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Background: Bacille Calmette–Guerin (BCG) immunotherapy is the first-line treatment in patients with high-risk non-muscle invasive papillary urothelial carcinoma (NMIPUC), the most common type of bladder cancer. The therapy outcomes are variable and may depend on the immune response within the tumor microenvironment. In our study, we explored the prognostic value of CD8+ cell density gradient indicators across the tumor epithelium–stroma interface of NMIPUC. Methods: Clinical and pathologic data were retrospectively collected from 157 NMIPUC patients treated with BCG immunotherapy after transurethral resection. Whole-slide digital image analysis of CD8 immunohistochemistry slides was used for tissue segmentation, CD8+ cell quantification, and the assessment of CD8+ cell densities within the epithelium–stroma interface. Subsequently, the gradient indicators (center of mass and immunodrop) were computed to represent the density gradient across the interface. Results: By univariable analysis of the clinicopathologic factors, including the history of previous NMIPUC, poor tumor differentiation, and pT1 stage, were associated with shorter RFS (p < 0.05). In CD8+ analyses, only the gradient indicators but not the absolute CD8+ densities were predictive for RFS (p < 0.05). The best-performing cross-validated model included previous episodes of NMIPUC (HR = 4.4492, p = 0.0063), poor differentiation (HR = 2.3672, p = 0.0457), and immunodrop (HR = 5.5072, p = 0.0455). Conclusions: We found that gradient indicators of CD8+ cell densities across the tumor epithelium–stroma interface, along with routine clinical and pathology data, improve the prediction of RFS in NMIPUC.

Hepatocellular carcinoma (HCC) often emerges in the setting of long-standing inflammatory liver disease. CD8 lymphocytes are involved in both the antitumoral response and hepatocyte damage in the remaining parenchyma. We investigated the dual role of CD8 lymphocytes by assessing density profiles at the interfaces of both HCC and perineoplastic liver parenchyma with surrounding stroma in whole-slide immunohistochemistry images of surgical resection samples. We applied a hexagonal grid-based digital image analysis method to sample the interface zones and compute the CD8 density profiles within them. The prognostic value of the indicators was explored in the context of clinicopathological, peripheral blood testing, and surgery data. Independent predictors of worse OS were a low standard deviation of CD8+ density along the tumor edge, high mean CD8+ density within the epithelial aspect of the perineoplastic liver-stroma interface, longer duration of surgery, a higher level of aspartate transaminase (AST), and a higher basophil count in the peripheral blood. A combined score, derived from these five independent predictors, enabled risk stratification of the patients into three prognostic categories with a 5-year OS probability of 76%, 40%, and 8%. Independent predictors of longer RFS were stage pT1, shorter duration of surgery, larger tumor size, wider tumor-free margin, and higher mean CD8+ density in the epithelial aspect of the tumor-stroma interface. We conclude that (1) our computational models reveal independent and opposite prognostic impacts of CD8+ cell densities at the interfaces of the malignant and non-malignant epithelium interfaces with the surrounding stroma; and (2) together with pathology, surgery, and laboratory data, comprehensive prognostic models can be constructed to predict patient outcomes after liver resection due to HCC.

Pretreatment by reversible electroporation followed by resting (storage under saturated moisture at 21 ± 2 °C) was evaluated for modification of the properties of dried and rehydrated Thai basil leaves. The treated leaves were dried by convection at 40 °C or in a vacuum at room temperature. The results showed that vacuum drying provoked more cell damage and tissue collapse than convective air drying at a moisture ratio (MR) of 0.2 and 0.1. Under this level of MR, the pulsed electric field (PEF) and resting pretreatment exerts a protective effect of the tissue for both drying methods. However, under complete dehydration (water activity, aw = 0.05) damage seems to be similar for both drying methods despite the PEF pretreatment. Remarkably, reversible electroporation followed by resting resulted in higher trichome preservation. At MR of 0.05, the area of trichomes on the surface of convective-dried, PEF-rested and fresh samples were not statistically different at 2267 ± 89 µm2 and 2218 ± 65 µm2, respectively, showing that this pretreatment still exerts a protective effect on trichomes when complete dehydration is achieved.

Intranuclear birefringent inclusions (IBI) found in various cell types in paraffin-embedded tissue sections have long been considered to be a tissue processing artifact, although an association with biological processes has been suggested. We applied polychromatic polarization microscopy to image their spatial organization. Our study provides evidence that IBI are caused by liquid paraffin-macromolecular crystals formed during paraffin-embedding procedures within cells and potentially reflect an active transcriptional status.

