The Impact of HAPPY (Humanity Assurance Protocol in Interventional Radiotherapy) on the Psychological Well-being of Gynecological Cancer Patients.

BACKGROUND: HAPPY (Humanity Assurance Protocol in interventional radiotherapy) reports the necessity for gynecological cancer patients to undergo interventional radiotherapy (IRT, also called brachytherapy). The present paper has evaluated how some precautions may improve the psychological well-being of the patients during IRT. METHODS: Patients with gynecological cancer undergoing IRT-HDR were analyzed. Patients answered three questionnaires before the IRT procedure (T0) and at the end of IRT (T1): Distress Thermometer (DT), Numerical Rating Scale for IRT procedure distress (NRS), and Hospital Anxiety and Depression Scale (HADS). Correlations have been calculated pairwise through pandas. corrwith with a Pearson algorithm, and the p-values have been calculated through scipy.stats.pearsonr. Plots have been generated through seaborn and matplotlib. A Wilcoxon test was used. RESULTS: 55 patients were selected for this study. The median age of the patients was 64 (range, 39-84) years. 52 patients were with stage I endometrial cancer, whereas 3/3 patients with cervical cancer had locally advanced stages (IIB-IVA). 26 patients had a high education level (47.3%), and 38 were married or with a partner (69.1%). Only 14/55 (25.45%) patients were working. The HADS, DT, and NRS averages before the IRT procedure (T0) were 10.2, 3.8, and 4.3, respectively. After applying the HAPPY protocol, the HADS, DT, and NRS averages after IRT (T1) were 9.4, 3.4, and 2.6, respectively. The Wilcoxon signed rank test analysis showed a significant improvement in NRS (p < 0.00001) and HADS (p = 0.034). Living with a partner, parents or relatives was the only parameter statistically significantly associated with better DT pre-IRT (p = 0.04), HADS pre-IRT (p = 0.01), DT post-IRT (p = 0.01), and HADS post-IRT (p = 0.04). CONCLUSION: In our study, the HAPPY protocol was associated with a significant reduction in patients' distress, anxiety, and discomfort.

A process mining approach for clinical guidelines compliance: real-world application in rectal cancer.

In the era of evidence-based medicine, several clinical guidelines were developed, supporting cancer management from diagnosis to treatment and aiming to optimize patient care and hospital resources. Nevertheless, individual patient characteristics and organizational factors may lead to deviations from these standard recommendations during clinical practice. In this context, process mining in healthcare constitutes a valid tool to evaluate conformance of real treatment pathways, extracted from hospital data warehouses as event log, to standard clinical guidelines, translated into computer-interpretable formats. In this study we translate the European Society of Medical Oncology guidelines for rectal cancer treatment into a computer-interpretable format using Pseudo-Workflow formalism (PWF), a language already employed in pMineR software library for Process Mining in Healthcare. We investigate the adherence of a real-world cohort of rectal cancer patients treated at Fondazione Policlinico Universitario A. Gemelli IRCCS, data associated with cancer diagnosis and treatment are extracted from hospital databases in 453 patients diagnosed with rectal cancer. PWF enables the easy implementation of guidelines in a computer-interpretable format and visualizations that can improve understandability and interpretability of physicians. Results of the conformance checking analysis on our cohort identify a subgroup of patients receiving a long course treatment that deviates from guidelines due to a moderate increase in radiotherapy dose and an addition of oxaliplatin during chemotherapy treatment. This study demonstrates the importance of PWF to evaluate clinical guidelines adherence and to identify reasons of deviations during a treatment process in a real-world and multidisciplinary setting.

Non-melanoma Skin Cancer Treated by Contact High-dose-rate Radiotherapy (Brachytherapy): A Mono-institutional Series and Literature Review.

BACKGROUND/AIM: Non-melanoma skin cancers (NMSC) are the most common neoplasms worldwide and their incidence has been proven to increase in recent years and their treatment should aim at cancer cure as well as cosmetic and functional results. The aim of the study was to report the results of our mono-institutional series of high-dose-rate radiotherapy (cHDR-RT) in NMSC, based on a homogenous technique and two different treatment schedules. PATIENTS AND METHODS: All patients affected by NMSC who were consecutively evaluated and treated at our Interventional Oncology Center from October 2018 to August 2020, were included. Patients underwent cHDR-RT using flap applicators and remotely afterloaded Ir-192 sources. RESULTS: Overall, 51 patients were treated for a total of 67 lesions. Local control (LC) and disease-specific survival (DSS) were 94.0% and 100%, respectively. Grade 1, grade 2, grade 3 and grade 4 acute toxicity rates were 24.6%, 3.5%, 3.5%, and 0.0%, respectively. The cosmetic results were graded as excellent/good, fair, and poor in 73.7%, 19.3%, and 7.0%. CONCLUSION: cHDR-RT of NMSC is an effective alternative to surgery due to excellent outcomes both in terms of local control and aesthetic results especially in the face.

The Assisi Think Tank Meeting Breast Large Database for Standardized Data Collection in Breast Cancer-ATTM.BLADE.

Background: During the 2016 Assisi Think Tank Meeting (ATTM) on breast cancer, the panel of experts proposed developing a validated system, based on rapid learning health care (RLHC) principles, to standardize inter-center data collection and promote personalized treatments for breast cancer. Material and Methods: The seven-step Breast LArge DatabasE (BLADE) project included data collection, analysis, application, and evaluation on a data-sharing platform. The multidisciplinary team developed a consensus-based ontology of validated variables with over 80% agreement. This English-language ontology constituted a breast cancer library with seven knowledge domains: baseline, primary systemic therapy, surgery, adjuvant systemic therapies, radiation therapy, follow-up, and toxicity. The library was uploaded to the BLADE domain. The safety of data encryption and preservation was tested according to General Data Protection Regulation (GDPR) guidelines on data from 15 clinical charts. The system was validated on 64 patients who had undergone post-mastectomy radiation therapy. In October 2018, the BLADE system was approved by the Ethical Committee of Fondazione Policlinico Gemelli IRCCS, Rome, Italy (Protocol No. 0043996/18). Results: From June 2016 to July 2019, the multidisciplinary team completed the work plan. An ontology of 218 validated variables was uploaded to the BLADE domain. The GDPR safety test confirmed encryption and data preservation (on 5000 random cases). All validation benchmarks were met. Conclusion:BLADE is a support system for follow-up and assessment of breast cancer care. To successfully develop and validate it as the first standardized data collection system, multidisciplinary collaboration was crucial in selecting its ontology and knowledge domains. BLADE is suitable for multi-center uploading of retrospective and prospective clinical data, as it ensures anonymity and data privacy.

Could the conservative approach be considered safe in the treatment of locally advanced rectal cancer in case of a clinical near-complete or complete response? A retrospective analysis.

BACKGROUND: Conservative approach has emerged as an option for the management of rectal cancer (RC) patients with a near or complete clinical response after neoadjuvant chemoradiotherapy (nCRT). The aim of this study is to assess the impact of the conservative approach by comparing patients' survival outcomes and quality of life with those who had surgical resection. METHODS: A single-institution and retrospective study including RC patients who reached a near complete or complete clinical response after nCRT from January 2010 to September 2019. Conservative approaches included local excision or watch and wait strategy; surgery approaches included anterior resection or abdominal-perineal resection.Local regrowth (LR), overall survival, disease free survival, metastasis free survival and colostomy free survival were evaluated through Kaplan-Meier curves and compared trough log-rank tests. Quality of life was measured by the following validated questionnaires: EORTC QLC30, EORTC QLQ - CR29 and Fecal Incontinence Quality of Life scale. RESULTS: Overall 157 patients were analyzed: 105 (66,9%) underwent radical surgery and 52 (33,1%) had a conservative approach. With a median follow-up of 51 months, 2 patients in the surgical group had a local recurrence and 8 in the conservative group had a LR, respectively. Distance metastasis occurred in 7 and 1 patients of surgical and conservative group, respectively. No differences were detected in terms of survival outcomes except for colostomy free survival (p: 0,01). The conservative group showed better intestinal (p < 0.01) and sexual (p: 0,04) function and emotional status (p: 0,02). CONCLUSIONS: Conservative approach seems to be safe in terms of survival outcomes with a significant advantage on quality of life in RC patients who achieved clinical complete response after nCRT.

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.

Convolutional Neural Network Based on Fluorescein Angiography Images for Retinopathy of Prematurity Management.

Purpose: The purpose of this study was to explore the use of fluorescein angiography (FA) images in a convolutional neural network (CNN) in the management of retinopathy of prematurity (ROP). Methods: The dataset involved a total of 835 FA images of 149 eyes (90 patients), where each eye was associated with a binary outcome (57 "untreated" eyes and 92 "treated"; 308 "untreated" images, 527 "treated"). The resolution of the images was 1600 and 1200 px in 20% of cases, whereas the remaining 80% had a resolution of 640 and 480 px. All the images were resized to 640 and 480 px before training and no other preprocessing was applied. A CNN with four convolutional layers was trained on 90% of the images (n = 752) randomly chosen. The accuracy of the prediction was assessed on the remaining 10% of images (n = 83). Keras version 2.2.0 for R with Tensorflow backend version 1.11.0 was used for the analysis. Results: The validation accuracy after 100 epochs was 0.88, whereas training accuracy was 0.97. The receiver operating characteristic (ROC) presented an area under the curve (AUC) of 0.91. Conclusions: Our study showed, we believe for the first time, the applicability of artificial intelligence (CNN) technology in the ROP management driven by FA. Further studies are needed to exploit different fields of applications of this technology. Translational Relevance: This algorithm is the basis for a system that could be applied to both ROP as well as experimental oxygen induced retinopathy.

A new standardized data collection system for brain stereotactic external radiotherapy: the PRE.M.I.S.E project.

BACKGROUND: In recent years, novel radiation therapy techniques have moved clinical practice toward tailored medicine. An essential role is played by the decision support system, which requires a standardization of data collection. The Aim of the Prediction Models In Stereotactic External radiotherapy (PRE.M.I.S.E.) project is the implementation of systems that analyze heterogeneous datasets. This article presents the project design, focusing on brain stereotactic radiotherapy (SRT). MATERIALS & METHODS: First, raw ontology was defined by exploiting semiformal languages (block and entity relationship diagrams) and the natural language; then, it was transposed in a Case Report Form, creating a storage system. RESULTS: More than 130 brain SRT's variables were selected. The dedicated software Beyond Ontology Awareness (BOA-Web) was set and data collection is ongoing. CONCLUSION: The PRE.M.I.S.E. project provides standardized data collection for a specific radiation therapy technique, such as SRT. Future aims are: including other centers and validating an extracranial SRT ontology.