Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study.

BACKGROUND: Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after repeated GBCA administration with yet unknown clinical significance. We aimed to assess the feasibility and diagnostic value of synthetic post-contrast T1-weighted MRI generated from pre-contrast MRI sequences through deep convolutional neural networks (dCNN) for tumour response assessment in neuro-oncology. METHODS: In this multicentre, retrospective cohort study, we used MRI examinations to train and validate a dCNN for synthesising post-contrast T1-weighted sequences from pre-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery sequences. We used MRI scans with availability of these sequences from 775 patients with glioblastoma treated at Heidelberg University Hospital, Heidelberg, Germany (775 MRI examinations); 260 patients who participated in the phase 2 CORE trial (1083 MRI examinations, 59 institutions); and 505 patients who participated in the phase 3 CENTRIC trial (3147 MRI examinations, 149 institutions). Separate training runs to rank the importance of individual sequences and (for a subset) diffusion-weighted imaging were conducted. Independent testing was performed on MRI data from the phase 2 and phase 3 EORTC-26101 trial (521 patients, 1924 MRI examinations, 32 institutions). The similarity between synthetic and true contrast enhancement on post-contrast T1-weighted MRI was quantified using the structural similarity index measure (SSIM). Automated tumour segmentation and volumetric tumour response assessment based on synthetic versus true post-contrast T1-weighted sequences was performed in the EORTC-26101 trial and agreement was assessed with Kaplan-Meier plots. FINDINGS: The median SSIM score for predicting contrast enhancement on synthetic post-contrast T1-weighted sequences in the EORTC-26101 test set was 0·818 (95% CI 0·817-0·820). Segmentation of the contrast-enhancing tumour from synthetic post-contrast T1-weighted sequences yielded a median tumour volume of 6·31 cm3 (5·60 to 7·14), thereby underestimating the true tumour volume by a median of -0·48 cm3 (-0·37 to -0·76) with the concordance correlation coefficient suggesting a strong linear association between tumour volumes derived from synthetic versus true post-contrast T1-weighted sequences (0·782, 0·751-0·807, p<0·0001). Volumetric tumour response assessment in the EORTC-26101 trial showed a median time to progression of 4·2 months (95% CI 4·1-5·2) with synthetic post-contrast T1-weighted and 4·3 months (4·1-5·5) with true post-contrast T1-weighted sequences (p=0·33). The strength of the association between the time to progression as a surrogate endpoint for predicting the patients' overall survival in the EORTC-26101 cohort was similar when derived from synthetic post-contrast T1-weighted sequences (hazard ratio of 1·749, 95% CI 1·282-2·387, p=0·0004) and model C-index (0·667, 0·622-0·708) versus true post-contrast T1-weighted MRI (1·799, 95% CI 1·314-2·464, p=0·0003) and model C-index (0·673, 95% CI 0·626-0·711). INTERPRETATION: Generating synthetic post-contrast T1-weighted MRI from pre-contrast MRI using dCNN is feasible and quantification of the contrast-enhancing tumour burden from synthetic post-contrast T1-weighted MRI allows assessment of the patient's response to treatment with no significant difference by comparison with true post-contrast T1-weighted sequences with administration of GBCAs. This finding could guide the application of dCNN in radiology to potentially reduce the necessity of GBCA administration. FUNDING: Deutsche Forschungsgemeinschaft.

Proposed response assessment and endpoints for meningioma clinical trials: report from the Response Assessment in Neuro-Oncology Working Group.

No standard criteria exist for assessing response and progression in clinical trials involving patients with meningioma, and there is no consensus on the optimal endpoints for trials currently under way. As a result, there is substantial variation in the design and response criteria of meningioma trials, making comparison between trials difficult. In addition, future trials should be designed with accepted standardized endpoints. The Response Assessment in Neuro-Oncology Meningioma Working Group is an international effort to develop standardized radiologic criteria for treatment response for meningioma clinical trials. In this proposal, we present the recommendations for response criteria and endpoints for clinical trials involving patients with meningiomas.

Intraoperative computed tomography with integrated navigation system in a multidisciplinary operating suite.

OBJECTIVE: We report our preliminary experience in a prospective series of patients with regard to feasibility, work flow, and image quality using a multislice computed tomographic (CT) scanner combined with a frameless neuronavigation system (NNS). METHODS: A sliding gantry 40-slice CT scanner was installed in a preexisting operating room. The scanner was connected to a frameless infrared-based NNS. Image data was transferred directly from the scanner into the navigation system. This allowed updating of the NNS during surgery by automated image registration based on the position of the gantry. Intraoperative CT angiography was possible. The patient was positioned on a radiolucent operating table that fits within the bore of the gantry. During image acquisition, the gantry moved over the patient. This table allowed all positions and movements like any normal operating table without compromising the positioning of the patient. For cranial surgery, a carbon-made radiolucent head clamp was fixed to the table. RESULTS: Experience with the first 230 patients confirms the feasibility of intraoperative CT scanning (136 patients with intracranial pathology, 94 patients with spinal lesions). After a specific work flow, interruption of surgery for intraoperative scanning can be limited to 10 to 15 minutes in cranial surgery and to 9 minutes in spinal surgery. Intraoperative imaging changed the course of surgery in 16 of the 230 cases either because control CT scans showed suboptimal screw position (17 of 307 screws, with 9 in 7 patients requiring correction) or that tumor resection was insufficient (9 cases). Intraoperative CT angiography has been performed in 7 cases so far with good image quality to determine residual flow in an aneurysm. Image quality was excellent in spinal and cranial base surgery. CONCLUSION: The system can be installed in a preexisting operating environment without the need for special surgical instruments. It increases the safety of the patient and the surgeon without necessitating a change in the existing surgical protocol and work flow. Imaging and updating of the NNS can be performed at any time during surgery with very limited time and modification of the surgical setup. Multidisciplinary use increases utilization of the system and thus improves the cost-efficiency relationship.