Posttreatment high-grade glioma: usefulness of peak height position with semiquantitative MR perfusion histogram analysis in an entire contrast-enhanced lesion for predicting volume fraction of recurrence.
OBJECTIVE
To determine whether semiquantitative histogram analysis of the normalized cerebral blood volume (CBV) for an entire contrast material-enhanced lesion could be used to predict the volume fraction of posttreatment high-grade glioma recurrence compared with posttreatment change.


METHODS
The institutional review board approved this retrospective study. Informed consent was obtained. Thirty-nine patients with pathologically proved predominant tumor recurrence (tumor recurrence group, tumor fraction > or =50% [n = 14]), mixed tumor and posttreatment change (mixed group, tumor fraction > or =20% and <50% [n = 10]), and predominant posttreatment change (treatment change group, tumor fraction <20% [n = 15]) were evaluated. Histogram parameters of normalized CBV-histogram width, peak height position (PHP), and maximum value (MV)-were measured in entire contrast-enhanced lesions and used as discriminative indexes. Ordered logistic regression was used to determine independent factors for predicting the diseases of posttreatment contrast-enhanced lesions. Leave-one-out cross-validation was used to determine diagnostic accuracy.


RESULTS
PHP was an independent predictive factor (P = .003) for differentiating contrast-enhanced lesions in patients with posttreatment gliomas. According to receiver operating characteristic curve analyses, PHP provided sensitivity of 90.2% and specificity of 91.1% for differentiating tumor recurrence from mixed and treatment change groups at an optimum threshold of 1.7 by using leave-one-out cross-validation. MV helped distinguish treatment change group from tumor recurrence and mixed groups at an optimum threshold of 2.6 (sensitivity, 96.5%; specificity, 93.1%).


CONCLUSIONS
PHP can be used to predict the volume fraction of posttreatment high-grade glioma recurrence.
Kim
Ho Sung
HS
Department of Diagnostic Radiology, Ajou University School of Medicine, Yeongtong-gu, Suwon, Gyeonggi-do 442-749, Korea. J978005@lycos.co.kr
Kim
Jang-Hee
JH
Kim
Se-Hyuk
SH
Cho
Kyung-Gi
KG
Kim
Sun Yong
SY
D000293:Adolescent; D000328:Adult; D000368:Aged; D001932:Brain Neoplasms / Q000473:pathology*; D002560:Cerebrovascular Circulation; D003287:Contrast Media; D005260:Female; D005910:Glioma / Q000473:pathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D016015:Logistic Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local / Q000473:pathology; D012372:ROC Curve; D012189:Retrospective Studies; D012680:Sensitivity and Specificity
D003287:Contrast Media