Computational methods for metastasis detection in lymph nodes and characterization of the metastasis-free lymph node microarchitecture: A systematic-narrative hybrid review.

Background: Histological examination of tumor draining lymph nodes (LNs) plays a vital role in cancer staging and prognostication. However, as soon as a LN is classed as metastasis-free, no further investigation will be performed and thus, potentially clinically relevant information detectable in tumor-free LNs is currently not captured. Objective: To systematically study and critically assess methods for the analysis of digitized histological LN images described in published research. Methods: A systematic search was conducted in several public databases up to December 2023 using relevant search terms. Studies using brightfield light microscopy images of hematoxylin and eosin or immunohistochemically stained LN tissue sections aiming to detect and/or segment LNs, their compartments or metastatic tumor using artificial intelligence (AI) were included. Dataset, AI methodology, cancer type, and study objective were compared between articles. Results: A total of 7201 articles were collected and 73 articles remained for detailed analyses after article screening. Of the remaining articles, 86% aimed at LN metastasis identification, 8% aimed at LN compartment segmentation, and remaining focused on LN contouring. Furthermore, 78% of articles used patch classification and 22% used pixel segmentation models for analyses. Five out of six studies (83%) of metastasis-free LNs were performed on publicly unavailable datasets, making quantitative article comparison impossible. Conclusions: Multi-scale models mimicking multiple microscopy zooms show promise for computational LN analysis. Large-scale datasets are needed to establish the clinical relevance of analyzing metastasis-free LN in detail. Further research is needed to identify clinically interpretable metrics for LN compartment characterization.

The clinical importance of the host anti-tumour reaction patterns in regional tumour draining lymph nodes in patients with locally advanced resectable gastric cancer: a systematic review and meta-analysis.

BACKGROUND: The status of regional tumour draining lymph nodes (LN) is crucial for prognostic evaluation in gastric cancer (GaC) patients. Changes in lymph node microarchitecture, such as follicular hyperplasia (FH), sinus histiocytosis (SH), or paracortical hyperplasia (PH), may be triggered by the anti-tumour immune response. However, the prognostic value of these changes in GaC patients is unclear. METHODS: A systematic search in multiple databases was conducted to identify studies on the prognostic value of microarchitecture changes in regional tumour-negative and tumour-positive LNs measured on histopathological slides. Since the number of GaC publications was very limited, the search was subsequently expanded to include junctional and oesophageal cancer (OeC). RESULTS: A total of 28 articles (17 gastric cancer, 11 oesophageal cancer) met the inclusion criteria, analyzing 26,503 lymph nodes from 3711 GaC and 1912 OeC patients. The studies described eight different types of lymph node microarchitecture changes, categorized into three patterns: hyperplasia (SH, FH, PH), cell-specific infiltration (dendritic cells, T cells, neutrophils, macrophages), and differential gene expression. Meta-analysis of five GaC studies showed a positive association between SH in tumour-negative lymph nodes and better 5-year overall survival. Pooled risk ratios for all LNs showed increased 5-year overall survival for the presence of SH and PH. CONCLUSIONS: This systematic review suggests that sinus histiocytosis and paracortical hyperplasia in regional tumour-negative lymph nodes may provide additional prognostic information for gastric and oesophageal cancer patients. Further studies are needed to better understand the lymph node reaction patterns and explore their impact of chemotherapy treatment and immunotherapy efficacy.

Tumour infiltrating lymphocytes and survival after adjuvant chemotherapy in patients with gastric cancer: post-hoc analysis of the CLASSIC trial.

BACKGROUND: Only a subset of gastric cancer (GC) patients with stage II-III benefits from chemotherapy after surgery. Tumour infiltrating lymphocytes per area (TIL density) has been suggested as a potential predictive biomarker of chemotherapy benefit. METHODS: We quantified TIL density in digital images of haematoxylin-eosin (HE) stained tissue using deep learning in 307 GC patients of the Yonsei Cancer Center (YCC) (193 surgery+adjuvant chemotherapy [S + C], 114 surgery alone [S]) and 629 CLASSIC trial GC patients (325 S + C and 304 S). The relationship between TIL density, disease-free survival (DFS) and clinicopathological variables was analysed. RESULTS: YCC S patients and CLASSIC S patients with high TIL density had longer DFS than S patients with low TIL density (P = 0.007 and P = 0.013, respectively). Furthermore, CLASSIC patients with low TIL density had longer DFS if treated with S + C compared to S (P = 0.003). No significant relationship of TIL density with other clinicopathological variables was found. CONCLUSION: This is the first study to suggest TIL density automatically quantified in routine HE stained tissue sections as a novel, clinically useful biomarker to identify stage II-III GC patients deriving benefit from adjuvant chemotherapy. Validation of our results in a prospective study is warranted.

