CEREBRAL-TUMOR VOLUME CALCULATIONS USING PLANIMETRIC AND EIGENIMAGE ANALYSIS

Volume determination in cerebral tumors requires accurate and reproduc ible segmentation. This task has been traditionally accomplished using planimetric methods which define the boundary of the lesion using thr esholding and edge detection schemes. These methods lack accuracy and reproducibility when the contrast between the lesion and surrounding t issue is not maximized. Because of this limitation contrast agents are used providing reproducible results for the enhancing portion of the lesion. A novel approach for volume determination has been developed ( eigenimage filter) which segments a desired feature (tissue type) from surrounding undesired features in a sequence of images. This method c orrects for partial volume effects and has been shown to provide accur ate and reproducible volume determinations. In addition, the eigenimag e filter does not require the use of contrast and has the capability t o segment a lesion into multiple regions. This allows different compon ents of the lesion to be included and monitored in treatment. In this study planimetric methods and the eigenimage filter were compared for segmenting cerebral tumors and determining their volumes. The planimet ric methods were reproducible in determining volumes for the enhancing portion of the lesion with interobserver percent differences < 8% and intraobserver percent differences < 4%. The eigenimage filter had int erobserver percent differences < 7% and intraobserver percent differen ces < 3%. In the eigenimage procedure both the enhancing portion of th e lesion as well as additional regions within the lesion were identifi ed. Comparing the results obtained from the two methods demonstrated g ood agreement for presurgical studies (percent differences < 9%). When comparing postsurgical studies large differences were seen. In the po stsurgical studies the eigenimage method allowed multiple regions to b e followed in subsequent MRI and in two patients showed a volume chang e that suggested tumor recurrence more clearly. Since the amount of in formation obtained using the eigenimage filter may allow a more comple te assessment of the lesion, it is suggested that it could improve the clinical evaluation of cerebral tumors. (C) 1996 American Association of Physicists in Medicine.