Assessment of intratumoral heterogeneity and tumor-host interaction within the tumor microenvironment is becoming increasingly important for innovative cancer therapy decisions because of the unique information it can generate about the state of the disease. However, its assessment and quantification are limited by ambiguous definitions of the tumor-host interface and by human cognitive capacity in current pathology practice. Advances in machine learning and artificial intelligence have opened the field of digital pathology to novel tissue image analytics and feature extraction for generation of high-capacity computational disease management models. A particular benefit is expected from machine-learning applications that can perform extraction and quantification of subvisual features of both intratumoral heterogeneity and tumor microenvironment aspects. These methods generate information about cancer cell subpopulation heterogeneity, potential tumor-host interactions, and tissue microarchitecture, derived from morphologically resolved content using both explicit and implicit features. Several studies have achieved promising diagnostic, prognostic, and predictive artificial intelligence models that often outperform current clinical and pathology criteria. However, further effort is needed for clinical adoption of such methods through development of standardizable high-capacity workflows and proper validation studies.

Tumor-associated immune cells have been shown to predict patient outcome in colorectal (CRC) and other cancers. Spatial digital image analysis-based cell quantification increases the informative power delivered by tumor microenvironment features and leads to new prognostic scoring systems. In this study we evaluated the intratumoral density of immunohistochemically stained CD8, CD20 and CD68 cells in 87 cases of CRC (48 were microsatellite stable, MSS, and 39 had microsatellite instability, MSI) in both the intratumoral tumor tissue and within the tumor-stroma interface zone (IZ) which was extracted by a previously developed unbiased hexagonal grid analytics method. Indicators of immune-cell gradients across the extracted IZ were computed and explored along with absolute cell densities, clinicopathological and molecular data, including gene mutation (BRAF, KRAS, PIK3CA) and MSI status. Multiple regression modeling identified (p &lt, 0.0001) three independent prognostic factors: CD8+ and CD20+ Immunogradient indicators, that reflect cell migration towards the tumor, were associated with improved patient survival, while the infiltrative tumor growth pattern was linked to worse patient outcome. These features were combined into CD8-CD20 Immunogradient and immuno-interface scores which outperformed both tumor-node-metastasis (TNM) staging and molecular characteristics, and importantly, revealed high prognostic value both in MSS and MSI CRCs.

The distribution of tumor-infiltrating lymphocytes (TILs) within the tumor microenvironment provides strong prognostic value, which is increasingly important with the arrival of new immunotherapy modalities. Both visual and image analysis-based assays are developed to assess the immune contexture of the tumors. We propose an automated method based on grid subsampling of microscopy image analysis data to extract the tumor-stroma interface zone (IZ) of controlled width. The IZ is a ranking of tissue areas by their distance to the tumor edge, which is determined by a set of explicit rules. TIL density profiles across the IZ are used to compute a set of novel immunogradient indicators that reflect TIL gradient towards the tumor. We applied this method on CD8 immunohistochemistry images of surgically excised hormone receptor-positive breast and colorectal cancers to predict overall patient survival. In both cohorts, the immunogradient indicators enabled strong and independent prognostic stratification, outperforming clinical and pathologic variables. Patients with breast cancer with low immunogradient levels had a prominent decrease in survival probability 5 years after surgery. Our study provides proof of concept that data-driven, automated, operator-independent IZ sampling enables spatial immune response measurement in the tumor-host interaction frontline for prediction of disease outcomes.

Proliferative activity, assessed by Ki67 immunohistochemistry (IHC), is an established prognostic and predictive biomarker of breast cancer (BC). However, it remains under-utilized due to lack of standardized robust measurement methodologies and significant intratumor heterogeneity of expression. A recently proposed methodology for IHC biomarker assessment in whole slide images (WSI), based on systematic subsampling of tissue information extracted by digital image analysis (DIA) into hexagonal tiling arrays, enables computation of a comprehensive set of Ki67 indicators, including intratumor variability. In this study, the tiling methodology was applied to assess Ki67 expression in WSI of 152 surgically removed Ki67-stained (on full-face sections) BC specimens and to test which, if any, Ki67 indicators can predict overall survival (OS). Visual Ki67 IHC estimates and conventional clinico-pathologic parameters were also included in the study. Analysis revealed linearly independent intrinsic factors of the Ki67 IHC variance: proliferation (level of expression), disordered texture (entropy), tumor size and Nottingham Prognostic Index, bimodality, and correlation. All visual and DIA-generated indicators of the level of Ki67 expression provided significant cutoff values as single predictors of OS. However, only bimodality indicators (Ashman's D, in particular) were independent predictors of OS in the context of hormone receptor and HER2 status. From this, we conclude that spatial heterogeneity of proliferative tumor activity, measured by DIA of Ki67 IHC expression and analyzed by the hexagonal tiling approach, can serve as an independent prognostic indicator of OS in BC patients that outperforms the prognostic power of the level of proliferative activity.

