S762 Evaluation of Clinical Variables, Radiological Visual Analog Scoring, and Radiomics Features on MR Enterography for Characterizing Severe Inflammation and Fibrosis in Stricturing Crohn’s Disease
Notice bibliographique
Résumé
Introduction: Current non-invasive cross-sectional imaging modalities such as MR enterography (MRE) offer excellent diagnostic accuracy of Crohn’s disease (CD) strictures, but cannot accurately determine the extent of stricture fibrosis and inflammation. Radiomics, a quantitative image extraction analysis technology, may offer a solution. We present initial results for a machine-reader evaluation of severe inflammation and fibrosis in CD strictures via quantitative radiomic features and expert radiologist scoring of MRE. Methods: In this retrospective, single center, IRB-approved study, 51 patients (n=34 for discovery; n=17 for hold-out validation) had confirmed stricturing CD on MRE and histopathology from surgery within 15 weeks of MRE. Histopathological Stenosis Therapy & Research (STAR) scoring of specimens (range 0-100, scores ≥50 =severe) was the reference standard for both inflammation and fibrosis. An expert radiologist coordinated with the scoring pathologist to annotate the resected strictures on MRE and provide a global visual analog score (VAS, 0-100) assessment of inflammation and chronic non-inflammatory findings (fibrosis). 1852 3D radiomic features were extracted from the stricture regions on MRE, from which the most relevant feature subsets were identified via cross-validated machine learning analysis in the discovery cohort for differentiating between severe vs less severe inflammation and fibrosis. Radiomic features and VAS scores were evaluated against pathology-defined severe inflammation and fibrosis in the validation cohort via ROC analysis. Results: Two distinct sets of radiomic features capturing textural heterogeneity (patterns, local entropy) within strictures were significantly associated (p< 0.01) with severe inflammation and severe fibrosis; across both discovery (AUC=0.66, 0.76) and hold-out validation (AUCs =0.71,0.83) (Figure). Radiological VAS had an AUC=0.68 for identifying severe inflammation and AUC =0.47 for severe fibrosis. Combining radiomic features and VAS had no significant impact on predictor performance. Clinical variables including sex, age, Montreal classification and stricture type were not significantly associated severe inflammation or fibrosis, across discovery and validation groups (Table). Conclusion: Radiomic analysis shows improved performance in identifying severe inflammation and severe fibrosis in CD strictures on MRE compared to radiological visual assessment scoring and clinical variables.Figure 1.: Top-ranked radiomics features are distinctively associated with severe inflammation (top row, pattern-based) and severe fibrosis (bottom row, wavelets) on MRE. Also shown are radiological VAS for severe inflammation and severe fibrosis. Table 1. - Demographics and baseline clinical features of the cohort, segregating discovery and hold-out validation radiomic cohorts MRE Overall (N=51) Fibrosis Discovery Group (N=34) Fibrosis Validation Group (N=17) Inflammation Discovery Group (N=34) Inflammation Validation Group (N=17) Factor N Statistics N Statistics N Statistics P-value N Statistics N Statistics P-value Male Sex, n (%) 51 26 (51) 34 16 (47) 17 10 (57) 0.43 a 34 15 (44) 17 11 (65) 