Search

Current approach to identify BRCA 1/2 carriers in the general population is ineffective as most of the carriers remain undiagnosed. Radiomics is an emerging tool for large scale quantitative analysis of features from standard diagnostic imaging and has been applied also to identify gene mutational status. The objective of this study was to evaluate the clinical and economic impact of integrating a radiogenomics model with clinical and family history data in identifying BRCA mutation carriers in the general population. This cost‐effective analysis compares three different approaches to women selection for BRCA testing: established clinical criteria/family history (model 1); established clinical criteria/family history and the currently available radiogenomic model (49% sensitivity and 87% specificity) based on ultrasound images (model 2); same approach used in model 2 but simulating an improvement of the performances of the radiogenomic model (80% sensitivity and 95% specificity) (model 3). All models were trained with literature data. Direct costs were calculated according to the rates currently used in Italy. The analysis was performed simulating different scenarios on the generation of 18‐year‐old girls in Italy (274,000 people). The main outcome was to identify the most effective model comparing the number of years of BRCA‐cancer healthy life expectancy (HLYs). An incremental cost‐effectiveness ratio (ICER) was also derived to determine the cost in order to increase BRCA carriers‐healthy life span by 1 year. Compared to model 1, model 2 increases the detection rate of BRCA carriers by 41.8%, reduces the rate of BRCA‐related cancers by 23.7%, generating over a 62‐year observation period a cost increase by 2.51 €/Year/Person. Moreover, model 3 further increases BRCA carriers detection (+ 68.3%) and decrease in BRCA‐related cancers (− 38.4%) is observed compared to model 1. Model 3 increases costs by 0.7 €/Year/Person. After one generation, the estimated ICER in the

Background: The current management of lung cancer patients has reached a high level of complexity. Indeed, besides the traditional clinical variables (e.g., age, sex, TNM stage), new omics data have recently been introduced in clinical practice, thereby making more complex the decision-making process. With the advent of Artificial intelligence (AI) techniques, various omics datasets may be used to create more accurate predictive models paving the way for a better care in lung cancer patients. Methods: The LANTERN study is a multi-center observational clinical trial involving a multidisciplinary consortium of five institutions from different European countries. The aim of this trial is to develop accurate several predictive models for lung cancer patients, through the creation of Digital Human Avatars (DHA), defined as digital representations of patients using various omics-based variables and integrating well-established clinical factors with genomic data, quantitative imaging data etc. A total of 600 lung cancer patients will be prospectively enrolled by the recruiting centers and multi-omics data will be collected. Data will then be modelled and parameterized in an experimental context of cutting-edge big data analysis. All data variables will be recorded according to a shared common ontology based on variable-specific domains in order to enhance their direct actionability. An exploratory analysis will then initiate the biomarker identification process. The second phase of the project will focus on creating multiple multivariate models trained though advanced machine learning (ML) and AI techniques for the specific areas of interest. Finally, the developed models will be validated in order to test their robustness, transferability and generalizability, leading to the development of the DHA. All the potential clinical and scientific stakeholders will be involved in the DHA development process. The main goals aim of LANTERN project are: i) To develop predictive mode

inglese

BackgroundThe glioblastoma's bad prognosis is primarily due to intra-tumor heterogeneity, demonstrated from several studies that collected molecular biology, cytogenetic data and more recently radiomic features for a better prognostic stratification. The GLIFA project (GLIoblastoma Feature Analysis) is a multicentric project planned to investigate the role of radiomic analysis in GB management, to verify if radiomic features in the tissue around the resection cavity may guide the radiation target volume delineation. Materials and methodsWe retrospectively analyze from three centers radiomic features extracted from 90 patients with total or near total resection, who completed the standard adjuvant treatment and for whom we had post-operative images available for features extraction. The Manual segmentation was performed on post gadolinium T1w MRI sequence by 2 radiation oncologists and reviewed by a neuroradiologist, both with at least 10 years of experience. The Regions of interest (ROI) considered for the analysis were: the surgical cavity +/- post-surgical residual mass (CTV_cavity); the CTV a margin of 1.5 cm added to CTV_cavity and the volume resulting from subtracting the CTV_cavity from the CTV was defined as CTV_Ring. Radiomic analysis and modeling were conducted in RStudio. Z-score normalization was applied to each radiomic feature. A radiomic model was generated using features extracted from the Ring to perform a binary classification and predict the PFS at 6 months. A 3-fold cross-validation repeated five times was implemented for internal validation of the model. ResultsTwo-hundred and seventy ROIs were contoured. The proposed radiomic model was given by the best fitting logistic regression model, and included the following 3 features: F_cm_merged.contrast, F_cm_merged.info.corr.2, F_rlm_merged.rlnu. A good agreement between model predicted probabilities and observed outcome probabilities was obtained (p-value of 0.49 by Hosmer and Lemeshow statistical te

