Motivation: This study presents a novel nonlinear model which can predict 10-year carotid ultrasound image-based phenotypes by fusing nine traditional cardiovascular risk factors (ethnicity, gender, age, artery type, body mass index, hemoglobin A1c, hypertension, low-density lipoprotein, and smoking) with five types of carotid automated image phenotypes (three types of carotid intima-media thickness (IMT), wall variability, and total plaque area). Methodology: Two-step process was adapted: First, five baseline carotid image-based phenotypes were automatically measured using AtheroEdge ™ (AtheroPoint ™ , CA, USA) system by two operators (novice and experienced) and an expert. Second, based on the annual progression rates of cIMT due to nine traditional cardiovascular risk factors, a novel nonlinear model was adapted for 10-year predictions of carotid phenotypes. Results: Institute review board (IRB) approved 204 Japanese patients’ left/right common carotid artery (407 ultrasound scans) was collected with a mean age of 69 ± 11 years. Age and hemoglobin were reported to have a high influence on the 10-year carotid phenotypes. Mean correlation coefficient (CC) between 10-year carotid image-based phenotype and age was improved by 39.35% in males and 25.38% in females. The area under the curves for the 10-year measurements of five phenotypes IMT ave10yr , IMT max10yr , IMT min10yr , IMTV 10yr , and TPA 10yr were 0.96, 0.94, 0.90, 1.0, and 1.0. Inter-operator variability between two operators showed significant CC (P < 0.0001). Conclusions: A nonlinear model was developed and validated by fusing nine conventional CV risk factors with current carotid image-based phenotypes for predicting the 10-year carotid ultrasound image-based phenotypes which may be used risk assessment.

Nonlinear model for the carotid artery disease 10-year risk prediction by fusing conventional cardiovascular factors to carotid ultrasound image phenotypes: A Japanese diabetes cohort study

Piga M.;Saba L.;Carcassi C.;
2019-01-01

Abstract

Motivation: This study presents a novel nonlinear model which can predict 10-year carotid ultrasound image-based phenotypes by fusing nine traditional cardiovascular risk factors (ethnicity, gender, age, artery type, body mass index, hemoglobin A1c, hypertension, low-density lipoprotein, and smoking) with five types of carotid automated image phenotypes (three types of carotid intima-media thickness (IMT), wall variability, and total plaque area). Methodology: Two-step process was adapted: First, five baseline carotid image-based phenotypes were automatically measured using AtheroEdge ™ (AtheroPoint ™ , CA, USA) system by two operators (novice and experienced) and an expert. Second, based on the annual progression rates of cIMT due to nine traditional cardiovascular risk factors, a novel nonlinear model was adapted for 10-year predictions of carotid phenotypes. Results: Institute review board (IRB) approved 204 Japanese patients’ left/right common carotid artery (407 ultrasound scans) was collected with a mean age of 69 ± 11 years. Age and hemoglobin were reported to have a high influence on the 10-year carotid phenotypes. Mean correlation coefficient (CC) between 10-year carotid image-based phenotype and age was improved by 39.35% in males and 25.38% in females. The area under the curves for the 10-year measurements of five phenotypes IMT ave10yr , IMT max10yr , IMT min10yr , IMTV 10yr , and TPA 10yr were 0.96, 0.94, 0.90, 1.0, and 1.0. Inter-operator variability between two operators showed significant CC (P < 0.0001). Conclusions: A nonlinear model was developed and validated by fusing nine conventional CV risk factors with current carotid image-based phenotypes for predicting the 10-year carotid ultrasound image-based phenotypes which may be used risk assessment.
2019
10-year risk prediction; atherosclerosis; carotid; intima-media thickness; nonlinear modeling; stroke; total plaque area; traditional cardiovascular risk; ultrasound; Aged; Carotid Arteries; Carotid Artery Diseases; Cohort Studies; Female; Humans; Japan; Male; Middle Aged; Predictive Value of Tests; Risk Assessment; Ultrasonography; Diabetes Mellitus
File in questo prodotto:
File Dimensione Formato  
khanna2019 altro.pdf

Solo gestori archivio

Tipologia: versione editoriale
Dimensione 2.14 MB
Formato Adobe PDF
2.14 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/283903
Citazioni
  • ???jsp.display-item.citation.pmc??? 16
  • Scopus 44
  • ???jsp.display-item.citation.isi??? 41
social impact