KIT 1 (Keep in Touch) Project-Televisits for Cancer Patients during Italian Lockdown for COVID-19 Pandemic: The Real-World Experience of Establishing a Telemedicine System

To evaluate the adoption of an integrated eHealth platform for televisit/monitoring/consultation during the COVID-19 pandemic. Methods: During the lockdown imposed by the Italian government during the COVID19 pandemic spread, a dedicated multi-professional working group was set up in the Radiation Oncology Department with the primary aim of reducing patients' exposure to COVID-19 by adopting de-centralized/remote consultation methodologies. Each patient's clinical history was screened before the visit to assess if a traditional clinical visit would be recommended or if a remote evaluation was to be preferred. Real world data (RWD) in the form of patient-reported outcomes (PROMs) and patient reported experiences (PREMs) were collected from patients who underwent televisit/teleconsultation through the eHealth platform. Results: During the lockdown period (from 8 March to 4 May 2020) a total of 1956 visits were managed. A total of 983 (50.26%) of these visits were performed via email (to apply for and to upload of documents) and phone call management; 31 visits (1.58%) were performed using the eHealth system. Substantially, all patients found the eHealth platform useful and user-friendly, consistently indicating that this type of service would also be useful after the pandemic. Conclusions: The rapid implementation of an eHealth system was feasible and well-accepted by the patients during the pandemic. However, we believe that further evidence is to be generated to further support large-scale adoption

Fractal-Based Radiomic Approach to Tailor the Chemotherapy Treatment in Rectal Cancer: A Generating Hypothesis Study

IntroductionThe aim of this study was to create a radiomic model able to calculate the probability of 5-year disease-free survival (5yDFS) when oxaliplatin (OXA) is or not administered in patients with locally advanced rectal cancer (LARC) and treated with neoadjuvant chemoradiotherapy (nCRT), allowing physicians to choose the best chemotherapy (CT) regimen. MethodsLARC patients with cT3-4 cN0 or cT1-4 cN1-2 were treated according to an nCRT protocol that included concomitant CT schedules with or without OXA and radiotherapy dose of 55 Gy in 25 fractions. Radiomic analysis was performed on the T2-weighted (T2-w) MR images acquired during the initial tumor staging. Statistical analysis was performed separately for the cohort of patients treated with and without OXA. The ability of every single radiomic feature in predicting 5yDFS as a univariate analysis was assessed using the Wilcoxon-Mann-Whitney (WMW) test or t-test. Two logistic models (one for each cohort) were calculated, and their performance was assessed using the area under the receiver operating characteristic (ROC) curve (AUC). ResultsA total of 176 image features belonging to four families (morphological, statistical, textural, and fractal) were calculated for each patient. At the univariate analysis, the only feature showing significance in predicting 5yDFS was the maximum fractal dimension of the subpopulation identified considering 30% and 50% as threshold levels (maxFD(30-50)). Once the models were developed using this feature, an AUC of 0.67 (0.57-0.77) and 0.75 (0.56-0.95) was obtained for patients treated with and without OXA, respectively. A maxFD(30-50) >1.6 was correlated to a higher 5yDFS probability in patients treated with OXA. ConclusionThis study suggests that radiomic analysis of MR T2-w images can be used to define the optimal concomitant CT regimen for stage III LARC cancer patients. In particular, by providing an indication of the gross tumor volume (GTV) spatial heterogeneity at initial staging, maxFD(30-50) seems to be able to predict the probability of 5yDFS. New studies including a larger cohort of patients and external validation sets are recommended to verify the results of this hypothesis-generating study

Impact of body composition parameters on radiation therapy compliance in locally advanced rectal cancer: A retrospective observational analysis

