Glioma radiogenomics and artificial intelligence: road to precision cancer medicine.

Radiogenomics refers to the study of the relationship between imaging phenotypes and gene expression patterns/molecular characteristics, which might allow improved diagnosis, decision-making, and predicting patient outcomes in the context of multiple diseases. Central nervous system (CNS) tumours contribute to significant cancer-related mortality in the present age. Although historically CNS neoplasms were classified and graded based on microscopic appearance, there was discordance between two histologically similar tumours that showed varying prognosis and behaviour, attributable to their molecular signatures. These led to the incorporation of molecular markers in the classification of CNS neoplasms. Meanwhile, advancements in imaging technology such as diffusion-based imaging (including tractography), perfusion, and spectroscopy in addition to the conventional imaging of glial neoplasms, have opened an avenue for radiogenomics. This review touches upon the schema of the current classification of gliomas, concepts behind molecular markers, and parameters that are used in radiogenomics to characterise gliomas and the role of artificial intelligence for the same. Further, the role of radiomics in the grading of brain tumours, prediction of treatment response and prognosis has been discussed. Use of automated and semi-automated tumour segmentation for radiotherapy planning and follow-up has also been discussed briefly.

Sinonasal papilloma: what influences the decision to request a magnetic resonance imaging scan?

BACKGROUND: Computed tomography is the standard pre-operative imaging modality for sinonasal papilloma. The complementary use of magnetic resonance imaging as an additional investigation is debated. This study aimed to establish whether magnetic resonance imaging can accurately detect tumour extent and is a useful adjunct to computed tomography. METHODS: A retrospective review was conducted on 19 patients with sinonasal papilloma. The interpretation of computed tomography and magnetic resonance imaging scans, by three clinicians, was conducted by comparing prediction of tumour extent. The perceived necessity of magnetic resonance imaging was compared between clinicians. RESULTS: The addition of magnetic resonance imaging improved accuracy of pre-operative interpretation; specifically, this finding was significant in cases with frontal sinus involvement. Surgeons were more likely than a radiologist to request magnetic resonance imaging, particularly when computed tomography indicated frontal sinus disease. CONCLUSION: Pre-operative combined magnetic resonance imaging and computed tomography helped predict disease in the frontal sinus better than computed tomography alone. A close working relationship between the ENT and radiology departments is important for accurate tumour localisation.

Magnetic resonance imaging in rectal cancer downstaged using neoadjuvant chemoradiation: accuracy of prediction of tumour stage and circumferential resection margin status.

OBJECTIVE: The aim was to examine the accuracy of magnetic resonance imaging (MRI) in predicting circumferential resection margin (CRM) involvement, T- and N-stage in patients with locally advanced carcinoma of the rectum, who had undergone long-course downstaging chemoradiation (CRT). METHOD: Patients with rectal cancer were selected for long-course downstaging CRT if their tumour was considered to threaten (< or = 1 mm) or involve the CRM on MRI. Eighty such patients had a repeat MRI at a median of 6 weeks post-CRT followed by surgical excision soon thereafter. The findings on the post-CRT MRI were compared with histological examination of the surgical specimen. RESULTS: For CRM involvement, post-CRT restaging MRI had an accuracy of 81% (65/80) a sensitivity of 54% (7/13), a specificity of 87% (58/67), a positive predictive value of 44% (7/16) and a negative predictive value of 91% (58/64). Accuracy for T- and N-staging was 43% (34/80) and 78% (62/80), respectively. 38% of T-stages were overstaged and 20% understaged. 4% of N-stages were overstaged and 19% understaged. The 13 patients with histological positive CRM had worse clinical outcomes than the 67 patients with negative CRM in terms of disease-free survival (relative risk of reduced DFS 4.6, P = 0.001) and overall survival (relative risk of death 3.6, P = 0.016). CONCLUSION: Magnetic resonance imaging has good specificity and negative predictive value for predicting an uninvolved CRM post downstaging CRT in locally advanced rectal cancer although sensitivity and positive predictive value for an involved CRM were unsatisfactory. The shortcomings of MRI stem from poor differentiation of viable tumour from posttreatment changes and inability to identify small nodal and tumour deposits. Clinical correlates in this group of patients have confirmed the importance of achieving a clear CRM at surgery.