Evidence map›Paper›PMID 41864910›Full record

ArticleDiagnostic pathology2026

Development and validation of a computer program for histoanatomical morphometric analysis of the bowel wall in children with Hirschsprung's disease.

Tebin Hawez, Tobias Erlöv, Christina Granéli, Gustav Andersson, Tyra Lundberg, Emma Fransson, Maria Evertsson, Magnus Cinthio, Pernilla Stenström

Abstract readValidation Study
In one paragraph

Article in Diagnostic pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Tebin HawezDepartment of Clinical Sciences Lund/Pediatrics, Lund University, Lund, Sweden. tebin.hawez@med.lu.se.
Tobias ErlövDepartment of Biomedical Engineering, The Faculty of Engineering, Lund University, Lund, Sweden.
Christina GranéliDepartment of Clinical Sciences Lund/Pediatrics, Lund University, Lund, Sweden.
Gustav AnderssonDepartment of Clinical Genetics, Pathology and Molecular Diagnostics, Skåne University Hospital, Lund, Sweden.
Tyra LundbergDepartment of Clinical Sciences Lund/Pediatrics, Lund University, Lund, Sweden.
Emma FranssonDepartment of Clinical Sciences Lund/Pediatrics, Lund University, Lund, Sweden.
Maria EvertssonDepartment of Clinical Sciences Lund/Biomedical Engineering, Lund University, Lund, Sweden.
Magnus CinthioDepartment of Biomedical Engineering, The Faculty of Engineering, Lund University, Lund, Sweden.
Pernilla StenströmDepartment of Clinical Sciences Lund/Pediatrics, Lund University, Lund, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDeveloping new diagnostic imaging methods that provide detailed visualization of the histoanatomy of tissues and organs requires precise histomorphometric evaluation. With a particular focus on bowel, this study aimed to develop and validate a computer program for reliable and efficient assessment of bowel wall histomorphometry.

methodsA MATLAB-based computer program was developed in-house to manually delineate and automatically calculate mean layer thickness of the muscularis propria layers, submucosa and mucosa in histopathology images of bowel wall specimens from patients operated on for Hirschsprung’s disease. Validation included assessment of inter- and intra-observer reliability and agreement for generated mean thicknesses, as well as comparison with manual measurements (mean of 10 thickness measurement points). Reliability was assessed through intraclass correlation coefficient (ICC) (good > 0.75) and agreement through Bland-Altman analysis (good= mean close to zero and spread within 2 standard deviations).

resultsThe program allowed for import of histopathology images for bowel wall layer analysis. After manual layer delineation, the program automatically calculated mean layer thickness (mm) ± standard deviation based on approximately 3000 measurement points. For the inter-observer analyses the reliability was moderate to good in the majority of the histoanatomic layers (ICC range 0.6–0.9) and agreement was similarly good based on the Bland-Altman analyses. Also, the intra-observer reliability ranged between good and excellent in the majority of histoanatomic layers (ICC range 0.7-1.0). The high-precision layer delineation and mean thickness extraction per image took 15 min, compared to 60 min for manual measurement.

conclusionsThe developed computer program enables precise and time-efficient measurements of histoanatomic layer thicknesses in histopathology images of bowel wall, with good reliabilities and agreements between examinators. The program’s application is useful in histomorphometric evaluations for advancing diagnostic imaging techniques.

Indexed as

Hirschsprung DiseaseImage Interpretation, Computer-AssistedSoftwareChildChild, PreschoolFemaleHumansInfantMaleObserver VariationPredictive Value of TestsReproducibility of ResultsBowel wallComputer programHistoanatomical morphometricsHistopathology

Identifiers

PMID41864910
PMCPMC13063597

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