Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome.

Despite known histological, biological, and clinical differences between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), relatively little is known about the spatial differences in their corresponding immune contextures. Our study of over 1000 LUAD and LUSC tumors revealed that computationally derived patterns of tumor-infiltrating lymphocytes (TILs) on H&E images were different between LUAD (N = 421) and LUSC (N = 438), with TIL density being prognostic of overall survival in LUAD and spatial arrangement being more prognostically relevant in LUSC. In addition, the LUAD-specific TIL signature was associated with OS in an external validation set of 100 NSCLC treated with more than six different neoadjuvant chemotherapy regimens, and predictive of response to therapy in the clinical trial CA209-057 (n = 303). In LUAD, the prognostic TIL signature was primarily comprised of CD4+ T and CD8+ T cells, whereas in LUSC, the immune patterns were comprised of CD4+ T, CD8+ T, and CD20+ B cells. In both subtypes, prognostic TIL features were associated with transcriptomics-derived immune scores and biological pathways implicated in immune recognition, response, and evasion. Our results suggest the need for histologic subtype-specific TIL-based models for stratifying survival risk and predicting response to therapy. Our findings suggest that predictive models for response to therapy will need to account for the unique morphologic and molecular immune patterns as a function of histologic subtype of NSCLC

Wide-field modulated imaging for non-invasive quantification of tissue properties: a method development study

Modulated Imaging (MI) is a recently reported method for rapid, non-invasive quantification of tissue optical properties (reduced scattering, µs and absorption, µa), which can be performed across a range of optical wavelengths to determine chromophore concentrations. In this thesis, development and characterization of a compact, low cost MI system is reported, using off-the-shelf hardware components with a custom software interface capable of easy modification for specific applications. This prototype setup consists of a color CCD camera which captures the diffusely reflected light from an object illuminated with patterns generated by a miniature projector. Broadband white light from the projector is delivered through a filter wheel containing narrowband filters for measurement at 420nm, 570nm, and 620nm wavelengths. A software application in MATLAB was written to control and synchronize the phase-shifted illumination patterns with image acquisition, and perform processing of image data into optical property maps. System accuracy was characterized by measuring a series of tissue simulating phantoms fabricated with varying µs and µa, with both the prototype platform and a commercially available MI system as a reference. The overall error of the prototype system, for µs ranging from 0.93-2.23mm-1 and µa ranging from 0.009-0.049mm-1, was approximately 10% and 16%, respectively. Utilizing a lookup table that requires measurements at two illumination spatial frequencies instead of performing a least-squares fit to diffuse reflectance measurements at ten frequencies reduced the acquisition and processing time by 80%, while reducing the accuracy of optical property determination by approximately 3%. In summary, a prototype MI platform was developed and shown to be capable of quantifying the optical properties within biologically relevant µs and µa ranges. The system was assembled for less than 10% of the cost of commercially available systems while enabling individual components to be upgraded for a wider range of accurate optical property determination. Scattering and absorption maps obtained at multiple wavelengths can subsequently be used to quantify the concentrations of various tissue chromophores including hemoglobin, water, and lipids. Non-invasive, image based acquisition of such information may have impact in medical applications, ultimately improving patient health through disease characterization and monitoring progress of treatment.M.S.Includes bibliographical referencesby Vipul Atulkumar Bax

The accuracy of dynamic predictive autofocusing for whole slide imaging

Context: Whole slide imaging (WSI) for digital pathology involves the rapid automated acquisition of multiple high-power fields from a microscope slide containing a tissue specimen. Capturing each field in the correct focal plane is essential to create high-quality digital images. Others have described a novel focusing method which reduces the number of focal planes required to generate accurate focus. However, this method was not applied dynamically in an automated WSI system under continuous motion. Aims: This report measures the accuracy of this method when applied in a rapid continuous scan mode using a dual sensor WSI system with interleaved acquisition of images. Methods: We acquired over 400 tiles in a "stop and go" scan mode, surveying the entire z depth in each tile and used this as ground truth. We compared this ground truth focal height to the focal height determined using a rapid 3-point focus algorithm applied dynamically in a continuous scanning mode. Results: Our data showed the average focal height error of 0.30 (±0.27) μm compared to ground truth, which is well within the system′s depth of field. On a tile by tile assessment, approximately 95% of the tiles were within the system′s depth of field. Further, this method was six times faster than acquiring tiles compared to the same method in a non-continuous scan mode. Conclusions: The data indicates that the method employed can yield a significant improvement in scan speed while maintaining highly accurate autofocusing

A Rare Case of Amyloid Goiter: Ultrasonographic Findings and Thioflavin T Staining

Background: Clinically significant enlargement of the thyroid gland by amyloid deposition is rare. A case study of 22-year-old lady with gradual enlargement of the thyroid gland has been presented. Routine haemological, biochemical test including thyroid function tests were normal. Ultrasonographic findings were nonspecific. Amyloid goiter has to be differentiated from other types of goitre and malignancy. FNAC was found to be suspicious for the presence of amyloid. Special staining with thioflavin T confirmed amyloid deposition

Water pollution of Sabarmati River—a Harbinger to potential disaster

River Sabarmati is one of the biggest and major river of Gujarat that runs through two major cities of Gujarat, Gandhinagar and Ahmedabad and finally meets the Gulf of Khambhat (GoK) in the Arabian Sea. A study was conducted to evaluate the water quality of this river, as it could possibly be one of the major sources for filling up Kalpasar, the proposed man-made freshwater reservoir supposed to be the biggest one in the world. A total of nine sampling stations were established covering 163 km stretch of the river from upstream of Gandhinagar city to Vataman near Sabarmati estuary. Physicochemical (temprature, pH, salinity, chloride, total dissolved solids, turbidity, dissolved oxygen, biochemical oxygen demand, phenol, and petroleum hydrocarbons), biological (phytoplankton), and microbiological (total and selective bacterial count) analyses indicated that the river stretch from Ahmedabad-Vasana barriage to Vataman was highly polluted due to perennial waste discharges mainly from municipal drainage and industries. An implementation of sustainable management plan with proper treatment of both municipal and industrial effluents is essential to prevent further deterioration of the water quality of this river

New Technologies to Image Tumors.

The premise of this book is the importance of the tumor microenvironment (TME). Until recently, most research on and clinical attention to cancer biology, diagnosis, and prognosis were focused on the malignant (or premalignant) cellular compartment that could be readily appreciated using standard morphology-based imaging

Deep computational image analysis of immune cell niches reveals treatment-specific outcome associations in lung cancer

Abstract The tumor immune composition influences prognosis and treatment sensitivity in lung cancer. The presence of effective adaptive immune responses is associated with increased clinical benefit after immune checkpoint blockers. Conversely, immunotherapy resistance can occur as a consequence of local T-cell exhaustion/dysfunction and upregulation of immunosuppressive signals and regulatory cells. Consequently, merely measuring the amount of tumor-infiltrating lymphocytes (TILs) may not accurately reflect the complexity of tumor-immune interactions and T-cell functional states and may not be valuable as a treatment-specific biomarker. In this work, we investigate an immune-related biomarker (PhenoTIL) and its value in associating with treatment-specific outcomes in non-small cell lung cancer (NSCLC). PhenoTIL is a novel computational pathology approach that uses machine learning to capture spatial interplay and infer functional features of immune cell niches associated with tumor rejection and patient outcomes. PhenoTIL’s advantage is the computational characterization of the tumor immune microenvironment extracted from H&E-stained preparations. Association with clinical outcome and major non-small cell lung cancer (NSCLC) histology variants was studied in baseline tumor specimens from 1,774 lung cancer patients treated with immunotherapy and/or chemotherapy, including the clinical trial Checkmate 057 (NCT01673867)

Scoring PD-L1 Expression in Urothelial Carcinoma: An International Multi-Institutional Study on Comparison of Manual and Artificial Intelligence Measurement Model (AIM-PD-L1) Pathology Assessments

International audienceAssessing programmed death ligand 1 (PD-L1) expression on tumor cells (TCs) using Food and Drug Administration-approved, validated immunoassays can guide the use of immune checkpoint inhibitor (ICI) therapy in cancer treatment. However, substantial interobserver variability has been reported using these immunoassays. Artificial intelligence (AI) has the potential to accurately measure biomarker expression in tissue samples, but its reliability and comparability to standard manual scoring remain to be evaluated. This multinational study sought to compare the %TC scoring of PD-L1 expression in advanced urothelial carcinoma, assessed by either an AI Measurement Model (AIM-PD-L1) or expert pathologists. The concordance among pathologists and between pathologists and AIM-PD-L1 was determined. The positivity rate of >= 1%TC PD-L1 was between 20-30% for 8/10 pathologists, and the degree of agreement and scoring distribution for among pathologists and between pathologists and AIM-PD-L1 was similar both scored as a continuous variable or using the pre-defined cutoff. Numerically higher score variation was observed with the 22C3 assay than with the 28-8 assay. A 2-h training module on the 28-8 assay did not significantly impact manual assessment. Cases exhibiting significantly higher variability in the assessment of PD-L1 expression (mean absolute deviation > 10) were found to have patterns of PD-L1 staining that were more challenging to interpret. An improved understanding of sources of manual scoring variability can be applied to PD-L1 expression analysis in the clinical setting. In the future, the application of AI algorithms could serve as a valuable reference guide for pathologists while scoring PD-L1