Surgical management and outcome of newly diagnosed glioblastoma without contrast enhancement (low-grade appearance): a report of the RANO resect group

BACKGROUND

Resection of the contrast-enhancing (CE) tumor represents the standard of care in newly diagnosed glioblastoma. However, some tumors ultimately diagnosed as glioblastoma lack contrast enhancement and have a 'low-grade appearance' on imaging (non-CE glioblastoma). We aimed to (a) volumetrically define the value of non-CE tumor resection in the absence of contrast enhancement, and to (b) delineate outcome differences between glioblastoma patients with and without contrast enhancement.

METHODS

The RANO resect group retrospectively compiled a global, eight-center cohort of patients with newly diagnosed glioblastoma per WHO 2021 classification. The associations between postoperative tumor volumes and outcome were analyzed. Propensity score-matched analyses were constructed to compare glioblastomas with and without contrast enhancement.

RESULTS

Among 1323 newly diagnosed IDH-wildtype glioblastomas, we identified 98 patients (7.4%) without contrast enhancement. In such patients, smaller postoperative tumor volumes were associated with more favorable outcome. There was an exponential increase in risk for death with larger residual non-CE tumor. Accordingly, extensive resection was associated with improved survival compared to lesion biopsy. These findings were retained on a multivariable analysis adjusting for demographic and clinical markers. Compared to CE glioblastoma, patients with non-CE glioblastoma had a more favorable clinical profile and superior outcome as confirmed in propensity score analyses by matching the patients with non-CE glioblastoma to patients with CE glioblastoma using a large set of clinical variables.

CONCLUSIONS

The absence of contrast enhancement characterizes a less aggressive clinical phenotype of IDH-wildtype glioblastomas. Maximal resection of non-CE tumors has prognostic implications and translates into favorable outcome.

Prognostic evaluation of re-resection for recurrent glioblastoma using the novel RANO classification for extent of resection: A report of the RANO resect group

BACKGROUND

The value of re-resection in recurrent glioblastoma remains controversial as a randomized trial that specifies intentional incomplete resection cannot be justified ethically. Here, we aimed to (1) explore the prognostic role of extent of re-resection using the previously proposed Response Assessment in Neuro-Oncology (RANO) classification (based upon residual contrast-enhancing (CE) and non-CE tumor), and to (2) define factors consolidating the surgical effects on outcome.

METHODS

The RANO resect group retrospectively compiled an 8-center cohort of patients with first recurrence from previously resected glioblastomas. The associations of re-resection and other clinical factors with outcome were analyzed. Propensity score-matched analyses were constructed to minimize confounding effects when comparing the different RANO classes.

RESULTS

We studied 681 patients with first recurrence of Isocitrate Dehydrogenase (IDH) wild-type glioblastomas, including 310 patients who underwent re-resection. Re-resection was associated with prolonged survival even when stratifying for molecular and clinical confounders on multivariate analysis; ≤1 cm3 residual CE tumor was associated with longer survival than non-surgical management. Accordingly, "maximal resection" (class 2) had superior survival compared to "submaximal resection" (class 3). Administration of (radio-)chemotherapy in the absence of postoperative deficits augmented the survival associations of smaller residual CE tumors. Conversely, "supramaximal resection" of non-CE tumor (class 1) was not associated with prolonged survival but was frequently accompanied by postoperative deficits. The prognostic role of residual CE tumor was confirmed in propensity score analyses.

CONCLUSIONS

The RANO resect classification serves to stratify patients with re-resection of glioblastoma. Complete resection according to RANO resect classes 1 and 2 is prognostic.

Prognostic validation of a new classification system for extent of resection in glioblastoma: a report of the RANO resect group

BACKGROUND

Terminology to describe extent of resection in glioblastoma is inconsistent across clinical trials. A surgical classification system was previously proposed based upon residual contrast-enhancing (CE) tumor. We aimed to (I) explore the prognostic utility of the classification system and (II) define how much removed non-CE tumor translates into a survival benefit.

METHODS

The international RANO resect group retrospectively searched previously compiled databases from seven neuro-oncological centers in the USA and Europe for patients with newly diagnosed glioblastoma per WHO 2021 classification. Clinical and volumetric information from pre- and post-operative MRI were collected.

RESULTS

We collected 1008 patients with newly diagnosed IDHwt glioblastoma. 744 IDHwt glioblastomas were treated with radiochemotherapy per EORTC 26981/22981 (TMZ/RT→TMZ) following surgery. Among these homogenously treated patients, lower absolute residual tumor volumes (in cm 3) were favorably associated with outcome: patients with 'maximal CE resection' (class 2) had superior outcome compared to patients with 'submaximal CE resection' (class 3) or 'biopsy' (class 4). Extensive resection of non-CE tumor (≤5 cm 3 residual non-CE tumor) was associated with better survival among patients with complete CE resection, thus defining class 1 ('supramaximal CE resection'). The prognostic value of the resection classes was retained on multivariate analysis when adjusting for molecular and clinical markers.