0.17 a Diagnosis age of IBD, median (range), yrs 51 21 (4-90) 34 24 (10-90) 17 20 (2-62) 0.88 c 34 20.5 (5-67) 17 25 (4-90) 0.79 c Diagnosis age of Stricture, median (range), yrs 51 32 (11-90) 34 30.5 (19-90) 17 33 (11-69) 0.78 c 34 29.5 (11-71) 17 35 (20-90) 0.24 c Age at MRE, median (range), yrs 51 34 (18-91) 34 33 (19-91) 17 36 (18-69) 0.83 c 34 31 (18-71) 17 37 (22-91) 0.21 c Duration between IBD/stricture dx, median (range), years 51 8 (0-30) 34 6.5 (0-30) 17 10 (0-26) 0.62 c 34 7.5 (0-30) 17 8 (0-21) 0.8 c Duration between Stricture dx/Surgery, median (range), months 51 9 (0-145) 51 10 (0-145) 17 6 (0-121) 0.82 c 34 5.5 (0-145) 17 19 (0-78) 0.24 c Duration between MRE and resection, median (range), weeks 51 7.1 (0-15) 34 7.35 (0-13) 17 7 (0.9-15) 0.36 c 34 7.9 (0.1-15) 17 7.1 (0-14.9) 0.93 c Obstructive Symptoms at time of imaging, n (%) 51 42 (82) 34 28 (82) 17 14 (82) 1 b 34 27 (79) 17 15 (88) 0.7 b CD Montreal Classification, n (%) 51 34 17 0.64 a 34 17 0.14 a B2 (Stricturing) 23 (45) 14 (41) 9 (53) 17 (50) 6 (35) B2p (Stricturing with perianal disease) 15 (29) 11 (32) 4 (23) 11 (32) 4 (23) B3 (Fistulizing) 6 (12) 5 (15) 1 (6) 4 (12) 2 (12) B3p (Fistulizing with perianal disease) 7 (14) 4 (12) 3 (18) 2 (6) 5 (29) History of extraintestinal manifestations, n (%) 51 32 (63) 34 22 (65) 17 10 (59) 0.68 a 34 22 (65) 17 10 (59) 0.68 a Ileocecal resection prior to current stricture, n (%) 51 25 (49) 34 17 (50) 17 8 (47) 0.84 a 34 16 (47) 17 9 (53) 0.69 a Number of resections, median (range) 25 2 (1-5) 16 2 (1-5) 8 2 (1-4) 0.88 c 16 2 (1-4) 2 (1-5) 0.94 c Type of stricture, n (%) 51 34 17 1 a 34 17 1 a Naïve 27 (53) 18 (53) 9 (53) 18 (53) 9 (53) Anastomotic 24 (47) 16 (47) 8 (47) 16 (47) 8 (47) Medications for IBD < 8 weeks from imaging, n (%) 51 34 17 34 17 5-aminosalicylic-acid, oral or rectal 10 (20) 8 (24) 2 (12) 0.46 b 6 (18) 4 (24) 0.71 b Steroid, systematic 19 (37) 11 (32) 8 (47) 0.31 a 12 (35) 7 (41) 0.68 a Steroid, rectal or Budesonide 12 (24) 9 (27) 3 (18) 0.73 b 8 (24) 4 (24) 1 b Mercaptopurine or Azathioprine 12 (24) 7 (21) 5 (29) 0.5 b 10 (29) 2 (12) 0.29 b Methotrexate 2 (4) 2 (6) 0 (0) 0.55 b 1 (3) 1 (6) 1 b Certolizumab 2 (4) 2 (6) 0 (0) 0.55 b 1 (3) 1 (6) 1 b Adalimumab 13 (25) 10 (29) 3 (18) 0.5 b 8 (24) 5 (29) 0.74 b Infliximab 5 (10) 3 (9) 2 (12) 1 b 4 (12) 1 (6) 0.65 b Vedolizumab 5 (10) 4 (12) 1 (6) 0.65 b 2 (6) 3 (18) 0.32 b None 6 (12) 4 (12) 1 (6) 0.65 b 4 (12) 1 (6) 0.65 b Global Assessments by Radiologist Global Stricture Severity, median (range), 0-100 51 60 (20-100) 34 50 (20-100) 17 60 (20-100) 0.4 c 34 60 (20-100) 17 40 (20-95) 0.44 c Global Inflammation Severity, median (range), 0-100 51 40 (15-95) 34 40 (15-85) 17 50 (15-95) 0.27 c 34 40 (15-85) 17 40 (15-95) 0.7 c Global Chronic non-inflammatory changes Severity, median (range), 0-100 51 30 (5-80) 34 30 (5-80) 17 40 (5-80) 0.16 c 34 30 (5-80) 17 30 (5-70) 0.89 c Global Assessments by Pathologist Severity of inflammation, median (range), 0-100 51 66 (2-100) 34 67 (2-100) 17 64 (10-94) 0.52 c 34 61.5 (2-100) 17 67 (10-100) 0.73 c Severity of fibrosis, median (range), 0-100 51 60 (5-94) 34 60 (5-94) 17 55 (10-88) 0.93 c 34 57.5 (5-94) 17 63 (10-90) 0.93 c aChi-Square testbFisher exact testcMann Whitney U test.MRE: magnetic resonance enterography; N: Number; IBD: inflammatory bowel disease; dx: diagnosis; CD: Crohn’s disease.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».