Automated detection and delineation of lymph nodes in haematoxylin & eosin stained digitised slides.

Treatment of patients with oesophageal and gastric cancer (OeGC) is guided by disease stage, patient performance status and preferences. Lymph node (LN) status is one of the strongest prognostic factors for OeGC patients. However, survival varies between patients with the same disease stage and LN status. We recently showed that LN size from patients with OeGC might also have prognostic value, thus making delineations of LNs essential for size estimation and the extraction of other imaging biomarkers. We hypothesized that a machine learning workflow is able to: (1) find digital H&E stained slides containing LNs, (2) create a scoring system providing degrees of certainty for the results, and (3) delineate LNs in those images. To train and validate the pipeline, we used 1695 H&E slides from the OE02 trial. The dataset was divided into training (80%) and validation (20%). The model was tested on an external dataset of 826 H&E slides from the OE05 trial. U-Net architecture was used to generate prediction maps from which predefined features were extracted. These features were subsequently used to train an XGBoost model to determine if a region truly contained a LN. With our innovative method, the balanced accuracies of the LN detection were 0.93 on the validation dataset (0.83 on the test dataset) compared to 0.81 (0.81) on the validation (test) datasets when using the standard method of thresholding U-Net predictions to arrive at a binary mask. Our method allowed for the creation of an "uncertain" category, and partly limited false-positive predictions on the external dataset. The mean Dice score was 0.73 (0.60) per-image and 0.66 (0.48) per-LN for the validation (test) datasets. Our pipeline detects images with LNs more accurately than conventional methods, and high-throughput delineation of LNs can facilitate future LN content analyses of large datasets.

The role of the longitudinal muscle in the anal sphincter complex: Implications for the Intersphincteric Plane in Low Rectal Cancer Surgery?

Intersphincteric resection (ISR) enables radical sphincter-preserving surgery in a subset of low rectal tumors impinging on the anal sphincter complex (ASC). Excellent anatomical knowledge is essential for optimal ISR. This study describes the role of the longitudinal muscle (LM) in the ASC and implications for ISR and other low rectal and anal pathologies. Six human adult en bloc cadaveric specimens (three males, three females) were obtained from the University of Leeds GIFT Research Tissue Programme. Paraffin-embedded mega blocks containing the ASC were produced and serially sectioned at 250 µm intervals. Whole mount microscopic sections were histologically stained and digitally scanned. The intersphincteric plane was shown to be potentially very variable. In some places adipose tissue is located between the external anal sphincter (EAS) and internal anal sphincter (IAS), whereas in others the LM interdigitates to obliterate the plane. Elsewhere the LM is (partly) absent with the intersphincteric plane lying on the IAS. The LM gave rise to the formation of the submucosae and corrugator ani muscles by penetrating the IAS and EAS. In four of six specimens, striated muscle fibers from the EAS curled around the distal IAS reaching the anal submucosa. The ASC formed a complex structure, varying between individuals with an inconstant LM affecting the potential location of the intersphincteric plane as well as a high degree of intermingling striated and smooth muscle fibers potentially further disrupting the plane. The complexity of identifying the correct pathological staging of low rectal cancer is also demonstrated. Clin. Anat. 33:567-577, 2020. © 2019 Wiley Periodicals, Inc.

Quantitative Myocardial Perfusion Imaging Versus Visual Analysis in Diagnosing Myocardial Ischemia: A CE-MARC Substudy.

OBJECTIVES: This study sought to compare the diagnostic accuracy of visual and quantitative analyses of myocardial perfusion cardiovascular magnetic resonance against a reference standard of quantitative coronary angiography. BACKGROUND: Visual analysis of perfusion cardiovascular magnetic resonance studies for assessing myocardial perfusion has been shown to have high diagnostic accuracy for coronary artery disease. However, only a few small studies have assessed the diagnostic accuracy of quantitative myocardial perfusion. METHODS: This retrospective study included 128 patients randomly selected from the CE-MARC (Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease) study population such that the distribution of risk factors and disease status was proportionate to the full population. Visual analysis results of cardiovascular magnetic resonance perfusion images, by consensus of 2 expert readers, were taken from the original study reports. Quantitative myocardial blood flow estimates were obtained using Fermi-constrained deconvolution. The reference standard for myocardial ischemia was a quantitative coronary x-ray angiogram stenosis severity of ≥70% diameter in any coronary artery of >2 mm diameter, or ≥50% in the left main stem. Diagnostic performance was calculated using receiver-operating characteristic curve analysis. RESULTS: The area under the curve for visual analysis was 0.88 (95% confidence interval: 0.81 to 0.95) with a sensitivity of 81.0% (95% confidence interval: 69.1% to 92.8%) and specificity of 86.0% (95% confidence interval: 78.7% to 93.4%). For quantitative stress myocardial blood flow the area under the curve was 0.89 (95% confidence interval: 0.83 to 0.96) with a sensitivity of 87.5% (95% confidence interval: 77.3% to 97.7%) and specificity of 84.5% (95% confidence interval: 76.8% to 92.3%). There was no statistically significant difference between the diagnostic performance of quantitative and visual analyses (p = 0.72). Incorporating rest myocardial blood flow values to generate a myocardial perfusion reserve did not significantly increase the quantitative analysis area under the curve (p = 0.79). CONCLUSIONS: Quantitative perfusion has a high diagnostic accuracy for detecting coronary artery disease but is not superior to visual analysis. The incorporation of rest perfusion imaging does not improve diagnostic accuracy in quantitative perfusion analysis.

