalised operations tailored to the individual