Summary This paper presents a new local volume estimator, the spatial rotator, which is based on measurements on a virtual 3D probe, using computer assisted microscopy. The basic design of the probe builds upon the rotator principle which requires only a few manual intersection markings, thus making the spatial rotator fast to use. Since a 3D probe is involved, it is expected that the spatial rotator will be more efficient than the the nucleator and the planar rotator, which are based on measurements in a single plane. An extensive simulation study shows that the spatial rotator may be more efficient than the traditional local volume estimators. Furthermore, the spatial rotator can be seen as a further development of the Cavalieri estimator, which does not require randomization of sectioning or viewing direction. The tissue may thus be sectioned in any arbitrary direction, making it easy to identify the specific tissue region under study. In order to use the spatial rotator in practice, however, it is necessary to be able to identify intersection points between cell boundaries and test rays in a series of parallel focal planes, also at the peripheral parts of the cell boundaries. In cases where over- and underprojection phenomena are not negligible, they should therefore be corrected for if the spatial rotator is to be applied. If such a correction is not possible, it is needed to avoid these phenomena by using microscopy with increased resolution in the focal plane.

Human epidermal growth factor receptor 2 gene- (HER2-) targeted therapy for breast cancer relies primarily on HER2 overexpression established by immunohistochemistry (IHC) with borderline cases being further tested for amplification by fluorescence in situ hybridization (FISH). Manual interpretation of HER2 FISH is based on a limited number of cells and rather complex definitions of equivocal, polysomic, and genetically heterogeneous (GH) cases. Image analysis (IA) can extract high-capacity data and potentially improve HER2 testing in borderline cases. We investigated statistically derived indicators of HER2 heterogeneity in HER2 FISH data obtained by automated IA of 50 IHC borderline (2+) cases of invasive ductal breast carcinoma. Overall, IA significantly underestimated the conventional HER2, CEP17 counts, and HER2/CEP17 ratio; however, it collected more amplified cells in some cases below the lower limit of GH definition by manual procedure. Indicators for amplification, polysomy, and bimodality were extracted by factor analysis and allowed clustering of the tumors into amplified, nonamplified, and equivocal/polysomy categories. The bimodality indicator provided independent cell diversity characteristics for all clusters. Tumors classified as bimodal only partially coincided with the conventional GH heterogeneity category. We conclude that automated high-capacity nonselective tumor cell assay can generate evidence-based HER2 intratumor heterogeneity indicators to refine GH definitions.

Introduction/ Background Gene expression studies have identified molecular subtypes of breast cancer with implications to chemotherapy recommendations. For distinction of these types a combination of hormone receptors and proliferative activity of tumor cells, estimated by Ki67 labeling index from immunohistochemistry (IHC) is used. Clinical studies are frequently based on IHC performed on tissue microarrays (TMA) with variable tissue sampling. This raises the need for evidence-based sampling criteria for individual studies. We present a novel tissue sampling simulation model and demonstrate its application on Ki67 assessment in breast cancer tissue taking into account its intra-tumoral heterogeneity. Aims The aim is, using a novel method for easy virtual TMA simulation, to determine the optimal tissue sampling requirements in the context of variable intra-tissue heterogeneity level of Ki67 immunohistochemistry in breast cancer. Methods Whole slide images (WSI) of 297 primary breast tumors immunohistochemically stained for Ki67 were subjected to digital image analysis (DIA). Percentage of invasive tumor cells stained for Ki67 were computed for hexagonal tiles superimposed on the WSI. From this, intra-tumoral Ki67 heterogeneity indicators (Haralick’s entropy values) were extracted and used to dichotomize the tumors into homogeneous and heterogeneous populations. Simulations with random selection of hexagons, equivalent to 0.75 mm circular diameter, were performed. The tissue sampling requirements were investigated in relation to tumor heterogeneity using linear regression and extended error analysis. Results The sampling requirements were dependent on the heterogeneity of the biomarker expression. To achieve a coefficient error of 10%, 5-6 cores were needed for homogeneous cases, while 11-12 cores for heterogeneous cases. In mixed tumor population, 8 TMA cores were required. Similarly, to achieve the same accuracy, approximately 4,000 nuclei must be counted when the intra-tumor heterogeneity is mixed/unknown. Tumors at the lower scale of proliferative activity would require larger sampling (10-12 TMA cores, or 5,000 nuclei) to achieve the same error measurement results as for highly proliferative tumors. Our data show that optimal tissue sampling for IHC biomarker evaluation is dependent on the heterogeneity of the tissue under study and needs to be determined on a per-use basis. We propose a method that can be applied to determine the TMA sampling strategy for specific biomarkers, tissues and study targets. In addition, our findings highlight the importance of high-capacity computer-based IHC measurement techniques to improve accuracy of the testing., Diagnostic Pathology, Vol 1 No 8 (2016): 13. European Congress on Digital Pathology