Objective: To develop and validate magnetic resonance (MR) imaging-based radiomics models for high-risk endometrial cancer (EC) prediction preoperatively, to be able to estimate deep myometrial invasion (DMI) and lymphovascular space invasion (LVSI), and to discriminate between low-risk and other categories of risk as proposed by ESGO/ESTRO/ESP (European Society of Gynaecological Oncology-European Society for Radiotherapy & Oncology and European Society of Pathology) guidelines. Methods: This retrospective study included 96 women with EC who underwent 1.5-T MR imaging before surgical staging between April 2009 and May 2019 in two referral centers divided into training (T = 73) and validation cohorts (V = 23). Radiomics features were extracted using the MODDICOM library with manual delineation of whole-tumor volume on MR images (axial T2-weighted). Diagnostic performances of radiomic models were evaluated by area under the receiver operating characteristic (ROC) curve in training (AUCT) and validation (AUCV) cohorts by using a subset of the most relevant texture features tested individually in univariate analysis using Wilcoxon-Mann-Whitney. Results: A total of 228 radiomics features were extracted and ultimately limited to 38 for DMI, 29 for LVSI, and 15 for risk-classes prediction for logistic radiomic modeling. Whole-tumor radiomic models yielded an AUCT/AUCV of 0.85/0.68 in DMI estimation, 0.92/0.81 in LVSI prediction, and 0.84/0.76 for differentiating low-risk vs other risk classes (intermediate/high-intermediate/high). Conclusion: MRI-based radiomics has great potential in developing advanced prognostication in EC.

In patients with kidney graft neoplasms, the treatment of choice is still represented by surgical approach, mainly based on partial nephrectomy/nephron sparing surgery (NSS). In this oncologic setting, focal treatments (FT) are becoming more and more useful to avoid the risk of dialysis, considering graft viability of utmost importance. There is still little evidence on which is the best FT option in kidney graft neoplasms and on its therapeutic indications. We performed a systematic review to assess the role of FT such as thermal ablation, interventional radiotherapy, electrochemotherapy, and stereotactic body radiotherapy, as alternative to NSS in the treatment of Stage I kidney cancer. We searched PubMed, Scopus, and Web of Science for articles published between 2010 and 2020 focusing on kidney transplant recipients with kidney graft neoplasm who had undergone FT. The review is framed by the population, intervention, control, and outcomes criteria. The studies underlined safety and efficacy of FT, with low morbidity and good graft survival, but none of them provided a direct comparison with graft nephrectomy or NSS. There is still no clear evidence that FTs, and percutaneous ones in particular, are indicated as a standard treatment in kidney graft neoplasms as opposed to total or partial graft nephrectomy.

Figure Legend In the original publication [1], there was a mistake in the legend for Figure 8. Values for C1 and C2 were inverted. The correct legend appears below. Figure 8 legend becomes: Clustering analysis from Inception V3 deep learning features based on combined superficial and deep OCT-As. The mean 1-year BVCA for C1 and C2 was 66.67 and 49.1, respectively, with a t-test p-value equal to 0.005. Text Correction There was an error in the original publication. Values for C1 and C2 were inverted. A correction has been made to Abstract, sentence: best-corrected visual acuity (BCVA) C1 = 49.10 (18.60 SD) and BCVA C2 = 66.67 (16.00 SD, p = 0.005) The sentence becomes: best-corrected visual acuity (BCVA) C1 = 66.67 (16.00 SD) and BCVA C2 = 49.10 (18.60 SD, p = 0.005). A correction has been made to Results, Paragraph 9, sentence: In this configuration, the mean of letters for C1 and C2 was 49.1 and 66.67, respectively, with a t-test p-value equal to 0.005 (Figure 8) The sentence becomes: In this configuration, the mean of letters for C1 and C2 was 66.67 and 49.1, respectively, with a t-test p-value equal to 0.005 (Figure 8). Error in Table In the original publication, there was a mistake in Table 2 as published. Values for C1 and C2 were inverted. The corrected Table 2 appears below.

The aim of the study was to evaluate survival in patients with advanced glottic laryngeal squamous cell carcinoma treated by bioradiotherapy (BioRT) with cetuximab and eventual salvage surgery (group A, n = 66) or upfront surgery (total laryngectomy or near-total laryngectomy) with or without postoperative radiotherapy (PORT) (group B, n = 66). The predictive role of HER1 expression in the bioselection of tumors was evaluated. Relapse-free (RFS), metastasis-free (MFS), overall (OS) survivals, salvageability, and rates of larynx preservation were analyzed. The two groups were balanced by propensity score method on their baseline characteristics. No significant differences in RFS and OS were found, while MFS results were significantly higher in group A (p = 0.04). Group A showed a 22% reduction in the probability of nodal metastasis (p = 0.0023), mostly in tumors with higher HER1 expression. The salvageability with TL at 3 years was 54% after prior BioRT and 18% after prior upfront NTL (p < 0.05). BioRT with cetuximab showed a reduction in the risk of lymph node relapse, particularly in the case of HER1 positive tumors, and it allowed to achieve a higher rate of functional larynx preservation and a higher salvageability compared with upfront surgery. HER1 analysis could be clinically useful in the bioselection of tumors that may benefit from BioRT with cetuximab, particularly in those with neck node metastatic propensity.

