title: Whole-liver diffusion-weighted MRI histogram analysis: effect of the presence of colorectal hepatic metastases on the remaining liver parenchyma.
abstract: OBJECTIVE
  To explore whether whole-liver diffusion-weighted MRI analysis (of the apparently normal liver parenchyma) can help differentiate between patients with colorectal liver metastasis and controls without liver disease.
  
  
  METHODS
  Ten patients with colorectal liver metastasis and 10 controls with no focal/diffuse liver disease underwent liver MRI at 1.5 T including diffusion-weighted imaging (DWI; b-values 0, 50, 100, 500, 750, 1000). Apparent diffusion coefficient (ADC) maps were calculated from the DWI images to carry out quantitative diffusion analyses. An experienced reader performed segmentation of the apparently nondiseased liver (excluding metastases/focal liver lesions) on the ADC maps. Histogram ADC parameters were calculated and compared between the patients and the controls.
  
  
  RESULTS
  The mean liver ADC was 0.95×10⁻³ mm²/s for the patients versus 1.03×10⁻³ mm²/s for the controls (P=0.42). The fifth percentile of the ADC was significantly lower for the patients compared with the controls (0.45 vs. 0.69 10⁻³ mm²/s, P=0.01). The SD was significantly higher in the patient group (0.30 vs. 0.22, P<0.001). Median, skewness, kurtosis, and 30th-95th percentile were not significantly different between the two groups. Areas under the receiver operator characteristics curves to differentiate patients with metastatic liver involvement from healthy controls without liver disease were 0.79 for the fifth percentile and 0.95 for the SD.
  
  
  CONCLUSIONS
  Whole-liver diffusion-weighted MRI histogram analysis showed a significant shift towards lower fifth percentile ADC values and higher SD in patients with colorectal liver metastasis compared with controls without liver disease.
authors: Departments of aRadiology bSurgery, Maastricht University Medical Center cGROW School for Oncology and Developmental Biology, Maastricht, The Netherlands dDepartment of Radiology, Alexandra Hospital, Jurong Health, Singapore, Singapore eLaboratory of Computational Medicine, Institute of Computer Science, FORTH, Heraklion, Crete, Greece.
authors: Doenja M J
authors: DM
authors: Lambregts
authors: Milou H
authors: MH
authors: Martens
authors: Raymond C W
authors: RC
authors: Quah
authors: Katerina
authors: K
authors: Nikiforaki
authors: Luc A
authors: LA
authors: Heijnen
authors: Cornelis H C
authors: CH
authors: Dejong
authors: Geerard L
authors: GL
authors: Beets
authors: Kostas
authors: K
authors: Marias
authors: Nickolas
authors: N
authors: Papanikolaou
authors: Regina G H
authors: RG
authors: Beets-Tan
mesh_terms: D000328:Adult; D000368:Aged; D016022:Case-Control Studies; D015179:Colorectal Neoplasms / Q000473:pathology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000473:pathology*; D008113:Liver Neoplasms / Q000175:diagnosis* / Q000556:secondary*; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D012189:Retrospective Studies