Four-dimensional (4D) flow imaging has been used to study flow patterns and pathophysiology, usually focused on specific thoracic vessels and cardiac chambers. Whole-heart 4D flow at high measurement accuracy covering the entire thoracic cardiovascular system would be desirable to simplify and improve hemodynamic assessment. This has been a challenge because compensation of respiratory motion is difficult to achieve, but it is paramount to limit artifacts and improve accuracy. In this work we propose a self-gating technique for respiratory motion-compensation integrated into a whole-heart 4D flow acquisition that overcomes these challenges. Flow components are measured in all three directions for each pixel over the complete cardiac cycle, and 1D volume projections are obtained at certain time intervals for respiratory gating in real time during the acquisition. The technique was tested in 15 volunteers, in which stroke volumes (SVs) in the great arteries showed excellent agreement with standard 2D phase-contrast (PC) scans. In contrast, nongated 4D flow with two averages had substantial disagreement with 2D flow. Applied to patients with congenital cardiac left-to-right shunting, the precision of flux data was highly beneficial. The methodology presented here has the potential to allow a complete study of flow pathophysiology of the thoracic cardiovascular system from a single free-breathing scan.

Patient-specific preoperative planning in complex congenital heart disease may be greatly facilitated by virtual cardiotomy. Surgeons can perform an unlimited number of surgical incisions on a virtual 3-D reconstruction to evaluate the feasibility of different surgical strategies.To quantitatively evaluate the quality of the underlying imaging data and the accuracy of the corresponding segmentation, and to qualitatively evaluate the feasibility of virtual cardiotomy.A whole-heart MRI sequence was applied in 42 children with congenital heart disease (age 3 +/- 3 years, weight 13 +/- 9 kg, heart rate 96 +/- 21 bpm). Image quality was graded 1-4 (diagnostic image qualityor =2) by two independent blinded observers. In patients with diagnostic image quality the segmentation quality was also graded 1-4 (4 no discrepancies, 1 misleading error).The average image quality score was 2.7 - sufficient for virtual reconstruction in 35 of 38 patients (92%) older than 1 month. Segmentation time was 59 +/- 10 min (average quality score 3.5). Virtual cardiotomy was performed in 19 patients.Accurate virtual reconstructions of patient-specific cardiac anatomy can be produced in less than 1 h from 3-D MRI. The presented work thus introduces a new, clinically feasible noninvasive technique for improved preoperative planning in complex cases of congenital heart disease.

This chapter contains an introduction to rotational integral geometry that is the key tool in local stereological procedures for estimating quantitative properties of spatial structures. In rotational integral geometry, focus is on integrals of geometric functionals with respect to rotation invariant measures. Rotational integrals of intrinsic volumes are studied. The opposite problem of expressing intrinsic volumes as rotational integrals is also considered. It is shown how to express intrinsic volumes as integrals with respect to geometric functionals defined on lower dimensional linear subspaces. Rotational integral geometry of Minkowski tensors is shortly discussed as well as a principal rotational formula. These tools are then applied in local stereology leading to unbiased stereological estimators of mean intrinsic volumes for isotropic random sets. At the end of the chapter, emphasis is put on how these procedures can be implemented when automatic image analysis is available. Computational procedures play an increasingly important role in the stereological analysis of spatial structures and a new sub-discipline, computational stereology, is emerging.

Digital pathology is an interdisciplinary field where competency in pathology, laboratory techniques, informatics, computer science, information systems, engineering, and even biology converge. This implies that teaching students about digital pathology requires coverage, expertise, and hands-on experience in all these disciplines. With this in mind, a syllabus was developed for a digital pathology summer school aimed at professionals in the aforementioned fields, as well as trainees and doctoral students. The aim of this communication is to share the context, rationale, and syllabus for this school of digital pathology.

