Measuring Histologic Activity in Inflammatory Bowel Disease: Why and How

"Clinicians Are From Mars and Pathologists Are From Venus" Revisited: Synoptic Reports Improve Clinician Comprehension of Pathology Reports in Inflammatory Bowel Disease

CONTEXT.—

A prior study in this journal, "Clinicians Are from Mars and Pathologists Are From Venus," demonstrated that clinicians can erroneously interpret pathology reports up to 30% of the time. After noticing reporting heterogeneity in the setting of inflammatory bowel disease (IBD), we speculated that a standardized synoptic report could improve gastroenterologist comprehension.

OBJECTIVE.—

To investigate the effect of a synoptic table on gastroenterologist comprehension of IBD pathology reports.

DESIGN.—

We recruited gastroenterology fellows and faculty to participate in this study. All participants were given 6 pathology reports and asked if the following were present: active inflammation, chronic inflammation, IBD, and dysplasia. Participants were also asked to rate their confidence. After a 6-week washout period, the same questionnaire was distributed with a synoptic report. We performed paired t-tests to compare the mean accuracy and confidence scores between the preintervention and postintervention responses.

RESULTS.—

A total of 39 physicians participated: 9 fellows and 30 faculty. Mean accuracy scores were higher after the intervention (0.81 versus 0.86; P < .001). Mean confidence was also higher after intervention, but this was not statistically significant (3.91 versus 3.98; P = .24).

CONCLUSIONS.—

The improvement in accuracy scores after intervention confirms that clinician comprehension improved with the synoptic table. A synoptic report may provide a standardized way of communicating diagnostic information to clinicians in the setting of IBD and potentially other inflammatory conditions.

Histologic assessments in ulcerative colitis: the evidence behind a new endpoint in clinical trials

INTRODUCTION

Treatment goals for ulcerative colitis (UC) are evolving from the achievement of clinical remission to more rigorous goals defined by endoscopic and histologic healing. Achievement of deeper remission targets aims to reduce the risk of colectomy, hospitalizations, and colorectal cancer.

AREAS COVERED

This review covers histologic assessments, histologic remission as a clinical trial endpoint, and the association between histologic disease activity and clinical outcomes. Future directions are also discussed, including the use of advanced imaging and artificial intelligence technologies, as well as potential future treatment targets beyond histologic remission.

EXPERT OPINION

Histologic assessments are used for their sensitivity in measuring mucosal inflammatory changes in UC. Due to correlation with disease activity, histologic assessments may support clinical decision-making regarding treatment decisions as such assessments can be associated with rates of clinical relapse, hospitalization, colectomy, and neoplasia. While histologic remission is limited by varying definitions and multiple histologic indices, work is ongoing to create a consensus on the use of histologic assessments in clinical trials. As research advances, aspirational targets beyond histologic remission, such as molecular healing and disease clearance, are being explored.

Automating Ground Truth Annotations for Gland Segmentation Through Immunohistochemistry

Microscopic evaluation of glands in the colon is of utmost importance in the diagnosis of inflammatory bowel disease and cancer. When properly trained, deep learning pipelines can provide a systematic, reproducible, and quantitative assessment of disease-related changes in glandular tissue architecture. The training and testing of deep learning models require large amounts of manual annotations, which are difficult, time-consuming, and expensive to obtain. Here, we propose a method for automated generation of ground truth in digital hematoxylin and eosin (H&E)-stained slides using immunohistochemistry (IHC) labels. The image processing pipeline generates annotations of glands in H&E histopathology images from colon biopsy specimens by transfer of gland masks from KRT8/18, CDX2, or EPCAM IHC. The IHC gland outlines are transferred to coregistered H&E images for training of deep learning models. We compared the performance of the deep learning models to that of manual annotations using an internal held-out set of biopsy specimens as well as 2 public data sets. Our results show that EPCAM IHC provides gland outlines that closely match manual gland annotations (Dice = 0.89) and are resilient to damage by inflammation. In addition, we propose a simple data sampling technique that allows models trained on data from several sources to be adapted to a new data source using just a few newly annotated samples. The best performing models achieved average Dice scores of 0.902 and 0.89 on Gland Segmentation and Colorectal Adenocarcinoma Gland colon cancer public data sets, respectively, when trained with only 10% of annotated cases from either public cohort. Altogether, the performances of our models indicate that automated annotations using cell type-specific IHC markers can safely replace manual annotations. Automated IHC labels from single-institution cohorts can be combined with small numbers of hand-annotated cases from multi-institutional cohorts to train models that generalize well to diverse data sources.

Evaluation of Disease Activity in Inflammatory Bowel Disease: Diagnostic Tools in the Assessment of Histological Healing

Inflammatory bowel disease (IBD) comprises two types of chronic intestinal disorders: Crohn's disease and ulcerative colitis. In long-standing ulcerative colitis disease activity, histological persistent inflammation has been linked to an increased risk of relapse, and long-term corticosteroid use, even when endoscopic remission is reached. In Crohn's disease, the discontinuous nature of lesions and transmural inflammation have limited the standardized histological assessment. The current evidence from research proposes that besides clinical and endoscopic healing, the achievement of histological healing constitutes an endpoint to assess disease activity and remission in IBD patients concerning better long-term disease outcomes. Histological alterations may persist even in the absence of endoscopic lesions. For these reasons, new advanced techniques promise to revolutionize the field of IBD by improving the endoscopic and histologic assessment, disease characterization, and ultimately patient care, with an established role in daily practice for objective assessment of lesions. This review outlines the importance of including microscopic evaluation in IBD, highlighting the clinical benefits of a deep state of disease remission using validated diagnostic methods and scoring systems for daily clinical practice.

Artificial Intelligence Enables Quantitative Assessment of Ulcerative Colitis Histology

Ulcerative colitis is a chronic inflammatory bowel disease that is characterized by a relapsing and remitting course. Assessment of disease activity critically informs treatment decisions. In addition to endoscopic remission, histologic remission is emerging as a treatment target and a key factor in the evaluation of disease activity and therapeutic efficacy. However, manual pathologist evaluation is semiquantitative and limited in granularity. Machine learning approaches are increasingly being developed to aid pathologists in accurate and reproducible scoring of histology, enabling precise quantitation of clinically relevant features. Here, we report the development and validation of convolutional neural network models that quantify histologic features pertinent to ulcerative colitis disease activity, directly from hematoxylin and eosin-stained whole slide images. Tissue and cell model predictions were used to generate quantitative human-interpretable features to fully characterize the histology samples. Tissue and cell predictions showed comparable agreement to pathologist annotations, and the extracted slide-level human-interpretable features demonstrated strong correlations with disease severity and pathologist-assigned Nancy histological index scores. Moreover, using a random forest classifier based on 13 human-interpretable features derived from the tissue and cell models, we were able to accurately predict Nancy histological index scores, with a weighted kappa (κ = 0.91) and Spearman correlation (⍴ = 0.89, P < .001) when compared with pathologist consensus Nancy histological index scores. We were also able to predict histologic remission, based on the absence of neutrophil extravasation, with a high accuracy of 0.97. This work demonstrates the potential of computer vision to enable a standardized and robust assessment of ulcerative colitis histopathology for translational research and improved evaluation of disease activity and prognosis.

Histopathological assessment of the microscopic activity in inflammatory bowel diseases: What are we looking for?

Advances in diagnostics of inflammatory bowel diseases (IBD) and improved treatment strategies allowed the establishment of new therapeutic endpoints. Currently, it is desirable not only to cease clinical symptoms, but mainly to achieve endoscopic remission, a macroscopic normalization of the bowel mucosa. However, up to one-third of IBD patients in remission exhibit persisting microscopic activity of the disease. The evidence suggests a better predictive value of histology for the development of clinical complications such as clinical relapse, surgical intervention, need for therapy escalation, or development of colorectal cancer. The proper assessment of microscopic inflammatory activity thus became an important part of the overall histopathological evaluation of colonic biopsies and many histopathological scoring indices have been established. Nonetheless, a majority of them have not been validated and no scoring index became a part of the routine bioptic practice. This review summarizes a predictive value of microscopic disease activity assessment for the subsequent clinical course of IBD, describes the most commonly used scoring indices for Crohn's disease and ulcerative colitis, and comments on current limitations and unresolved issues.

Histological Scores in Patients with Inflammatory Bowel Diseases: The State of the Art

The histological assessment has been advocated as a detailed and accurate measure of disease activity in inflammatory bowel diseases (IBD). In ulcerative colitis (UC), histological activity has been demonstrated to be associated with higher rates of relapse, prolonged corticosteroid use and long-term complications, even when endoscopic remission is achieved. Therefore, histological healing may represent a potential treatment target. Several histological scores have been developed and are available today. The Robarts histopathology index (RHI) and the Nancy index (NI) are the only two recommended by the European Crohn’s and Colitis Organization (ECCO) for use in patients with UC. Conversely, in Crohn’s disease (CD), the discontinuous nature of lesions has limited standardized histological assessment. Most of the available histological scoring systems in CD are complex and not validated. The aim of this review is to comprehensively summarize the latest evidence regarding histological scoring systems in IBD. We guide the reader through understanding the importance of an accurate microscopic evaluation using validated scoring systems, highlighting the strengths and pitfalls of each score. The priorities of future research needs are also addressed.