CONCLUSIONS

The proposed "RANO categories for extent of resection in glioblastoma" are highly prognostic and may serve for stratification within clinical trials. Removal of non-CE tumor beyond the CE tumor borders may translate into additional survival benefit, providing a rationale to explicitly denominate such 'supramaximal CE resection'.

NIMG-04. PREDICTING THE BRAF MUTATIONAL STATUS IN PATIENTS WITH MELANOMA BRAIN METASTASES USING RADIOMICS - A BICENTRIC STUDY

BACKGROUND

The BRAF V600E mutation is present in approximately 50% of patients with melanoma and is an important prerequisite for a response to targeted therapies such as BRAF inhibitors. In the majority of patients, the BRAF mutational status is based on the analysis of tissue samples from the extracranial primary tumor only. Since the extracranial and intracranial BRAF mutational status may be discrepant, the additional information on the BRAF mutational status of melanoma brain metastases would be of clinical value, e.g., for the prediction of response to targeted therapies. Here, we evaluated the potential of MRI radiomics for the determination of the intracranial BRAF mutational status in patients with melanoma brain metastases.

PATIENTS AND METHODS

Fifty-nine patients with melanoma brain metastases from two university hospitals (group 1, 45 patients; group 2, 14 patients) were operated with subsequent genetic analysis of the intracranial BRAF mutational status. All patients underwent structural MRI preoperatively. Areas of contrast enhancement were manually segmented and analyzed. Group 1 was used for model training and validation, group 2 for model testing. After image preprocessing and radiomics feature extraction, a test-retest analysis was performed to identify robust features prior to feature selection. Finally, the best performing radiomics model was applied to the test data. Diagnostic performances were evaluated using receiver operating characteristic (ROC) analyses.

RESULTS

Twenty-two patients (49%) in group 1, and 6 patients (43%) in group 2 had an intrametastatic BRAF V600E mutation. Using the best performing six parameter radiomics signature, a linear support vector machine classifier yielded an area under the ROC curve (AUC) of 0.92 (sensitivity, 83%; specificity, 88%) in the test data.

CONCLUSION

The developed radiomics classifier allows a non-invasive prediction of the intracranial BRAF V600E mutational status in patients with melanoma brain metastases and may be of value for treatment decisions.

P14.06 Radiomics for the non-invasive determination of the BRAF mutational status in patients with melanoma brain metastases

BACKGROUND

The BRAF V600E mutation is present in approximately 50% of patients with melanoma and is an important prerequisite for a response to targeted therapies such as BRAF inhibitors. In the majority of patients, the BRAF mutational status is based on the analysis of tissue samples from the extracranial primary tumor only. Since the extracranial and intracranial BRAF mutational status may be discrepant, the additional information on the BRAF mutational status of melanoma brain metastases would be of clinical value, e.g., for the prediction of response to targeted therapies. Here, we evaluated the potential of structural MRI radiomics for the determination of the intracranial BRAF mutational status in patients with melanoma brain metastases.

MATERIAL AND METHODS

Fifty-nine patients with melanoma brain metastases from two university hospitals (group 1, 45 patients; group 2, 14 patients) underwent surgery with subsequent genetic analysis of the brain metastases tissue to determine the BRAF mutational status. All patients underwent structural MRI preoperatively. Areas of contrast enhancement were manually segmented and analyzed. Group 1 was used for model training and validation, group 2 for model testing. After image preprocessing, 1,316 radiomics features were extracted using the open-source PyRadiomics package. A test-retest analysis was performed to identify robust features prior to feature selection. Finally, the best performing radiomics model was applied to the test data (group 2). Diagnostic performances were evaluated using receiver operating characteristic (ROC) analyses.

RESULTS

Twenty-two patients (49%) in group 1, and 6 patients (43%) in group 2 had an intrametastatic BRAF V600E mutation. Using a six parameter radiomics signature, a linear support vector machine classifier yielded an average area under the ROC curve (AUC) of 0.87 (accuracy, 85%; sensitivity, 78%; specificity, 91%) for prediction of the BRAF mutational status in the training data (group 1). Finally, the classifier achieved an AUC of 0.85 (accuracy, 86%; sensitivity, 83%; specificity, 88%) in the test data (group 2).

CONCLUSION

The developed radiomics classifier allows a non-invasive prediction of the intracranial BRAF V600E mutational status in patients with melanoma brain metastases and may be of value for treatment decisions.