Use of CT perfusion to discriminate between brain metastases from different primaries

The Role of 3D-pCASL MRI in the Differential Diagnosis of Glioblastoma and Brain Metastases

Purpose

The first aim of this study was to compare the intratumoral and peritumoral blood flow parameters in glioblastomas and brain metastases measured by pseudocontinuous arterial spin labeling MRI (3D pCASL). The second aim of this study was to determine whether pCASL could aid in identifying the source of brain metastases.

Materials and Methods

This study included 173 patients aged 12 to 83 years (median age—61 years), who were observed at the National Medical Research Center for Neurosurgery. All patients underwent preoperative MRI with pCASL perfusion. Thereafter patients were operated on and received histological diagnosis. No patients received preoperative chemo or radiotherapy.

Results

The values of maximum and normalized intratumoral blood flow were significantly higher in the group with gliblastoma than in the group with brain metastases: 168.98 + −91.96 versus 152.1 + −173.32 and 7.6 + −8.4 versus 9.3 + −5.33 respectively (p <0.01). However, ROC analysis showed low AUC specificity and sensitivity (0.64, 70%, 60% for mTBF and 0.66, 77%, 62% for nTBF). Peritumoral blood flow parameters were also higher in the glioblastoma group (29.61 + −22.89 versus 16.58 + −6.46 for mTBF and 1.63 + −1.14 versus 0.88 + −0.38 for nTBF, respectively; p <0.01). ROC analysis showed the following measurements of AUC, specificity, and sensitivity (0.75, 68%, 73% for mTBF and 0.77, 58%, 91% for nTBF). Regarding pCASL and various histological subsets of brain metastases, the study found statistically significant differences between the lung and melanoma metastases and the lung and kidney metastases. ROC analysis gave the following values for lung and melanoma metastases: AUC—0.76, specificity—75%, and sensitivity—73% for mTBF; 0.83, 67%, and 93% respectively, for nTBF. For lung and kidney metastases: AUC—0.74, specificity—70%, and sensitivity—93% for mTBF; 0.75, 70%, and 93% respectively, for nTBF.

Conclusions

pCASL could aid in differential diagnosis between glioblastoma and brain metastases. Measurement of peritumoral blood flow demonstrates higher specificity and sensitivity than with intratumoral blood flow. Moreover, pCASL provides the ability to distinguish lung metastases from kidney and melanoma metastases.

Differentiation between glioblastomas and brain metastases and regarding their primary site of malignancy using dynamic susceptibility contrast MRI at 3T

BACKGROUND

Differentiation between glioblastoma and brain metastasis may be challenging in conventional contrast-enhanced MRI.

PURPOSE

To investigate if perfusion-weighted MRI is able to differentiate glioblastoma from metastasis and, as a second aim was to see if it was possible in the latter group, to predict the primary site of neoplasm.

MATERIAL AND METHODS

Hundred and fourteen patients with newly discovered tumor lesion (76 metastases and 38 glioblastomas) underwent conventional contrast-enhanced MRI including dynamic susceptibility contrast perfusion sequence. The calculated relative cerebral blood volumes were analyzed in the solid tumor area, peritumoral area, area adjacent to peritumoral area, and normal appearing white matter in contralateral semioval center. The Student t-test was used to detect statistically significant differences in relative cerebral blood volume between glioblastomas and metastases in the aforementioned areas. Furthermore, the metastasis group was divided in four sub groups (lung-, breast-, melanoma-, and gastrointestinal origin) and using one-way ANOVA test. P-values < 0.05 were considered significant.

RESULTS

Relative cerebral blood volume (rCBV) in the peritumoral edema was significantly higher in glioblastomas than in metastases (mean 3.2 ± 1.4 and mean 0.9 ± 0.7), respectively, (P < 0.0001). No significant differences in the solid tumor area or the area adjacent to edema were found, (P = 0.28 and 0.21 respectively). There were no significant differences among metastases in the four groups.

CONCLUSION

It is possible to differentiate glioblastomas from metastases by measuring the CBV in the peritumoral edema. It is not possible to differentiate between brain metastases from different primaries (lung-, breast-, melanoma or gastrointestinal) using CBV-measurements in the solid tumor area, peritumoral edema or area adjacent to edema.

Dynamic contrast-enhanced MRI perfusion for differentiating between melanoma and lung cancer brain metastases

Brain metastases originating from different primary sites overlap in appearance and are difficult to differentiate with conventional MRI. Dynamic contrast-enhanced (DCE)-MRI can assess tumor microvasculature and has demonstrated utility in characterizing primary brain tumors. Our aim was to evaluate the performance of plasma volume (Vp) and volume transfer coefficient (Ktrans ) derived from DCE-MRI in distinguishing between melanoma and nonsmall cell lung cancer (NSCLC) brain metastases. Forty-seven NSCLC and 23 melanoma brain metastases were retrospectively assessed with DCE-MRI. Regions of interest were manually drawn around the metastases to calculate Vpmean and Kmeantrans. The Mann-Whitney U test and receiver operating characteristic analysis (ROC) were performed to compare perfusion parameters between the two groups. The Vpmean of melanoma brain metastases (4.35, standard deviation [SD] = 1.31) was significantly higher (P = 0.03) than Vpmean of NSCLC brain metastases (2.27, SD = 0.96). The Kmeantrans values were higher in melanoma brain metastases, but the difference between the two groups was not significant (P = 0.12). Based on ROC analysis, a cut-off value of 3.02 for Vpmean (area under curve = 0.659 with SD = 0.074) distinguished between melanoma brain metastases and NSCLC brain metastases (P < 0.01) with 72% specificity. Our data show the DCE-MRI parameter Vpmean can differentiate between melanoma and NSCLC brain metastases. The ability to noninvasively predict tumor histology of brain metastases in patients with multiple malignancies can have important clinical implications.