(1) Background: Periorificial face cancer (PFC), defined as both squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) arising around the eyelids, the nose vestibule and the lips, has very high incidence rates worldwide. The aim of our retrospective analysis, focusing on local control (LC) and patients’ degree of satisfaction with the cosmetic outcome, is to present the results of a single institutional series of patients affected by PFC and treated by interventional radiotherapy (brachytherapy–IRT). (2) Methods: We retrospectively evaluated patients affected by PFC who were treated at our Interventional Oncology Center (IOC) with interstitial IRT from 2012 to 2021 with doses and volumes specific for each subsite considered. (3) Results: We report the results of 40 patients affected by PFC and treated by HDR interstitial IRT. The median follow-up was 24 months. The actuarial 3-year LC was 94%. Regarding patients’ satisfaction, we found that 93% of patients were satisfied and only 7% of patients were not completely satisfied with the final cosmetic result. (4) Conclusions: Interstitial HDR IRT could be an effective therapeutic option providing adequate disease control and preventing potentially disfiguring surgical approaches. More numerous and standardized studies are warranted to confirm the available evidence.

Colorectal cancer (RC) is the third most common cancer, with an increasing incidence in recent years. Digital health solutions supporting multidisciplinary tumor boards (MTBs) could improve positive outcomes for RC patients. This paper describes the implementation process of a digital solution within the RC-MTB and its impact analysis in the context of the Fondazione Policlinico 'A. Gemelli' in Italy. Adopting a two-phase methodological approach, the first phase qualitatively describes each phase of the implementation of the IT platform, while the second phase quantitatively describes the analysis of the impact of the IT platform. Descriptive and inferential analyses were performed for all variables, with a p-value < 0.05 being considered statistically significant. The implementation of the platform allowed more healthcare professionals to attend meetings and resulted in a decrease in patients sent to the RC-MTB for re-staging and further diagnostic investigations and an increase in patients sent to the RC-MTB for treatment strategies. The results could be attributed to the facilitated access to the platform remotely for specialists, partly compensating for the restrictions imposed by the COVID-19 pandemic, as well as to the integration of the platform into the hospital's IT system. Furthermore, the early involvement of healthcare professionals in the process of customizing the platform to the specific needs of the RC-MTB may have facilitated its use and contributed to the encouraging quantitative results

Introduction: New digital technologies can become a tool for welcoming the patient through the artistic dimension. Cancer patients, in particular, need support that accompanies and supports them throughout their treatment. Materials and methods: The Art4ART project consist in the structural proposal to cancer patients of a web-based digital platform containing several forms of art as video-entertainments; a multimedia immersive room; an art-based welcoming of the patients with several original paintings; an environment with a peacefulness vertical garden; a reconceptualization of the chemotherapy-infusion seats. Data regarding patients’ preference and choices will be stored and analysed also using artificial intelligence (AI) algorithm to measure and predict impact indicators regarding clinical outcomes (survival and toxicity), psychological indicators. Moreover, the same digital platform will contribute to a better organization of the activities. Discussion: Through the systematic acquisition of patient preferences and through integration with other clinical parameters, it will be possible to measure the clinical, psychological, organisational, and social impact of the newly implemented Art4ART project. The use of digital technology leads us to apply the reversal of viewpoint from therapeutic acts to patient-centred care.

BRCA 1/2 genes mutation status can already determine the therapeutic algorithm of high grade serous ovarian cancer patients. Nevertheless, its assessment is not sufficient to identify all patients with genomic instability, since BRCA 1/2 mutations are only the most well-known mechanisms of homologous recombination deficiency (HR-d) pathway, and patients displaying HR-d behave similarly to BRCA mutated patients. HRd assessment can be challenging and is progressively overcoming BRCA testing not only for prognostic information but more importantly for drugs prescriptions. However, HR testing is not already integrated in clinical practice, it is quite expensive and it is not refundable in many countries. Selecting patients who are more likely to benefit from this assessment (BRCA 1/2 WT patients) at an early stage of the diagnostic process, would allow an optimization of genomic profiling resources. In this study, we sought to explore whether somatic BRCA1/2 genes status can be predicted using computational pathology from standard hematoxylin and eosin histology. In detail, we adopted a publicly available, deep-learning-based weakly supervised method that uses attention-based learning to automatically identify sub regions of high diagnostic value to accurately classify the whole slide (CLAM). The same model was also tested for progression free survival (PFS) prediction. The model was tested on a cohort of 664 (training set: n = 464, testing set: n = 132) ovarian cancer patients, of whom 233 (35.1%) had a somatic BRCA 1/2 mutation. An area under the curve of 0.7 and 0.55 was achieved in the training and testing set respectively. The model was then further refined by manually identifying areas of interest in half of the cases. 198 images were used for training (126/72) and 87 images for validation (55/32). The model reached a zero classification error on the training set, but the performance was 0.59 in terms of validation ROC AUC, with a 0.57 validation accuracy. Finally

Colorectal cancer (CRC) is one of the most common causes of death from cancer. Lung seeding occurs in approximately 10% of patients surgically treated for primary CRC with radical intent: the lung is the most common site of metastases after the liver. While surgical treatment of liver metastases is widely accepted to affect long-term outcomes, more controversial and not standardized is the therapy for CRC patients developing lung metastases. Experience suggests the potential curative role of pulmonary metastasectomy, especially in oligometastatic disease. However, the optimal strategy of care and the definition of prognostic factors after treatment still need to be defined. This review focused on the uncommon scenario of single pulmonary metastases from CRC. We explored pertinent literature and provide an overview of the epidemiology, clinical characteristics and imaging of single pulmonary metastases from CRC. Additionally, we identified the best available evidence for overall management. In particular, we analyzed the role and results of locoregional approaches (surgery, radiotherapy or ablative procedures) and their integration with systemic therapy.

