Your browser doesn't support javascript.
loading
Automated detection of white matter and cortical lesions in early stages of multiple sclerosis.
Fartaria, Mário João; Bonnier, Guillaume; Roche, Alexis; Kober, Tobias; Meuli, Reto; Rotzinger, David; Frackowiak, Richard; Schluep, Myriam; Du Pasquier, Renaud; Thiran, Jean-Philippe; Krueger, Gunnar; Bach Cuadra, Meritxell; Granziera, Cristina.
Afiliación
  • Fartaria MJ; Advanced Clinical Imaging Technology (HC CMEA SUI DI BM PI), Siemens Healthcare AG, Lausanne, Switzerland.
  • Bonnier G; Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Roche A; Advanced Clinical Imaging Technology (HC CMEA SUI DI BM PI), Siemens Healthcare AG, Lausanne, Switzerland.
  • Kober T; Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Meuli R; Laboratoire de Recherché en Neuroimagérie (LREN), Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
  • Rotzinger D; Advanced Clinical Imaging Technology (HC CMEA SUI DI BM PI), Siemens Healthcare AG, Lausanne, Switzerland.
  • Frackowiak R; Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Schluep M; Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
  • Du Pasquier R; Advanced Clinical Imaging Technology (HC CMEA SUI DI BM PI), Siemens Healthcare AG, Lausanne, Switzerland.
  • Thiran JP; Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Krueger G; Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
  • Bach Cuadra M; Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
  • Granziera C; Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
J Magn Reson Imaging ; 43(6): 1445-54, 2016 06.
Article en En | MEDLINE | ID: mdl-26606758
ABSTRACT

PURPOSE:

To develop a method to automatically detect multiple sclerosis (MS) lesions, located both in white matter (WM) and in the cortex, in patients with low disability and early disease stage. MATERIALS AND

METHODS:

We developed a lesion detection method, based on the k-nearest neighbor (k-NN) technique, to detect lesions as small as 0.0036 mL. This method uses the image intensity information from up to four different 3D magnetic resonance imaging (MRI) sequences (magnetization-prepared rapid gradient-echo, MPRAGE; magnetization-prepared two inversion-contrast rapid gradient-echo, MP2RAGE; 3D fluid-attenuated inversion recovery, FLAIR; and 3D double-inversion recovery, DIR), acquired on a 3T scanner. To these intensity features we added the information obtained by the spatial coordinates and tissue prior probabilities provided by the International Consortium for Brain Mapping (ICBM). Quantitative assessment was done in 39 early-stage MS patients with a "leave-one-out" cross-validation.

RESULTS:

The best lesion detection rate (DR) performance in WM was obtained using MP2RAGE, FLAIR, and DIR intensities (77% for lesions ≥0.0036 mL; 85% for lesions ≥0.005 mL). Similar results were obtained excluding the DIR intensity as well as when using only MPRAGE and FLAIR (DR = 75%, P = 0.5720). However, the combination of FLAIR with DIR and MP2RAGE appeared to be the best for detecting cortical lesions (DR = 62%), compared to the other combination of sequences (P < 0.001).

CONCLUSION:

For WM lesion detection, similar results were observed when only conventional clinical sequences (FLAIR, MPRAGE) were used compared to a combination of conventional and "advanced" sequences (MP2RAGE, DIR). Cortical lesion detection increased significantly when "advanced" sequences were used. J. Magn. Reson. Imaging 2015. J. Magn. Reson. Imaging 2016;431445-1454.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Reconocimiento de Normas Patrones Automatizadas / Interpretación de Imagen Asistida por Computador / Corteza Cerebral / Imagen de Difusión Tensora / Sustancia Blanca / Esclerosis Múltiple Tipo de estudio: Diagnostic_studies / Evaluation_studies / Screening_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: J Magn Reson Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2016 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Reconocimiento de Normas Patrones Automatizadas / Interpretación de Imagen Asistida por Computador / Corteza Cerebral / Imagen de Difusión Tensora / Sustancia Blanca / Esclerosis Múltiple Tipo de estudio: Diagnostic_studies / Evaluation_studies / Screening_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: J Magn Reson Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2016 Tipo del documento: Article País de afiliación: Suiza