Conventional MRI does not reliably distinguish radiation necrosis from tumor recurrence after stereotactic radiosurgery.

Publication/Presentation Date

8-1-2012

Abstract

Distinguishing radiation necrosis (RN) from tumor recurrence after stereotactic radiosurgery (SRS) for brain metastases is challenging. This study assesses the sensitivity (SN) and specificity (SP) of an MRI-based parameter, the "lesion quotient" (LQ), in characterizing tumor progression from RN. Records of patients treated with SRS for brain metastases between 01/01/1999 and 12/31/2009 and with histopathologic analysis of a subsequent contrast enhancing enlarging lesion at the treated site at a single institution were examined. The LQ, the ratio of maximal nodular cross sectional area on T2-weighted imaging to the corresponding maximal cross sectional area of T1-contrast enhancement, was calculated by a neuroradiologist blinded to the histopathological outcome. Cutoffs of0.6 have been previously suggested to have correlated with RN, mixed findings and tumor recurrence, respectively. These cutoff values were evaluated for SN, SP, positive predictive value (PPV) and negative predictive value (NPV). Logistic regression analysis evaluated for associated clinical factors. For the 51 patients evaluated, the SN, SP, PPV and NPV for identifying RN (LQ < 0.3) were 8, 91, 25 and 73 %, respectively. For the combination of recurrent tumor and RN (LQ 0.3-0.6) the SN, SP, PPV and NPV were 0, 64, 0 and 83 %. The SN, SP, PPV and NPV of the LQ for recurrent tumor (LQ > 0.6) were 59, 41, 62 and 39 %, respectively. Standard MRI techniques do not reliably discriminate between tumor progression and RN after treatment with SRS for brain metastases. Additional imaging modalities are warranted to aid in distinguishing between these diagnoses.

Volume

109

Issue

1

First Page

149

Last Page

158

ISSN

1573-7373

Disciplines

Diagnosis | Medicine and Health Sciences | Other Analytical, Diagnostic and Therapeutic Techniques and Equipment | Radiology

PubMedID

22638727

Department(s)

Department of Radiology and Diagnostic Medical Imaging

Document Type

Article

Share

COinS