Many image processing problems benefit from a complete solution to connected components labeling. This paper introduces a new data parallel labeling method based on calculation of label propagation sizes from the connectivity between pixels extracted in a pre-processing step and re-usal of established label propagation routes. The method achieves real-time performance for 2D images and it also generalizes to Voronoi diagrams and signed distance fields.

Four-dimensional (4D) flow imaging has been used to study flow patterns and pathophysiology, usually focused on specific thoracic vessels and cardiac chambers. Whole-heart 4D flow at high measurement accuracy covering the entire thoracic cardiovascular system would be desirable to simplify and improve hemodynamic assessment. This has been a challenge because compensation of respiratory motion is difficult to achieve, but it is paramount to limit artifacts and improve accuracy. In this work we propose a self-gating technique for respiratory motion-compensation integrated into a whole-heart 4D flow acquisition that overcomes these challenges. Flow components are measured in all three directions for each pixel over the complete cardiac cycle, and 1D volume projections are obtained at certain time intervals for respiratory gating in real time during the acquisition. The technique was tested in 15 volunteers, in which stroke volumes (SVs) in the great arteries showed excellent agreement with standard 2D phase-contrast (PC) scans. In contrast, nongated 4D flow with two averages had substantial disagreement with 2D flow. Applied to patients with congenital cardiac left-to-right shunting, the precision of flux data was highly beneficial. The methodology presented here has the potential to allow a complete study of flow pathophysiology of the thoracic cardiovascular system from a single free-breathing scan.

Background Two-dimensional, unidirectionally encoded, cardiovascular magnetic resonance (CMR) velocity mapping is an established technique for the quantification of blood flow in large vessels. However, it requires an operator to correctly align the planes of acquisition. If all three directional components of velocity are measured for each voxel of a 3D volume through the phases of the cardiac cycle, blood flow through any chosen plane can potentially be calculated retrospectively. The initial acquisition is then more time consuming but relatively operator independent. Aims To compare the curves and volumes of flow derived from conventional 2D and comprehensive 3D flow acquisitions in a steady state flow model, and in vivo through planes transecting the ascending aorta and pulmonary trunk in 10 healthy volunteers. Methods Using a 1.5 T Phillips Intera CMR system, 3D acquisitions used an anisotropic 3D segmented k-space phase contrast gradient echo sequence with a short EPI readout, with prospective ECG and diaphragm navigator gating. The 2D acquisitions used segmented k-space phase contrast with prospective ECG and diaphragm navigator gating. Quantitative flow analyses were performed retrospectively with dedicated software for both the in vivo and in vitro acquisitions. Results Analysis of in vitro data found the 3D technique to have overestimated the continuous flow rate by approximately 5% across the entire applied flow range. In vivo, the 2D and the 3D techniques yielded similar volumetric flow curves and measurements. Aortic flow: (mean ± SD), 2D = 89.5 ± 13.5 ml & 3D = 92.7 ± 17.5 ml. Pulmonary flow: 2D = 98.8 ± 18.4 ml & 3D = 94.9 ± 19.0 ml). Each in vivo 3D acquisition took about 8 minutes or more. Conclusion Flow measurements derived from the 3D and 2D acquisitions were comparable. Although time consuming, comprehensive 3D velocity acquisition could be relatively operator independent, and could potentially yield information on flow through several retrospectively chosen planes, for example in patients with congenital or valvular heart disease.

Since the advent of programmable graphics processors (GPUs) their computational powers have been utilized for general purpose computation. Initially by "exploiting" graphics APIs and recently through dedicated parallel computation frameworks such as the Compute Unified Device Architecture (CUDA) from Nvidia. This paper investigates multiple implementations of volumetric Mass-Spring-Damper systems in CUDA. The obtained performance is compared to previous implementations utilizing the GPU through the OpenGL graphics API. We find that both performance and optimization strategies differ widely between the OpenGL and CUDA implementations. Specifically, the previous recommendation of using implicitly connected particles is replaced by a recommendation that supports unstructured meshes and run-time topological changes with an insignificant performance reduction.

We present an extension of a self-respiratory technique to acquire 4D flow data. Self-navigation is obtained from k-space center profiles and the breathing signal is used in real time to gate the scan. The method allows us to acquire an isotropic non-angulated volume, 4D flow encoded, of the whole heart and great vessel in a single free-breathing scan. Results showed a strong correspondence between flow patterns obtained using this technique and with 2D flow. This approach represents an important advance for the characterization of the flow hemodynamics in the whole heart and a step forward to simplify cardiac MR examinations.