Current radiographic response criteria for brain tumors have difficulty describing changes surrounding postoperative resection cavities. Volumetric techniques may offer improved assessment, however usually are time-consuming, subjective and require expert opinion and specialized magnetic resonance imaging (MRI) sequences. We describe the application of a novel volumetric software algorithm that is nearly fully automated and uses standard T1 pre- and post-contrast MRI sequences. T1-weighted pre- and post-contrast images are automatically fused and normalized. The tumor region of interest is grossly outlined by the user. An atlas of the nasal mucosa is automatically detected and used to normalize levels of enhancement. The volume of enhancing tumor is then automatically calculated. We tested the ability of our method to calculate enhancing tumor volume with resection cavity collapse and when the enhancing tumor is obscured by subacute blood in a resection cavity. To determine variability in results, we compared narrowly-defined tumor regions with tumor regions that include adjacent meningeal enhancement and also compared different contrast enhancement threshold levels used for the automatic calculation of enhancing tumor volume. Our method quantified enhancing tumor volume despite resection cavity collapse. It detected tumor volume increase in the midst of blood products that incorrectly caused decreased measurements by other techniques. Similar trends in volume changes across scans were seen with inclusion or exclusion of meningeal enhancement and despite different automated thresholds for tissue enhancement. Our approach appears to overcome many of the challenges with response assessment of enhancing brain tumors and warrants further examination and validation.

Purpose A major obstacle in glioblastoma (GBM) therapy is the restrictive nature of the blood-brain barrier (BBB). Convection-enhanced delivery (CED) is a novel method of drug administration which allows direct parenchymal infusion of therapeutics, bypassing the BBB. MR1-1 is a novel recombinant immunotoxin that targets the GBM tumor-specific antigen EGFRvIII and can be delivered via CED infusion. However, drug distribution via CED varies dramatically, which necessitates active monitoring. Gadolinium conjugated to diethylenetriamine penta-acetic acid (Gd-DTPA) is a commonly used MRI contrast agent which can be co-infused with therapies using CED and may be useful in monitoring infusion leak and early distribution. Experimental design Forty immunocompetent rats were implanted with intracerebral cannulas that were connected to osmotic pumps and subsequently randomized into four groups that each received 0.2% human serum albumin (HSA) mixed with a different experimental infusion: 1) 25 ng/mL MR1-1; 2) 7 μmol/mL Gd-DTPA; 3) 25 ng/mL MR1-1 and 7 μmol/mL Gd-DTPA; 4) 250 ng/mL MR1-1 and 7μmol/mL Gd-DTPA. The rats were monitored clinically for six weeks then necropsied and histologically assessed for CNS toxicity. Results All rats survived the entirety of the study without clinical or histological toxicity attributable to the study drugs. There was no statistically significant difference in weight change over time among groups (p>0.999). Conclusion MR1-1 co-infused with Gd-DTPA via CED is safe in the long-term setting in a pre-clinical animal model. Our data supports the use of Gd-DTPA, as a surrogate tracer, co-infused with MR1-1 for drug distribution monitoring in patients with GBM.

Objective Robust methodology that allows objective, automated, and observer-independent measurements of brain tumor volume, especially postresection, is lacking; hence, determination of tumor response and progression in neuro-oncology is unreliable. Our objective was to determine if a semi-automated, volumetric method for quantifying enhancing tissue would perform with high reproducibility and low interobserver variability. Methods Fifty-seven scans from 13 patients with glioblastoma (GBM) were assessed, using our method, by two neuroradiologists, one neurosurgeon, one neurosurgery resident, one nurse practitioner, and one medical student. The two neuroradiologists also performed traditional one-dimensional and two-dimensional measurements. Intraclass correlation coefficients (ICC) assessed interobserver variability between measurements. Radiographic response was determined using Response Evaluation Criteria In Solid Tumors (RECIST) guidelines and Macdonald criteria. Kappa statistics described interobserver variability of volumetric radiographic response determinations. Results There was strong agreement for one-dimensional (RECIST) and two-dimensional (Macdonald) measurements between neuroradiologists (ICC=0.42 and 0.61, respectively), but the agreement using our novel automated approach was significantly stronger (ICC=0.97). Our volumetric method had the strongest agreement with regard to radiographic response (kappa=0.96) when compared with two-dimensional (0.54) or one-dimensional (0.46) methods. Despite diverse levels of experience, measurements using our volumetric program by all users remained remarkably high (0.94). Conclusion Interobserver variability with our semiautomated method is less than the variability with traditional methods of tumor measurement. It is objective, quick, and highly reproducible among operators with varying expertise. This approach should be further evaluated as a potential standard for response assessment based on contrast enhancement in brain tumors.

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