Evaluation of apparent diffusion coefficient thresholds for diagnosis of medulloblastoma using diffusion-weighted imaging

Abstract

We assess a diffusion-weighted imaging (DWI) analysis technique as a potential basis for computer-aided diagnosis (CAD) of pediatric posterior fossa tumors. A retrospective medical record search identified 103 children (mean age: 87 months) with posterior fossa tumors having a total of 126 preoperative MR scans with DWI. The minimum ADC (ADCmin) and normalized ADC (nADC) values [ratio of ADCmin values in tumor compared to normal tissue] were measured by a single observer blinded to diagnosis. Receiver operating characteristic (ROC) curves were generated to determine the optimal threshold for which the nADC and ADCmin values would predict tumor histology. Inter-rater reliability for predicting tumor type was evaluated using values measured by two additional observers. At histology, ten tumor types were identified, with astrocytoma (n=50), medulloblastoma (n=33), and ependymoma (n=9) accounting for 89%. Mean ADCmin (0.54 × 10(-3) mm(2)/s) and nADC (0.70) were lowest for medulloblastoma. Mean ADCmin (1.28 × 10(-3) mm(2)/s) and nADC (1.64) were highest for astrocytoma. For the ROC analysis, the area under the curve when discriminating medulloblastoma from other tumors using nADC was 0.939 and 0.965 when using ADCmin. The optimal ADCmin threshold was 0.66 × 10(-3) mm(2)/s, which yielded an 86% positive predictive value, 97% negative predictive value, and 93% accuracy. Inter-observer variability was very low, with near perfect agreement among all observers in predicting medulloblastoma. Our data indicate that both ADCmin and nADC could serve as the basis for a CAD program to distinguish medulloblastoma from other posterior fossa tumors with a high degree of accuracy.

Keywords: apparent diffusion coefficient; computer-assisted diagnosis; medulloblastoma; posterior fossa tumor.

Figure 1

MR Findings and ADC map in a 12-year-old girl with a medulloblastoma. A) Axial unenhanced T1-weighted image shows mass lesion in fourth ventricle. B) Axial fluid-attenuated (FLAIR) image shows a mildly hyperintense lesion compared to adjacent brain. C) Axial T2-weighted image shows the mass is inhomogeneous and hyperintense to adjacent brain. D) Axial contrast-enhanced T1-weighted axial image shows inhomogeneous contrast enhancement of the tumor. E) Axial apparent diffusion coefficient map shows the central portion of the tumor has low signal intensity. ADC_min was 0.531 × 10⁻³ mm²/s and nADC value was 0.733. The threshold values used in our study (ADC_min of 0.66 × 10⁻³ mm²/s and nADC of 0.905 for distinguishing medulloblastoma from astrocytoma, ependymoma, and other tumors) allowed discrimination of this medulloblastoma from other tumors.

Figure 2

Findings and ADC map in a 2-year-old boy with a fourth ventricle ependymoma. A) Axial unenhanced T1-weighted image shows mass lesion in fourth ventricle. B) Axial fluid-attenuated (FLAIR) image shows a mildly hyperintense lesion compared to adjacent brain. C) Axial T2-weighted image shows the mass is inhomogeneous and hyperintense to adjacent brain. D) Axial contrast-enhanced T1-weighted axial image shows mild contrast enhancement of the tumor. E) Axial apparent diffusion coefficient map shows the central portion of the tumor has low signal intensity. ADC_min was 0.90 × 10⁻³ mm²/s and nADC value was 1.08. The threshold values used in our study (ADCmin of 0.675 × 10⁻³ mm²/s and nADC of 1.0 for distinguishing medulloblastoma from ependymoma) allowed discrimination of this ependymoma from medulloblastoma.

Figure 3

MR Findings and ADC map in a 14-year-old boy with a cerebellar astrocytoma. A) Axial unenhanced T1-weighted image shows a large, inhomogeneous posterior fossa mass. B) Axial fluid-attenuated (FLAIR) image shows the mass to have cystic components and to cause obstructive hydrocephalus. C) Axial T2-weighted image shows a complex arrangement of cystic and solid portions of the mass. D) Axial contrast-enhanced T1-weighted axial image shows dense, inhomogeneous contrast enhancement of the mass. E) Axial apparent diffusion coefficient map shows the tumor has mildly increased signal intensity compared to adjacent normal brain. ADCmin was 1.64 × 10⁻³ mm²/s and nADC value was 2.03. The threshold values used in our study would correctly predict that this is not a medulloblastoma.

Figure 4

Receiver operating characteristics (ROC) curve for correct identification of medulloblastoma. The ROC curve for medulloblastoma identified from ependymoma using minimum tumor ADC (ADC_min) shown in blue and ADC ratio (nADC) shown in red. ROC curve for medulloblastoma identified from all tumors using ADC_min is shown in black and nADC is shown in green. Medulloblastoma is correctly identified more often when using ADC_min versus nADC.

Figure 5

Similarity of ADCmin measurements obtained on serial MR examinations. Minimum tumor ADC (ADCmin) values are plotted for each patient with multiple DWI examinations. Only one patient had variation in ADCmin that would have crossed the threshold shown as a horizontal line. Thus only one case would be categorized differently using ADC_min based upon the time of imaging. No general trend of ADC_min variation was seen over time.