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.

IDH-wildtype lower-grade diffuse gliomas: the importance of histological grade and molecular assessment for prognostic stratification.

BACKGROUND: Isocitrate dehydrogenase (IDH) wildtype (wt) grade II gliomas are a rare and heterogeneous entity. Survival and prognostic factors are poorly defined. METHODS: We searched retrospectively all patients diagnosed with diffuse World Health Organization (WHO) grades II and III gliomas at our center (1989-2020). RESULTS: Out of 517 grade II gliomas, 47 were "diffuse astrocytomas, IDHwt." Tumors frequently had fronto-temporo-insular location (28/47, 60%) and infiltrative behavior. We found telomerase reverse transcriptase (TERT) promoter mutations (23/45, 51%), whole chromosome 7 gains (10/37, 27%), whole chromosome 10 losses (10/41, 24%), and EGFR amplifications (4/43, 9%), but no TP53 mutations (0/22, 0%). Median overall survival (OS) was 59 months (vs 19 mo for IDHwt grade III gliomas) (P < 0.0001). Twenty-nine patients (29/43, 67%) met the definition of molecular glioblastoma according to cIMPACT-NOW update 3. Median OS in this subset was 42 months, which was shorter compared with patients with IDHwt grade II gliomas not meeting this definition (median OS: 57 mo), but substantially longer compared with IDHwt grade III gliomas meeting the definition for molecular glioblastoma (median OS: 17 mo, P < 0.0001). Most patients with IDHwt grade II gliomas met cIMPACT criteria because of isolated TERT promoter mutations (16/26, 62%), which were not predictive of poor outcome (median OS: 88 mo). Actionable targets, including 5 gene fusions involving FGFR3, were found in 7 patients (24%). CONCLUSIONS: Our findings highlight the importance of histological grading and molecular profiling for the prognostic stratification of IDHwt gliomas and suggest some caution when assimilating IDHwt grade II gliomas to molecular glioblastomas, especially those with isolated TERT promoter mutation.

A review of the international early recommendations for departments organization and cancer management priorities during the global COVID-19 pandemic: applicability in low- and middle-income countries.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by a new virus that has never been identified in humans before. COVID-19 caused at the time of writing of this article, 2.5 million cases of infections in 193 countries with 165,000 deaths, including two-third in Europe. In this context, Oncology Departments of the affected countries had to adapt quickly their health system care and establish new organizations and priorities. Thus, numerous recommendations and therapeutic options have been reported to optimize therapy delivery to patients with chronic disease and cancer. Obviously, while these cancer care recommendations are immediately applicable in Europe, they may not be applicable in certain emerging and low- and middle-income countries (LMICs). In this review, we aimed to summarize these international guidelines in accordance with cancer types, making a synthesis for daily practice to protect patients, staff and tailor anti-cancer therapy delivery taking into account patients/tumour criteria and tools availability. Thus, we will discuss their applicability in the LMICs with different organizations, limited means and different constraints.