N/A

Background: The COVID-19 pandemic affected healthcare systems worldwide. Predictive models developed by Artificial Intelligence (AI) and based on timely, centralized and standardized real world patient data could improve management of COVID-19 to achieve better clinical outcomes. The objectives of this manuscript are to describe the structure and technologies used to construct a COVID-19 Data Mart architecture and to present how a large hospital has tackled the challenge of supporting daily management of COVID-19 pandemic emergency, by creating a strong retrospective knowledge base, a real time environment and integrated information dashboard for daily practice and early identification of critical condition at patient level. This framework is also used as an informative, continuously enriched data lake, which is a base for several on-going predictive studies. Methods: The information technology framework for clinical practice and research was described. It was developed using SAS Institute software analytics tool and SAS® Vyia® environment and Open-Source environment R ® and Python ® for fast prototyping and modeling. The included variables and the source extraction procedures were presented. Results: The Data Mart covers a retrospective cohort of 5528 patients with SARS-CoV-2 infection. People who died were older, had more comorbidities, reported more frequently dyspnea at onset, had higher D-dimer, C-reactive protein and urea nitrogen. The dashboard was developed to support the management of COVID-19 patients at three levels: hospital, single ward and individual care level. Interpretation: The COVID-19 Data Mart based on integration of a large collection of clinical data and an AI-based integrated framework has been developed, based on a set of automated procedures for data mining and retrieval, transformation and integration, and has been embedded in the clinical practice to help managing daily care. Benefits from the availability of a Data Mart include the oppor

Purpose: The aim of this study is to determine if radiomics features extracted from staging magnetic resonance (MR) images could predict 2-year long-term clinical outcome in patients with locally advanced cervical cancer (LACC) after neoadjuvant chemoradiotherapy (NACRT). Materials and methods: We retrospectively enrolled patients with LACC diagnosis who underwent NACRT followed by radical surgery in two different institutions. Radiomics features were extracted from pre-treatment 1.5 T T2w MR images. The predictive performance of each feature was quantified in terms of Wilcoxon–Mann–Whitney test. Among the significant features, Pearson correlation coefficient (PCC) was calculated to quantify the correlation among the different predictors. A logistic regression model was calculated considering the two most significant features at the univariate analysis showing the lowest PCC value. The predictive performance of the model created was quantified out using the area under the receiver operating characteristic curve (AUC). Results: A total of 175 patients were retrospectively enrolled (142 for the training cohort and 33 for the validation one). 1896 radiomic feature were extracted, 91 of which showed significance (p < 0.05) at the univariate analysis. The radiomic model showing the highest predictive value combined the features calculated starting from the gray level co-occurrence-based features. This model achieved an AUC of 0.73 in the training set and 0.91 in the validation set. Conclusions: The proposed radiomic model showed promising performances in predicting 2-year overall survival before NACRT. Nevertheless, the observed results should be tested in larger studies with consistent external validation cohorts, to confirm their potential clinical use.

The modern management of esophageal cancer is crucially based on a multidisciplinary and multimodal approach. Radiotherapy is involved in neoadjuvant and adjuvant settings; moreover, it includes radical and palliative treatment intention (with a focus on the use of a stent and its potential integration with radiotherapy). In this review, the above-mentioned settings and approaches will be described. Referring to available international guidelines, the background evidence bases will be reviewed, and the ongoing, more relevant trials will be outlined. Target definitions and radiotherapy doses to administer will be mentioned. Peculiar applications such as brachytherapy (interventional radiation oncology), and data regarding innovative approaches including MRI-guided-RT and radiomic analysis will be reported. A focus on the avoidance of surgery for major clinical responses (particularly for SCC) is detailed.

Introduction: Pancreatic cancer (PC) is one of the most aggressive tumours, and better risk stratification among patients is required to provide tailored treatment. The meaning of radiomics and texture analysis as predictive techniques are not already systematically assessed. The aim of this study is to assess the role of radiomics in PC. Methods: A PubMed/MEDLINE and Embase systematic review was conducted to assess the role of radiomics in PC. The search strategy was ‘radiomics [All Fields] AND (“pancreas” [MeSH Terms] OR “pancreas” [All Fields] OR “pancreatic” [All Fields])’ and only original articles referred to PC in humans in the English language were considered. Results: A total of 123 studies and 183 studies were obtained using the mentioned search strategy on PubMed and Embase, respectively. After the complete selection process, a total of 56 papers were considered eligible for the analysis of the results. Radiomics methods were applied in PC for assessment technical feasibility and reproducibility aspects analysis, risk stratification, biologic or genomic status prediction and treatment response prediction. Discussion: Radiomics seems to be a promising approach to evaluate PC from diagnosis to treatment response prediction. Further and larger studies are required to confirm the role and allowed to include radiomics parameter in a comprehensive decision support system.

