RESUMO
Ovarian cancer is associated with high cancer-related mortality rate attributed to late-stage diagnosis, limited treatment options, and frequent disease recurrence. As a result, careful patient selection is important especially in setting of radical surgery. Radiomics is an emerging field in medical imaging, which may help provide vital prognostic evaluation and help patient selection for radical treatment strategies. This systematic review aims to assess the role of radiomics as a predictor of disease recurrence in ovarian cancer. A systematic search was conducted in Medline, EMBASE, and Web of Science databases. Studies meeting inclusion criteria investigating the use of radiomics to predict post-operative recurrence in ovarian cancer were included in our qualitative analysis. Study quality was assessed using the QUADAS-2 and Radiomics Quality Score tools. Six retrospective studies met the inclusion criteria, involving a total of 952 participants. Radiomic-based signatures demonstrated consistent performance in predicting disease recurrence, as evidenced by satisfactory area under the receiver operating characteristic curve values (AUC range 0.77-0.89). Radiomic-based signatures appear to good prognosticators of disease recurrence in ovarian cancer as estimated by AUC. The reviewed studies consistently reported the potential of radiomic features to enhance risk stratification and personalise treatment decisions in this complex cohort of patients. Further research is warranted to address limitations related to feature reliability, workflow heterogeneity, and the need for prospective validation studies.
RESUMO
Radiogenomics, a sub-domain of radiomics, refers to the prediction of underlying tumour biology using non-invasive imaging markers. This novel technology intends to reduce the high costs, workload and invasiveness associated with traditional genetic testing via the development of 'imaging biomarkers' that have the potential to serve as an alternative 'liquid-biopsy' in the determination of tumour biological characteristics. Radiogenomics also harnesses the potential to unlock aspects of tumour biology which are not possible to assess by conventional biopsy-based methods, such as full tumour burden, intra-/inter-lesion heterogeneity and the possibility of providing the information of tumour biology longitudinally. Several studies have shown the feasibility of developing a radiogenomic-based signature to predict treatment outcomes and tumour characteristics; however, many lack prospective, external validation. We performed a systematic review of the current literature surrounding the use of radiogenomics in rectal cancer to predict underlying tumour biology.
RESUMO
Purpose: There is a lack of data on the natural history of asymptomatic intrarenal calculi. In this study, we investigate stone-related events (SREs) in patients with untreated intrarenal calculi. We also investigate predictive factors for SREs. Methods: All patients found with an asymptomatic intrarenal calculus on CT kidney, ureter, bladder managed conservatively with interval imaging for ≥6 months were included. Patients were evaluated for any SRE. The rate of event according to calculus size, location, and number of calculi was also analyzed. Multivariate logistic regression analysis was performed to determine significant predictors for SREs. Results: In total, 266 renal units from 177 patients met inclusion criteria. The mean stone size was 4.44 mm (range 1-25 mm). Duration of follow-up was 43.78 ± 26.86 months (range 6-106 months). The overall rate of SREs, including intervention (n = 80) and spontaneous stone passage after ureteral colic (n = 40), was 45.1% (n = 120/266). Stones >5 mm were more likely to lead to an event compared with stones ≤5 mm (odds ratio [OR]: 2.94; p = 0.01). Interpolar stones and stones located in multiple calices were more likely to cause a SRE than lower pole stones (OR: 2.05; p = 0.05 and OR: 2.29; p = 0.03, respectively). Conclusion: In this large series of patients with asymptomatic intrarenal calculi, the incidence of a spontaneous SRE was 45.1% after 41 months. Stone size and stone location were significant predictors for a SRE. Information from this study will enable urologists to accurately risk stratify patients with asymptomatic renal stones.