Background: The impact of body composition and sarcopenia in locally advanced rectal cancer (LARC) is still unclear, even several studies have been published on this issue. Our study aims to analyze the impact of sarcopenia on neoadjuvant chemoradiotherapy (nCRT) tolerance and survival outcomes. Methods: This is a retrospective, monocentric study where LARC patients treated between 2010 and 2020 were enrolled. A single slice, from the pre-therapy simulation computed tomography (CT) scan, was used to perform the body composition analysis with dedicated software. The primary endpoint was the impact of body composition on radiotherapy (RT) interruption secondarily on overall survival (OS), disease-free survival (DFS), and local control (LC). Results: The study included 628 LARC patients (40.9 % female, mean age 63.4 years): 24 % had low skeletal muscle index (SMI), 30 % had low muscle density (MD) and 17 (10.3 % of obese) were sarcopenic obese. Higher BMI (OR 2.38, 95 % CI 1.36–4.01) and lower SMI (0.73, 95 % CI 0.55–0.94) resulted as independent predictors of RT interruption. Sarcopenic obesity (HR 2.83, 95 % CI 1.24–6.45) was related to worse OS, while MD (0.96, 95 % CI 0.93–0.98), and higher SMI (0.97, 95 % CI 0.95–0.99) were related to better OS; a lower MD remained also associated even in adjusted multivariable analysis (0.96, 95 % CI0.93–0.98). Moreover, higher visceral adipose tissue (VAT) resulted associated with worse DFS (1.02, 95 % CI 1.01–1.03), while higher SMI was related to better Local Control (0.96, 95 % CI 0.93–0.99). Conclusions: Body composition analysis, particularly of muscle and fat masses, may be a useful tool for better management of LARC patients undergoing RT. Increased collaboration between radiation oncologists and clinical nutritionists is advisable, to enable early nutritional support of LARC

The Role of Simultaneous Integrated Boost in Locally Advanced Rectal Cancer Patients with Positive Lateral Pelvic Lymph Nodes

Aims: Between 11 to 14% of patients with locally advanced rectal cancer (LARC) have positive lateral pelvic lymph nodes (LPLN) at diagnosis, related to a worse prognosis with a 5-year survival rate between 30 to 40%. The best treatment choice for this group of patients is still a challenge. The optimal radiotherapy (RT) dose for LPLN patients has been investigated. Methods: We retrospectively collected data from LARC patients with LPLN at the primary staging MRI, treated in our center from March 2003 to December 2020. Patients underwent a neoadjuvant concomitant chemo-radiotherapy (CRT) treatment on the primary tumor (T), mesorectum, and pelvic nodes, associated with a fluoride-based chemotherapy. The total reached dose was 45 Gy at 1.8 Gy/fr on the elective sites and 55 Gy at 2.2 Gy/fr on the disease and mesorectum. Patients were divided in two groups based on whether they received a simultaneous integrated RT boost on the LPLN or not. Overall Survival (OS), Disease Free Survival (DFS), Metastasis Free Survival (MFS), and Local Control (LC) were evaluated in the whole group and then compared between the two groups. Results: A total of 176 patients were evaluated: 82 were included in the RT boost group and 94 in the non-RT boost group. The median follow-up period was 57.8 months. All the clinical endpoint (OS, DFS, MFS, LC), resulted were affected by the simultaneous integrated boost on LPLN with a survival rate of 84.7%, 79.5%, 84.1%, and 92%, respectively, in the entire population. From the comparison of the two groups, there was a statistical significance towards the RT boost group with a p < 0.006, 0.030, 0.042, 0.026, respectively. Conclusions: Concomitant radiotherapy boost on positive LPLN has shown to be beneficial on the survival outcomes (OS, DFS, MFR, and LC) in patients with LARC and LPLN. This analysis demonstrates that a higher dose of radiotherapy on positive pelvic lymph nodes led not only to a higher local control but also to a better survival rate. These results, if validated by future prospective studies, can bring a valid alternative to the surgery dissection without the important side effects and permanent disabilities observed during the years

GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives

Background: Artificial Intelligence (AI) is increasingly used for process management in daily life. In the medical field AI is becoming part of computerized systems to manage information and encourage the generation of evidence. Here we present the development of the application of AI to IT systems present in the hospital, for the creation of a DataMart for the management of clinical and research processes in the field of breast cancer. Materials and methods: A multidisciplinary team of radiation oncologists, epidemiologists, medical oncologists, breast surgeons, data scientists, and data management experts worked together to identify relevant data and sources located inside the hospital system. Combinations of open-source data science packages and industry solutions were used to design the target framework. To validate the DataMart directly on real-life cases, the working team defined tumoral pathology and clinical purposes of proof of concepts (PoCs). Results: Data were classified into “Not organized, not ‘ontologized’ data”, “Organized, not ‘ontologized’ data”, and “Organized and ‘ontologized’ data”. Archives of real-world data (RWD) identified were platform based on ontology, hospital data warehouse, PDF documents, and electronic reports. Data extraction was performed by direct connection with structured data or text-mining technology. Two PoCs were performed, by which waiting time interval for radiotherapy and performance index of breast unit were tested and resulted available. Conclusions: GENERATOR Breast DataMart was created for supporting breast cancer pathways of care. An AI-based process automatically extracts data from different sources and uses them for generating trend studies and clinical evidence. Further studies and more proof of concepts are needed to exploit all the potentials of this system

GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives

Background: Artificial Intelligence (AI) is increasingly used for process management in daily life. In the medical field AI is becoming part of computerized systems to manage information and encourage the generation of evidence. Here we present the development of the application of AI to IT systems present in the hospital, for the creation of a DataMart for the management of clinical and research processes in the field of breast cancer. Materials and methods: A multidisciplinary team of radiation oncologists, epidemiologists, medical oncologists, breast surgeons, data scientists, and data management experts worked together to identify relevant data and sources located inside the hospital system. Combinations of open-source data science packages and industry solutions were used to design the target framework. To validate the DataMart directly on real-life cases, the working team defined tumoral pathology and clinical purposes of proof of concepts (PoCs). Results: Data were classified into “Not organized, not ‘ontologized’ data”, “Organized, not ‘ontologized’ data”, and “Organized and ‘ontologized’ data”. Archives of real-world data (RWD) identified were platform based on ontology, hospital data warehouse, PDF documents, and electronic reports. Data extraction was performed by direct connection with structured data or text-mining technology. Two PoCs were performed, by which waiting time interval for radiotherapy and performance index of breast unit were tested and resulted available. Conclusions: GENERATOR Breast DataMart was created for supporting breast cancer pathways of care. An AI-based process automatically extracts data from different sources and uses them for generating trend studies and clinical evidence. Further studies and more proof of concepts are needed to exploit all the potentials of this system

BRIDGE -1 TRIAL: BReak Interval Delayed surgery for Gastrointestinal Extraperitoneal rectal cancer, a multicentric phase III randomized trial

Design: Neoadjuvant chemoradiotherapy (nCRT) followed by surgery is the standard of care for locally advanced rectal cancer (LARC). Several studies have shown a correlation between a longer interval between the end of nCRT and surgery (surgical interval -SI) and an increased pathological complete response (pCR) rate, with a maximum obtained between 10 and 13 weeks. The primary endpoint of this multicenter, 2-arm randomised trial is to investigate SI lengthening, evaluating the difference in terms of complete response (CR) and Tumor Regression Grade (TRG)1 rate in the two arms. Secondly, the impact of SI lengthening on survival outcomes and quality of life (QoL) will be investigated. Methods: Intermediate-risk LARC patients undergoing nCRT will be prospectively included in the study. nCRT will be administered with a total dose of 55 Gy in 25 fractions on Gross Tumor Volume (GTV) plus the corresponding mesorectum of 45 Gy in 25 fractions on the whole pelvis. Chemotherapy with oral capecitabine will be administered continuously. The patients achieving a clinical major or complete response assessed at clinical-instrumental re-evaluation at 7-8 weeks after treatment completion, will be randomized into two groups, to undergo surgery or local excision at 9-11 weeks (control arm) or at 13-16 weeks (experimental arm). Pathological response will be assessed on the surgical specimen using the AJCC TNM v.7 and the TRG according to Mandard. Patients will be followed up to evaluate toxicity and QoL. The promoter center of the trial will conduct the randomization process through an automated procedure to prevent any possible bias. For sample size calculation, using CR difference of 20% as endpoint, 74 patients per arm will be enrolled. Conclusions: The results of this study may prospectively provide a new time frame for the clinical re-evaluation for complete/major responders patients in order to increase the CR rate to nCRT. Trial registration: ClinicalTrials.gov Identifier: NCT03581344