Purpose/Objective(s): Stereotactic ablative body radiotherapy (SBRT) for vertebral metastases is a challenging treatment process. Planning automation has recently reported the potential to improve plan quality and increase planning efficiency. We performed a dosimetric evaluation of the new Personalized engine implemented in Pinnacle3 for full planning automation of SBRT spine treatments in terms of plan quality, treatment efficiency, and delivery accuracy. Materials/Methods: The Pinnacle3 treatment planning system was used to reoptimize six patients with spinal metastases, employing two separate automated engines. These two automated engines, the existing Autoplanning and the new Personalized, are both template-based algorithms that employ a wishlist to construct planning goals and an iterative technique to replicate the planning procedure performed by skilled planners. The boost tumor volume (BTV) was defined as the macroscopically visible lesion on RM examination, and the planning target volume (PTV) corresponds with the entire vertebra. Dose was prescribed according to simultaneous integrated boost strategy with BTV and PTV irradiated simultaneously over 3 fractions with a dose of 30 and 21 Gy, respectively. Dose-volume histogram (DVH) metrics and conformance indices were used to compare clinically accepted manual plans (MP) with automated plans developed using both Autoplanning (AP) and Personalized engines (Pers). All plans were evaluated for planning efficiency and dose delivery accuracy. Results: For similar spinal cord sparing, automated plans reported a significant improvement of target coverage and dose conformity. On average, Pers plans increased near-minimal dose D98% by 10.4% and 8.9% and target coverage D95% by 8.0% and by 4.6% for BTV and PTV, respectively. Automated plans provided significantly superior dose conformity and dose contrast by 37%–47% and by 4.6%–5.7% compared with manual plans. Overall planning times were dramatically reduced to about

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 ra

Background: Neoadjuvant chemoradiation therapy (nCRT) is the standard treatment modality in locally advanced rectal cancer (LARC). Since response to radiotherapy (RT) is dose dependent in rectal cancer, dose escalation may lead to higher complete response rates. The possibility to predict patients who will achieve complete response (CR) is fundamental. Recently, an early tumour regression index (ERI) was introduced to predict pathological CR (pCR) after nCRT in LARC patients. The primary endpoints will be the increase of CR rate and the evaluation of feasibility of delta radiomics-based predictive MRI guided Radiotherapy (MRgRT) model. Methods: Patients affected by LARC cT2-3, N0-2 or cT4 for anal sphincter involvement N0-2a, M0 without high risk features will be enrolled in the trial. Neoadjuvant CRT will be administered using MRgRT. The initial RT treatment will consist in delivering 55 Gy in 25 fractions on Gross Tumor Volume (GTV) plus the corresponding mesorectum and 45 Gy in 25 fractions on the drainage nodes. Chemotherapy with 5-fluoracil (5-FU) or oral capecitabine will be administered continuously. A 0.35 Tesla MRI will be acquired at simulation and every day during MRgRT. At fraction 10, ERI will be calculated: if ERI will be inferior than 13.1, the patient will continue the original treatment; if ERI will be higher than 13.1 the treatment plan will be reoptimized, intensifying the dose to the residual tumor at the 11th fraction to reach 60.1 Gy. At the end of nCRT instrumental examinations are to be performed in order to restage patients. In case of stable disease or progression, the patient will undergo surgery. In case of major or complete clinical response, conservative approaches may be chosen. Patients will be followed up to evaluate toxicity and quality of life. The number of cases to be enrolled will be 63: all the patients will be treated at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome. Discussion: This clinical tri

Aim: The first prototype of the “Multidisciplinary Tumor Board Smart Virtual Assistant” is presented, aimed to (i) Automated classification of clinical stage starting from different free-text diagnostic reports; (ii) Resolution of inconsistencies by identifying controversial cases drawing the clinician’s attention to particular cases worthy for multi-disciplinary discussion; (iii) Support environment for education and knowledge transfer to junior staff; (iv) Integrated data-driven decision making and standardized language and interpretation. Patients and Method: Data from patients affected by Locally Advanced Cervical Cancer (LACC), FIGO stage IB2-IVa, treated between 2015 and 2018 were extracted. Magnetic Resonance (MR), Gynecologic examination under general anesthesia (EAU), and Positron Emission Tomography–Computed Tomography (PET-CT) performed at the time of diagnosis were the items from the Electronic Health Records (eHRs) considered for analysis. An automated extraction of eHR that capture the patient’s data before the diagnosis and then, through Natural Language Processing (NLP), analysis and categorization of all data to transform source information into structured data has been performed. Results: In the first round, the system has been used to retrieve all the eHR for the 96 patients with LACC. The system has been able to classify all patients belonging to the training set and - through the NLP procedures - the clinical features were analyzed and classified for each patient. A second important result was the setup of a predictive model to evaluate the patient’s staging (accuracy of 94%). Lastly, we created a user-oriented operational tool targeting the MTB who are confronted with the challenge of large volumes of patients to be diagnosed in the most accurate way. Conclusion: This is the first proof of concept concerning the possibility of creating a smart virtual assistant for the MTB. A significant benefit could come from the integration of these automate

Purpose: Our study investigated the contribution that the application of radiomics analysis on post-treatment magnetic resonance imaging can add to the assessments performed by an experienced disease-specific multidisciplinary tumor board (MTB) for the prediction of pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). Materials and methods: This analysis included consecutively retrospective LARC patients who obtained a complete or near-complete response after nCRT and/or a pCR after surgery between January 2010 and September 2019. A three-step radiomics features selection was performed and three models were generated: a radiomics model (rRM), a multidisciplinary tumor board model (yMTB) and a combined model (CM). The predictive performance of models was quantified using the receiver operating characteristic (ROC) curve, evaluating the area under curve (AUC). Results: The analysis involved 144 LARC patients; a total of 232 radiomics features were extracted from the MR images acquired post-nCRT. The yMTB, rRM and CM predicted pCR with an AUC of 0.82, 0.73 and 0.84, respectively. ROC comparison was not significant (p = 0.6) between yMTB and CM. Conclusion: Radiomics analysis showed good performance in identifying complete responders, which increased when combined with standard clinical evaluation; this increase was not statistically significant but did improve the prediction of clinical response.

Locally advanced pancreatic cancer (LAPC) represents a major urgency in oncology. Due to the massive involvement of the peripancreatic vessels, a curative-intent surgery is generally precluded. Historically, LAPC has been an indication for palliative systemic therapy. In recent years, with the introduction of intensive multi-agent chemotherapy regimens and aggressive surgical approaches, the survival of LAPC patients has significantly improved. In this complex and rapidly evolving scenario, the role of radiotherapy is still debated. The use of standard-dose conventional fractionated radiotherapy in LAPC has led to unsatisfactory oncological outcomes. However, technological advances in radiation therapy over recent years have definitively changed this paradigm. The use of ablative doses of radiotherapy, in association with image-guidance, respiratory organ-motion management, and adaptive protocols, has led to unprecedented results in terms of local control and survival. In this overview, principles, clinical applications, and current pitfalls of ablative radiotherapy (ART) as an emerging treatment option for LAPC are discussed.

Traditional healthcare paradigms rely on the disease-centered approach aiming at reducing human nature by discovering specific drivers and biomarkers that cause the advent and progression of diseases. This reductive approach is not always suitable to understand and manage complex conditions, such as multimorbidity and cancer. Multimorbidity requires considering heterogeneous data to tailor preventing and targeting interventions. Personalized Medicine represents an innovative approach to address the care needs of multimorbid patients considering relevant patient characteristics, such as lifestyle and individual preferences, in opposition to the more traditional “one-size-fits-all” strategy focused on interventions designed at the population level. Integration of omic (e.g., genomics) and non-strictly medical (e.g., lifestyle, the exposome) data is necessary to understand patients’ complexity. Artificial Intelligence can help integrate and manage heterogeneous data through advanced machine learning and bioinformatics algorithms to define the best treatment for each patient with multimorbidity and cancer. The experience of an Italian research hospital, leader in the field of oncology, may help to understand the multifaceted issue of managing multimorbidity and cancer in the framework of Personalized Medicine.

The changes and general alarm of the current COVID-19 pandemic have amplified the sense of precariousness and vulnerability for family members who, in addition to the emotional trauma of the cancer diagnosis, add the distress and fear of the risks associated with infection. The primary objectives of the present study were to investigate the psychological impact of the COVID-19 pandemic on the parents of pediatric cancer patients, and the level of stress, anxiety, and the child’s quality of life perceived by the parents during the COVID-19 epidemic. The parents of 45 consecutive children with solid and hematological tumors were enrolled. Four questionnaires (Impact of Event Scale-Revised – IES-R; Perceived Stress Scale – PSS; Spielberger State – Trait Anxiety Inventory – STAI-Y; Pediatric Quality of Life Inventory – PedsQL) were administered to the parents at the beginning of the pandemic lockdown. A 75% of parents exhibited remarkable levels of anxiety, with 60 subjects in state scale and 45 subjects in trait scale having scores that reached and exceeded the STAI-Y cut off. The bivariate matrix of correlation found a significant positive correlation between the IES-R and PSS scores (r = 0.55, P < 0.001). There was a positive correlation between the PSS and PedsQL (emotional needs) scale (P < 0.001) and a negative correlation between IES-R and STAI-Y (P < 0.001). The results confirm that parents of pediatric cancer patients have a high psychological risk for post-traumatic symptoms, high stress levels, and the presence of clinically significant levels of anxiety.

N/A

Objectives: To assess the feasibility and safety of a repeated SHort course Accelerated RadiatiON therapy (SHARON) regimen in the palliative setting of Head and Neck (H&N) cancer in older adults. Material and Methods: Patients with histological confirmed H&N cancers, age ≥ 80 years, expected survival >3 months, and Eastern Cooperative Oncology Group (ECOG) performance status of ≤3 were enrolled. Patients were treated in cohorts of six patients: a total dose of 20 Gy was delivered in 2 consecutive days with a twice-daily fractionation (5 Gy per fraction) and at least 8-h interval. If no Grade 3 toxicity was registered, a second enrollment started with another cohort of six patients to whom were administered two cycles (total dose of 40 Gy). The primary endpoint was to evaluate the feasibility of the two cycles of treatment. Secondary endpoints were evaluation of symptoms control rate, symptoms-free survival (SFS), and Quality of Life (QoL) scores. Results: Seventeen consecutive patients (median age: 85 years) were treated. Nine patients were treated with one cycle and 8 patients with two cycles. No G3 toxicity was reported in either cohort. With a median follow-up time of 4 months, 3-month SFS in the first and second cohorts was 83.3%, and 87.5%, respectively. The overall palliative response rate was 88%. Among 13 patients reporting pain, 8 (61.5%) showed an improvement or resolution of their pain. Conclusion: Repeated short course accelerated radiotherapy in a palliative setting of H&N cancers is safe and well-tolerated in older adults.

Background: Glioblastoma Multiforme (GBM) is the most common primary brain cancer and one of the most lethal tumors. Theoretically, modern radiotherapy (RT) techniques allow dose-escalation due to the reduced irradiation of healthy tissues. This study aimed to define the adjuvant maximum tolerated dose (MTD) using volumetric modulated arc RT with simultaneous integrated boost (VMAT-SIB) plus standard dose temozolomide (TMZ) in GBM. Methods: A Phase I clinical trial was performed in operated GBM patients using VMAT-SIB technique with progressively increased total dose. RT was delivered in 25 fractions (5 weeks) to two planning target volumes (PTVs) defined by adding a 5-mm margin to the clinical target volumes (CTVs). The CTV1 was the tumor bed plus the MRI enhancing residual lesion with 10-mm margin. The CTV2 was the CTV1 plus 20-mm margin. Only PTV1 dose was escalated (planned dose levels: 72.5, 75, 77.5, 80, 82.5, 85 Gy), while PTV2 dose remained unchanged (45 Gy/1.8 Gy). Concurrent and sequential TMZ was prescribed according to the EORTC/NCIC protocol. Dose-limiting toxicities (DLTs) were defined as any G ≥ 3 non-hematological acute toxicity or any G ≥ 4 acute hematological toxicities (RTOG scale) or any G ≥ 2 late toxicities (RTOG-EORTC scale). Results: Thirty-seven patients (M/F: 21/16; median age: 59 years; median follow-up: 12 months) were enrolled and treated as follows: 6 patients (72.5 Gy), 10 patients (75 Gy), 10 patients (77.5 Gy), 9 patients (80 Gy), 2 patients (82.5 Gy), and 0 patients (85 Gy). Eleven patients (29.7%) had G1-2 acute neurological toxicity, while 3 patients (8.1%) showed G ≥ 3 acute neurological toxicities at 77.5 Gy, 80 Gy, and 82.5 Gy levels, respectively. Since two DLTs (G3 neurological: 1 patient and G5 hematological toxicity: 1 patient) were observed at 82.5 Gy level, the trial was closed and the 80 Gy dose-level was defined as the MTD. Two asymptomatic histologically proven radionecrosis were recorded. Conclusions: According to the

N/A

In recent years, in our university hospital, the number of odontogenic and non-odontogenic abscesses has been rapidly increasing. We included 70 patients from January 4th 2018 to February 19th 2020 affected by the odontogenic ones. Deep neck infection can spread to the chest and is associated with high morbidity and mortality. The purpose of this mini-review is to demonstrate that, in case of complications, a multidisciplinary approach is needed to treat these infections, so that all practitioners should work together to achieve the patient’s rapid recovery.

Purpose: The knowledge of periprostatic nerve fiber (pNF) is still incomplete by means of conventional MRI. The purpose of our study was to demonstrate if DTI imaging is able to depict anatomical features of pNF. Methods: For this retrospective study, fifty-six patients (mean age 63.5 years), who underwent 1.5-T prostate MRI, including 32 directions DTI, were enrolled between October 2014 and December 2018. ANOVA test and Student’s t-test were performed between the mean values of the number, FA values, and fiber length of pNF between base and mid-gland, mid-gland and apex, base and apex, right and left side, and anterior and posterior face of the prostate. A qualitative analysis was performed to detect the main orientation of pNF through a colorimetric 3D tractographic reconstruction. Results: The number of pNF showed a decrease from the base (322) to mid-gland (248) and apex (75) (p < 0.05). The FA values were higher at base and mid-gland (0.435 and 0.456) compared to the apex (0.313) (p < 0.05). The length of pNF was higher at apex (13.4 mm) compared to base (11.5 mm) and mid-gland (11.7 mm) (p < 0.05). The number of pNF was higher on the posterior face compared to the anterior face at base (186 vs 137), (p < 0.001). The FA values were higher on the posterior face compared to the anterior face at base (0.452 vs 0.417), mid-gland (0.483 vs 0.429), and apex (0.42 vs 0.382), (p < 0.05). The length of the pNF was higher in the posterior (14.7 mm) than in the anterior face (12 mm) at apex (p < 0.001). The main orientation of pNF was longitudinal in all patients (56/56, 100%). Conclusions: DTI imaging has been demonstrated able to depict anatomical features of pNF.

Despite of the predominant role of chemotherapy and surgery in pancreatic ductal adenocarcinoma (PDAC), radiotherapy (RT) still has a place in multimodal management of this disease where local tumour sequelae are fatal in about 40% of the patients. RT (chemoradiotherapy and stereotactic body radiotherapy) is used and investigated in the non-metastatic setting as part of definitive treatment strategies, in (neo)adjuvant settings and for locally recurrent disease. The ACROP committee was delegated by ESTRO to recommend target volume delineation for these clinical situations. The guidelines of this document are a result of a structured evaluation of the best available evidence by a panel of international experts in the field. Guidance for treatment planning including diagnostic imaging is provided. Recommendations are given for GTV delineation. The role and the definition of CTV volumes are critically discussed. Aspects of motion management and patient positioning are taken into account for PTV definition. Furthermore, aspects of delineation of organs at risk and of dose constraints are described in both, standard and hypofractionated, settings. This guideline has the purpose to support standardised and optimised processes of RT treatment planning for both, clinical practice and prospective studies.

Purpose: To investigate the potential benefits of a hypofractionated radiotherapy boost (HRB) after chemotherapy (CT) and concomitant chemoradiotherapy (CRT) in locally advanced pancreatic cancer (LAPC) patients. Primary endpoints were early and late toxicity, local control (LC) and pain-free progression (PFP) assessment. Two-years overall survival (OS), metastasis-free survival (MFS) and disease-free survival (DFS) were secondary endpoints. Materials and methods: Patients (pts) affected by unresectable non-metastatic LAPC, previously treated with CT and CRT in upfront or sandwich setting, were selected for sequential HRB. Total prescribed dose was 30 Gy in 5 fractions (fr) to pancreatic primary lesion. Dose de-escalation was allowed in case of failure in respecting organs at risk constraints. Early and late toxicity were assessed according to CTCAE v.4.0 classification. The Kersh-Hazra scale was used for pain assessment. Local Control, PFP, MFS and DFS were calculated from the date of HRB to the date of relapse or the date of the last follow-up. Results: Thirty-one pts affected by unresectable, non-metastatic LAPC were consecutively enrolled from November 2004 to October 2019. All pts completed the planned HRB. Total delivered dose varied according to duodenal dose constraint: 20 Gy in 5 fr (N: 6; 19.4%), 20 Gy in 4 fr (N: 5; 16.2%), 25 Gy in 5 fr (N: 18; 58.0%) and 30 Gy in 6 fr (N: 2; 6.4%). Early and late toxicity were assessed in all pts: no Grade 3 or 4 acute gastrointestinal toxicity and no late gastrointestinal complications occurred. Median LC was 19 months (range 1–156) and 1- and 2-year PFP were 85% and 62.7%, respectively (median 28 months; range 2–139). According to the Kersh-Hazra scale, four pts had a Grade 3 and four pts had a Grade 1 abdominal pain before HRB. At the last follow-up only 3/31 pts had residual Grade 1 abdominal pain.Median MFS was 18 months (range 1–139). The 2-year OS after HRB was 57.4%, while

Personalized Medicine (PM) has shifted the traditional top-down approach to medicine based on the identification of single etiological factors to explain diseases, which was not suitable for explaining complex conditions. The concept of PM assumes several interpretations in the literature, with particular regards to Genetic and Genomic Medicine. Despite the fact that some disease-modifying genes affect disease expression and progression, many complex conditions cannot be understood through only this lens, especially when other lifestyle factors can play a crucial role (such as the environment, emotions, nutrition, etc.). Personalizing clinical phenotyping becomes a challenge when different pathophysiological mechanisms underlie the same manifestation. Brain disorders, cardiovascular and gastroentero-logical diseases can be paradigmatic examples. Experiences on the field of Fondazione Policlinico Gemelli in Rome (a research hospital recognized by the Italian Ministry of Health as national leader in “Personalized Medicine” and “Innovative Biomedical Technologies”) could help understanding which techniques and tools are the most performing to develop potential clinical phenotypes person-alization. The connection between practical experiences and scientific literature highlights how this potential can be reached towards Systems Medicine using Artificial Intelligence tools.

In the original article published, the last sentence in the sixth paragraph of the introduction section is incorrect. The correct sentence is “This data, were confirmed also in an Italian phase II study, in which it has been demonstrated that gemcitabine-based chemoradiotherapy was correlated with improved overall survival, especially in pts who are clinically more fit to complete the foreseen treatment schedule (CRT) (Mattiucci et al. 2010)”. The original article has been corrected.

The aim of this analysis was to assess the efficacy of stereotactic body radiotherapy (SBRT) in terms of local control (LC) and progression-free survival (PFS) in patients with lymph node metastases (NMs) from solid tumors. A systematic literature search from the earliest date to July 25th, 2019 was performed following PRISMA guidelines. Papers reporting LC and/or PFS of NMs using SBRT (< 10 fractions) were selected. The clinical outcomes rates were pooled by means of a random or fixed-effect model. Twenty-nine studies were eligible (969 patients: 938 (LC) and 698 (PFS)). LC and PFS results were reported in 28 and 18 papers, respectively. Heterogeneity was observed in terms of patient and treatment characteristics. Pooled 2-year LC reported in 11 studies was 79.3% (95%CI, 72.8%–85.7%) with substantial heterogeneity between studies (Q2 test: p = 0.0083; I2 = 57.9%), while pooled 2-year PFS reported in 8 studies was 35.9% (95%CI, 22.1%–49.7%) with very high heterogeneity between studies (Q2 test: p < 0.0001; I2 = 86.1%). Grade ≥ 3 and Grade 5 toxicity rates were 2.0% and 0.2%, respectively. SBRT of NMs seems to be safe and effective in terms of LC. However, due to the marked heterogeneity of the included series, prospective studies are required.

Background: Elderly patients are often excluded from advanced treatments owing to clinical complexity or frailty. Magnetic resonance–guided radiotherapy (MRgRT) represents a new frontier of radiotherapy delivery that can play an important role in the management of these patients. Aim: To assess MRgRT feasibility in elderly patients, describe their compliance with this treatment, and provide a scoring system for elderly patient selection. Methods: Patients aged >75 years were enrolled. No restrictions on tumor site, staging, or treatment intent were applied. Patients underwent joint radiation oncology–geriatrics visits to assess the feasibility of MRgRT and to identify the most significant items (i.e. clinical variables) for the setup of a scoring system. The proposed scoring system was then internally validated on a prospectively enrolled cohort of elderly patients who were candidates for MRgRT. