Your browser doesn't support javascript.
loading
Automated Registration and Color Labeling of Serial 3D Double Inversion Recovery MR Imaging for Detection of Lesion Progression in Multiple Sclerosis.
Park, Charlie C; Brummer, Marijn E; Sadigh, Gelareh; Saindane, Amit M; Mullins, Mark E; Allen, Jason W; Hu, Ranliang.
Afiliación
  • Park CC; Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1364 Clifton Road NE, Suite BG20, Atlanta, GA, 30322, USA.
  • Brummer ME; Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1364 Clifton Road NE, Suite BG20, Atlanta, GA, 30322, USA.
  • Sadigh G; Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1364 Clifton Road NE, Suite BG20, Atlanta, GA, 30322, USA.
  • Saindane AM; Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1364 Clifton Road NE, Suite BG20, Atlanta, GA, 30322, USA.
  • Mullins ME; Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1364 Clifton Road NE, Suite BG20, Atlanta, GA, 30322, USA.
  • Allen JW; Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1364 Clifton Road NE, Suite BG20, Atlanta, GA, 30322, USA.
  • Hu R; Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1364 Clifton Road NE, Suite BG20, Atlanta, GA, 30322, USA. ranliang.hu@emory.edu.
J Digit Imaging ; 36(2): 450-457, 2023 04.
Article en En | MEDLINE | ID: mdl-36352165
Automated co-registration and subtraction techniques have been shown to be useful in the assessment of longitudinal changes in multiple sclerosis (MS) lesion burden, but the majority depend on T2-fluid-attenuated inversion recovery sequences. We aimed to investigate the use of a novel automated temporal color complement imaging (CCI) map overlapped on 3D double inversion recovery (DIR), and to assess its diagnostic performance for detecting disease progression in patients with multiple sclerosis (MS) as compared to standard review of serial 3D DIR images. We developed a fully automated system that co-registers and compares baseline to follow-up 3D DIR images and outputs a pseudo-color RGB map in which red pixels indicate increased intensity values in the follow-up image (i.e., progression; new/enlarging lesion), blue-green pixels represent decreased intensity values (i.e., disappearing/shrinking lesion), and gray-scale pixels reflect unchanged intensity values. Three neuroradiologists blinded to clinical information independently reviewed each patient using standard DIR images alone and using CCI maps based on DIR images at two separate exams. Seventy-six follow-up examinations from 60 consecutive MS patients who underwent standard 3 T MR brain MS protocol that included 3D DIR were included. Median cohort age was 38.5 years, with 46 women, 59 relapsing-remitting type MS, and median follow-up interval of 250 days (interquartile range: 196-394 days). Lesion progression was detected in 67.1% of cases using CCI review versus 22.4% using standard review, with a total of 182 new or enlarged lesions using CCI review versus 28 using standard review. There was a statistically significant difference between the two methods in the rate of all progressive lesions (P < 0.001, McNemar's test) as well as cortical progressive lesions (P < 0.001). Automated CCI maps using co-registered serial 3D DIR, compared to standard review of 3D DIR alone, increased detection rate of MS lesion progression in patients undergoing clinical brain MRI exam.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Esclerosis Múltiple Tipo de estudio: Diagnostic_studies / Guideline Límite: Female / Humans / Infant Idioma: En Revista: J Digit Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM / INFORMATICA MEDICA / RADIOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Esclerosis Múltiple Tipo de estudio: Diagnostic_studies / Guideline Límite: Female / Humans / Infant Idioma: En Revista: J Digit Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM / INFORMATICA MEDICA / RADIOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos