Clinical Features, Non-Contrast CT Radiomic and Radiological Signs in Models for the Prediction of Hematoma Expansion in Intracerebral Hemorrhage

被引:2
|
作者
Chen, Zejia Frank [1 ]
Zhang, Liying [1 ]
Carrington, Andre M. [1 ,2 ,3 ]
Thornhill, Rebecca [2 ]
Miguel, Olivier [1 ,2 ]
Auriat, Angela M. [1 ,2 ]
Omid-Fard, Nima [2 ]
Hiremath, Shivaprakash [2 ]
Tshemeister Abitbul, Vered [1 ,2 ]
Dowlatshahi, Dar [1 ,4 ]
Demchuk, Andrew [5 ]
Gladstone, David [6 ]
Morotti, Andrea [7 ]
Casetta, Ilaria [8 ]
Fainardi, Enrico [9 ]
Huynh, Thien [10 ,11 ]
Elkabouli, Marah [1 ]
Talbot, Zoe [1 ]
Melkus, Gerd [1 ,2 ]
Aviv, Richard, I [1 ,2 ,12 ]
机构
[1] Ottawa Hosp Res Inst, Ottawa, ON, Canada
[2] Univ Ottawa, Dept Radiol Radiat Oncol & Med Phys, Ottawa, ON, Canada
[3] Univ Waterloo, Dept Syst Design Engn, Waterloo, ON, Canada
[4] Univ Ottawa, Dept Med Neurol, Ottawa, ON, Canada
[5] Foothills Med Ctr, Dept Med Neurol, Calgary, AB, Canada
[6] Univ Toronto, Sunnybrook Hlth Sci Ctr, Dept Med Neurol, Toronto, ON, Canada
[7] ASST Spedali Civili Brescia, Dept Neurol Sci & Vis, Neurol Unit, Brescia, Italy
[8] Univ Ferrara, Neurol Clin, Ferrara, Italy
[9] Univ Florence, Dept Expt & Clin Biomed Sci, Neuroradiol Unit, Florence, Italy
[10] Mayo Clin, Dept Radiol, Jacksonville, FL USA
[11] Mayo Clin, Dept Neurosurg, Jacksonville, FL USA
[12] Univ Ottawa, Ottawa Hosp, Dept Radiol, Gen Campus,CPCR Bldg,Room L2121, Ottawa, ON K1H 1M2, Canada
来源
CANADIAN ASSOCIATION OF RADIOLOGISTS JOURNAL-JOURNAL DE L ASSOCIATION CANADIENNE DES RADIOLOGISTES | 2023年 / 74卷 / 04期
基金
加拿大创新基金会;
关键词
hematoma expansion; intracerebral hemorrhage; radiomics; machine learning; non-contrast CT; NONCONTRAST COMPUTED-TOMOGRAPHY; GROWTH; SCORES;
D O I
10.1177/08465371231168383
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
PurposeRapid identification of hematoma expansion (HE) risk at baseline is a priority in intracerebral hemorrhage (ICH) patients and may impact clinical decision making. Predictive scores using clinical features and Non-Contract Computed Tomography (NCCT)-based features exist, however, the extent to which each feature set contributes to identification is limited. This paper aims to investigate the relative value of clinical, radiological, and radiomics features in HE prediction.MethodsOriginal data was retrospectively obtained from three major prospective clinical trials ["Spot Sign" Selection of Intracerebral Hemorrhage to Guide Hemostatic Therapy (SPOTLIGHT)NCT01359202; The Spot Sign for Predicting and Treating ICH Growth Study (STOP-IT)NCT00810888] Patients baseline and follow-up scans following ICH were included. Clinical, NCCT radiological, and radiomics features were extracted, and multivariate modeling was conducted on each feature set.Results317 patients from 38 sites met inclusion criteria. Warfarin use (p=0.001) and GCS score (p=0.046) were significant clinical predictors of HE. The best performing model for HE prediction included clinical, radiological, and radiomic features with an area under the curve (AUC) of 87.7%. NCCT radiological features improved upon clinical benchmark model AUC by 6.5% and a clinical & radiomic combination model by 6.4%. Addition of radiomics features improved goodness of fit of both clinical (p=0.012) and clinical & NCCT radiological (p=0.007) models, with marginal improvements on AUC. Inclusion of NCCT radiological signs was best for ruling out HE whereas the radiomic features were best for ruling in HE.ConclusionNCCT-based radiological and radiomics features can improve HE prediction when added to clinical features. Visual Abstract Objectif : L'identification rapide du risque d'expansion d'un hematome avant le debut des traitements est une priorite chez les patients ayant une hemorragie intracerebrale (HI) et elle peut avoir des consequences sur la prise de decisions cliniques. Il existe des scores predictifs utilisant les caracteristiques cliniques et les caracteristiques basees sur la tomodensitometrie sans contraste (TDM-sc). Toutefois, la portee de la contribution a l'identification de chaque ensemble de caracteristiques est limitee. Cet article vise a etudier la valeur relative des caracteristiques cliniques, radiologiques et radiomiques pour la prediction de l'expansion des hematomes. Methodes : Les donnees originales ont ete obtenues retrospectivement a partir de deux etudes cliniques prospectives majeures Spotlight et Spot-ITrr; : << Spot Sign >> Selection of Intracerebral Hemorrhage to Guide Hemostatic Therapy (SPOTLIGHT) (NCT01359202); The Spot Sign for Predicting and Treating ICH Growth Study (STOP-IT) (NCT00810888). Des examens d'imagerie de patients ayant souffert d'une HI effectues avant les traitements et au cours du suivi ont ete inclus. Les caracteristiques cliniques, radiologiques (TDM-sc) et radiomiques ont ete extraites et une modelisation multifactorielle a ete effectuee sur chaque ensemble de caracteristiques. Resultats : Une population de 317 patients provenant de 38 centres satisfaisait les criteres d'inclusion. L'utilisation de la warfarine (P = 0.001) et le score GCS (P = 0.046) ont ete des facteurs cliniques predictifs de l'expansion de l'hematome. Le modele le plus performant pour la prediction de l'expansion de l'hematome incluait les caracteristiques cliniques, radiologiques et radiomiques et presentait une aire sous la courbe (ASC) de 87.7 %. Les caracteristiques radiologiques (TDM-sc) ont ameliore de 6.5 % l'ASC du modele de reference clinique et de 6.4 % celle d'un modele combinant clinique et radiomique. L'ajout des caracteristiques radiomiques a ameliore la qualite d'adaptation des modeles cliniques et radiologiques (TDM-sc) avec une amelioration marginale de l'ASC. L'inclusion des signes radiologiques (TDM-sc) a ete le meilleur moyen d'ecarter un diagnostic d'hematome, tandis que les caracteristiques cliniques ont ete les meilleures pour confirmer son existence. Conclusions : Les caracteristiques radiologiques basees sur une TDM sans contraste et les caracteristiques radiomiques peuvent ameliorer la prediction de l'expansion d'un hematome intracerebral quand elles sont ajoutees aux caracteristiques cliniques.
引用
收藏
页码:713 / 722
页数:10
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