Patient-specific coronary blood supply territories for quantitative perfusion analysis.

Myocardial perfusion imaging, coupled with quantitative perfusion analysis, provides an important diagnostic tool for the identification of ischaemic heart disease caused by coronary stenoses. The accurate mapping between coronary anatomy and under-perfused areas of the myocardium is important for diagnosis and treatment. However, in the absence of the actual coronary anatomy during the reporting of perfusion images, areas of ischaemia are allocated to a coronary territory based on a population-derived 17-segment (American Heart Association) AHA model of coronary blood supply. This work presents a solution for the fusion of 2D Magnetic Resonance (MR) myocardial perfusion images and 3D MR angiography data with the aim to improve the detection of ischaemic heart disease. The key contribution of this work is a novel method for the mediated spatiotemporal registration of perfusion and angiography data and a novel method for the calculation of patient-specific coronary supply territories. The registration method uses 4D cardiac MR cine series spanning the complete cardiac cycle in order to overcome the under-constrained nature of non-rigid slice-to-volume perfusion-to-angiography registration. This is achieved by separating out the deformable registration problem and solving it through phase-to-phase registration of the cine series. The use of patient-specific blood supply territories in quantitative perfusion analysis (instead of the population-based model of coronary blood supply) has the potential of increasing the accuracy of perfusion analysis. Quantitative perfusion analysis diagnostic accuracy evaluation with patient-specific territories against the AHA model demonstrates the value of the mediated spatiotemporal registration in the context of ischaemic heart disease diagnosis.

3D Buried Utility Location Using A Marching-Cross-Section Algorithm for Multi-Sensor Data Fusion.

We address the problem of accurately locating buried utility segments by fusing data from multiple sensors using a novel Marching-Cross-Section (MCS) algorithm. Five types of sensors are used in this work: Ground Penetrating Radar (GPR), Passive Magnetic Fields (PMF), Magnetic Gradiometer (MG), Low Frequency Electromagnetic Fields (LFEM) and Vibro-Acoustics (VA). As part of the MCS algorithm, a novel formulation of the extended Kalman Filter (EKF) is proposed for marching existing utility tracks from a scan cross-section (scs) to the next one; novel rules for initializing utilities based on hypothesized detections on the first scs and for associating predicted utility tracks with hypothesized detections in the following scss are introduced. Algorithms are proposed for generating virtual scan lines based on given hypothesized detections when different sensors do not share common scan lines, or when only the coordinates of the hypothesized detections are provided without any information of the actual survey scan lines. The performance of the proposed system is evaluated with both synthetic data and real data. The experimental results in this work demonstrate that the proposed MCS algorithm can locate multiple buried utility segments simultaneously, including both straight and curved utilities, and can separate intersecting segments. By using the probabilities of a hypothesized detection being a pipe or a cable together with its 3D coordinates, the MCS algorithm is able to discriminate a pipe and a cable close to each other. The MCS algorithm can be used for both post- and on-site processing. When it is used on site, the detected tracks on the current scs can help to determine the location and direction of the next scan line. The proposed "multi-utility multi-sensor" system has no limit to the number of buried utilities or the number of sensors, and the more sensor data used, the more buried utility segments can be detected with more accurate location and orientation.

Investigation into diagnostic accuracy of common strategies for automated perfusion motion correction.

Respiratory motion is a significant obstacle to the use of quantitative perfusion in clinical practice. Increasingly complex motion correction algorithms are being developed to correct for respiratory motion. However, the impact of these improvements on the final diagnosis of ischemic heart disease has not been evaluated. The aim of this study was to compare the performance of four automated correction methods in terms of their impact on diagnostic accuracy. Three strategies for motion correction were used: (1) independent translation correction for all slices, (2) translation correction for the basal slice with transform propagation to the remaining two slices assuming identical motion in the remaining slices, and (3) rigid correction (translation and rotation) for the basal slice. There were no significant differences in diagnostic accuracy between the manual and automatic motion-corrected datasets ([Formula: see text]). The area under the curve values for manual motion correction and automatic motion correction were 0.93 and 0.92, respectively. All of the automated motion correction methods achieved a comparable diagnostic accuracy to manual correction. This suggests that the simplest automated motion correction method (method 2 with translation transform for basal location and transform propagation to the remaining slices) is a sufficiently complex motion correction method for use in quantitative myocardial perfusion.

Prospector: A web-based tool for rapid acquisition of gold standard data for pathology research and image analysis.

BACKGROUND: Obtaining ground truth for pathological images is essential for various experiments, especially for training and testing image analysis algorithms. However, obtaining pathologist input is often difficult, time consuming and expensive. This leads to algorithms being over-fitted to small datasets, and inappropriate validation, which causes poor performance on real world data. There is a great need to gather data from pathologists in a simple and efficient manner, in order to maximise the amount of data obtained. METHODS: We present a lightweight, web-based HTML5 system for administering and participating in data collection experiments. The system is designed for rapid input with minimal effort, and can be accessed from anywhere in the world with a reliable internet connection. RESULTS: We present two case studies that use the system to assess how limitations on fields of view affect pathologist agreement, and to what extent poorly stained slides affect judgement. In both cases, the system collects pathologist scores at a rate of less than two seconds per image. CONCLUSIONS: The system has multiple potential applications in pathology and other domains.

Comparison of diffusion tensor imaging by cardiovascular magnetic resonance and gadolinium enhanced 3D image intensity approaches to investigation of structural anisotropy in explanted rat hearts.

BACKGROUND: Cardiovascular magnetic resonance (CMR) can through the two methods 3D FLASH and diffusion tensor imaging (DTI) give complementary information on the local orientations of cardiomyocytes and their laminar arrays. METHODS: Eight explanted rat hearts were perfused with Gd-DTPA contrast agent and fixative and imaged in a 9.4T magnet by two types of acquisition: 3D fast low angle shot (FLASH) imaging, voxels 50 × 50 × 50 µm, and 3D spin echo DTI with monopolar diffusion gradients of 3.6 ms duration at 11.5 ms separation, voxels 200 × 200 × 200 µm. The sensitivity of each approach to imaging parameters was explored. RESULTS: The FLASH data showed laminar alignments of voxels with high signal, in keeping with the presumed predominance of contrast in the interstices between sheetlets. It was analysed, using structure-tensor (ST) analysis, to determine the most (v1(ST)), intermediate (v2(ST)) and least (v3(ST)) extended orthogonal directions of signal continuity. The DTI data was analysed to determine the most (e1(DTI)), intermediate (e2(DTI)) and least (e3(DTI)) orthogonal eigenvectors of extent of diffusion. The correspondence between the FLASH and DTI methods was measured and appraised. The most extended direction of FLASH signal (v1(ST)) agreed well with that of diffusion (e1(DTI)) throughout the left ventricle (representative discrepancy in the septum of 13.3 ± 6.7°: median ± absolute deviation) and both were in keeping with the expected local orientations of the long-axis of cardiomyocytes. However, the orientation of the least directions of FLASH signal continuity (v3(ST)) and diffusion (e3(ST)) showed greater discrepancies of up to 27.9 ± 17.4°. Both FLASH (v3(ST)) and DTI (e3(DTI)) where compared to directly measured laminar arrays in the FLASH images. For FLASH the discrepancy between the structure-tensor calculated v3(ST) and the directly measured FLASH laminar array normal was of 9 ± 7° for the lateral wall and 7 ± 9° for the septum (median ± inter quartile range), and for DTI the discrepancy between the calculated v3(DTI) and the directly measured FLASH laminar array normal was 22 ± 14° and 61 ± 53.4°. DTI was relatively insensitive to the number of diffusion directions and to time up to 72 hours post fixation, but was moderately affected by b-value (which was scaled by modifying diffusion gradient pulse strength with fixed gradient pulse separation). Optimal DTI parameters were b = 1000 mm/s(2) and 12 diffusion directions. FLASH acquisitions were relatively insensitive to the image processing parameters explored. CONCLUSIONS: We show that ST analysis of FLASH is a useful and accurate tool in the measurement of cardiac microstructure. While both FLASH and the DTI approaches appear promising for mapping of the alignments of myocytes throughout myocardium, marked discrepancies between the cross myocyte anisotropies deduced from each method call for consideration of their respective limitations.

