Radiological response of leptomeningeal metastases according to revised RANO criteria is associated with overall survival in breast cancer patients.

Assessment of treatment response in patients (pts) with leptomeningeal metastases (LM) represents a significant challenge and standardized criteria are needed. In 2017, the RANO LM Working Group proposed a standardized scorecard to evaluate MRI findings (further simplified in 2019). Here, we aim to validate the prognostic impact of response to treatment assessed using this tool in a multicentric cohort of breast cancer (BC) pts. Pts with BC-related LM diagnosed at two institutions between 2005 and 2018 were identified. Baseline and follow-up MRI scans were centrally reviewed and response assessment was evaluated using 2019 revised RANO LM criteria. A total of 142 pts with BC-related LM and available baseline brain MRI imaging were identified; 60 of them had at least one follow-up MRI. In this subgroup, median overall survival (OS) was 15.2 months (95%CI 9.5-21.0). At first re-evaluation, radiological response by RANO criteria was: complete response (CR) in 2 pts (3%), partial response (PR) in 12 (20%), stable disease (SD) in 33 (55%) and progression of disease (PD) in 13 (22%). Median OS was 31.1 months (HR 0.10, 95%CI 0.01-0.78) in pts with CR, 16.1 months (HR 0.41, 95%CI 0.17-0.97) in pts with PR, 17.9 months (HR 0.45, 95%CI 0.22-0.91) in pts with SD and 9.5 months in pts with PD (P = .029). A second blinded evaluation showed a moderate interobserver agreement (K = 0.562). Radiological response according to 2019 RANO criteria is significantly associated with OS in pts with BC-related LM, thus supporting the use of this evaluation tool both in trials and clinical practice.

Prognostic impact of extracranial disease control in HER2+ breast cancer-related brain metastases.

BACKGROUND: Brain metastases (BM) are common among HER2+ breast cancer (BC) and prognostic stratification is crucial for optimal management. BC-GPA score and subsequent refinements (modified-GPA, updated-GPA) recapitulate prognostic factors. Since none of these indexes includes extracranial disease control, we evaluated its prognostic value in HER2+ BCBM. METHODS: Patients diagnosed with HER2+ BCBM at Istituto Oncologico Veneto-Padova (2002-2021) and Montpellier Cancer Institute (2001-2015) were included as exploratory and validation cohorts, respectively. Extracranial disease control at BM diagnosis (no disease/stable disease/response vs. progressive disease) was evaluated. RESULTS: In the exploratory cohort of 113 patients (median OS 12.2 months), extracranial control (n = 65, 57.5%) was significantly associated with better OS at univariate (median OS 17.7 vs. 8.7 months, p = 0.005) and multivariate analysis after adjustment for BC-GPA (HR 0.61, 95% CI 0.39-0.94), modified-GPA (HR 0.64, 95% CI 0.42-0.98) and updated-GPA (HR 0.63, 95% CI 0.41-0.98). The prognostic impact of extracranial disease control (n = 66, 56.4%) was then confirmed in the validation cohort (n = 117) at univariate (median OS 20.2 vs. 9.1 months, p < 0.001) and multivariate analysis adjusting for BC-GPA (HR 0.41, 95% CI 0.27-0.61), modified-GPA (HR 0.44, 95% CI 0.29-0.67) and updated-GPA (HR 0.42, 95% CI 0.28-0.63). CONCLUSIONS: Extracranial disease control provides independent prognostic information in HER2+ BCBM beyond commonly used prognostic scores.

Clinical applications of radiomics and deep learning in breast and lung cancer: A narrative literature review on current evidence and future perspectives.

Radiomics, analysing quantitative features from medical imaging, has rapidly become an emerging field in translational oncology. Radiomics has been investigated in several neoplastic malignancies as it might allow for a non-invasive tumour characterization and for the identification of predictive and prognostic biomarkers. Over the last few years, evidence has been accumulating regarding potential clinical applications of machine learning in many crucial moments of cancer patients' history. However, the incorporation of radiomics in clinical decision-making process is still limited by low data reproducibility and study variability. Moreover, the need for prospective validations and standardizations is emerging. In this narrative review, we summarize current evidence regarding radiomic applications in high-incidence cancers (breast and lung) for screening, diagnosis, staging, treatment choice, response, and clinical outcome evaluation. We also discuss pro and cons of the radiomic approach, suggesting possible solutions to critical issues which might invalidate radiomics studies and propose future perspectives.

Effectiveness of Cone Beam Computed Tomography Imaging During Radiation Therapy for the Detection of Initial Coronavirus Lung Disease 2019.

In this unique historic period afflicted by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic, radiation therapy treatments cannot be delayed or suspended. We report the case of a 73-year-old woman with recently diagnosed extensive-stage small cell lung cancer with metastatic liver and bone lesions. A SARS-CoV-2 test was performed upon hospital admission and was negative. After 5 days she underwent radiation therapy on T6 and T11 with single fractions of 8 Gy each. Before treatment a cone beam computed tomography (CBCT) scan was performed to check the setup of the patient. Some suspected lung areas of ground glass opacities (GGOs) were clearly visible in the CBCT without any counterpart in the previous computed tomography (CT) simulation scan 3 days before. A new high-quality chest CT scan confirmed the previously suspected GGOs. The exam revealed multiple bilateral areas of subpleural GGOs, which are the primary findings on CT scan in the early phases of coronavirus disease 2019 (COVID-19) lung infection, in addition to pleural effusions, a finding that may occur as a complication of COVID-19. The patient then urgently repeated the SARS-CoV-2 test, which was positive and confirmed the infection. In conclusion, daily CBCT can be effective for early detection of COVID-19 lung disease in asymptomatic or mildly symptomatic patients.