Three-dimensional reconstruction of ductal carcinoma in situ with virtual slides.

AIMS: This study aimed to assess the feasibility of using virtual slides to create 3D histopathological reconstructions to aid in the study of the biology of DCIS. METHODS: Four µm thick serial sections of formalin fixed paraffin embedded tissue from three cases were cut and mounted onto glass slides, stained with haematoxylin and eosin, then scanned. The three image stacks comprised 30, 115 and 100 scanned sections creating a similar number of virtual slides. The virtual slides were registered using custom 3D software to create 3D tissue volumes. The volumes were annotated to highlight distinct features and 3D visualisations (segmentations) were created to study these features in 3D. RESULTS: The most time-intensive step was the manual annotation of virtual slides 3D histopathological reconstructions were created of (i) DCIS surrounded by adjacent invasion; (ii) pure DCIS and (iii) a 'normal' lobule. CONCLUSION: 3D in silico reconstructions of DCIS were created and more extensive studies can now be done within a realistic timescale. We have identified structural similarities between a benign lobule and DCIS which support the view that much DCIS, apparently in a 'duct' is contained within and expanded lobule. This method has the potential to provide insights into the biology of DCIS.

3-D tissue modelling and virtual pathology as new approaches to study ductal carcinoma in situ.

Widespread screening mammography programmes mean that ductal carcinoma in situ (DCIS), a pre-invasive breast lesion, is now more frequently diagnosed. However, not all diagnosed DCIS lesions progress to invasive breast cancer, which presents a dilemma for clinicians. As such, there is much interest in studying DCIS in the laboratory, in order to help understand more about its biology and determine the characteristics of those that progress to invasion. Greater knowledge would lead to targeted and better DCIS treatment. Here, we outline some of the models available to study DCIS, with a particular focus on animal-free systems.

Comparison of the Diagnostic Performance of Four Quantitative Myocardial Perfusion Estimation Methods Used in Cardiac MR Imaging: CE-MARC Substudy.

PURPOSE: To compare the diagnostic performance of four tracer kinetic analysis methods to quantify myocardial perfusion from magnetic resonance (MR) imaging cardiac perfusion data sets in terms of their ability to lead to the diagnosis of myocardial ischemia. MATERIALS AND METHODS: The study was approved by the regional ethics committee, and all patients gave written consent. A representative sample of 50 patients with suspected ischemic heart disease was retrospectively selected from the Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease trial data set. Quantitative myocardial blood flow (MBF) was estimated from rest and adenosine stress MR imaging perfusion data sets by using four established methods. A matching diagnosis of both an inducible defect as assessed with single photon emission computed tomography and a luminal stenosis of 70% or more as assessed with quantitative x-ray angiography was used as the reference standard for the presence of myocardial ischemia. Diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis for each method, with stress MBF and myocardial perfusion reserve (MPR) serving as continuous measures. RESULTS: Area under the ROC curve with stress MBF and MPR as the outcome measures, respectively, was 0.86 and 0.92 for the Fermi model, 0.85 and 0.87 for the uptake model, 0.85 and 0.80 for the one-compartment model, and 0.87 and 0.87 for model-independent deconvolution. There was no significant difference between any of the models or between MBF and MPR, except that the Fermi model outperformed the one-compartment model if MPR was used as the outcome measure (P = .02). CONCLUSION: Diagnostic performance of quantitative myocardial perfusion estimates is not affected by the tracer kinetic analysis method used.

3D reconstruction of multiple stained histology images.

CONTEXT: Three dimensional (3D) tissue reconstructions from the histology images with different stains allows the spatial alignment of structural and functional elements highlighted by different stains for quantitative study of many physiological and pathological phenomena. This has significant potential to improve the understanding of the growth patterns and the spatial arrangement of diseased cells, and enhance the study of biomechanical behavior of the tissue structures towards better treatments (e.g. tissue-engineering applications). METHODS: This paper evaluates three strategies for 3D reconstruction from sets of two dimensional (2D) histological sections with different stains, by combining methods of 2D multi-stain registration and 3D volumetric reconstruction from same stain sections. SETTING AND DESIGN: The different strategies have been evaluated on two liver specimens (80 sections in total) stained with Hematoxylin and Eosin (H and E), Sirius Red, and Cytokeratin (CK) 7. RESULTS AND CONCLUSION: A strategy of using multi-stain registration to align images of a second stain to a volume reconstructed by same-stain registration results in the lowest overall error, although an interlaced image registration approach may be more robust to poor section quality.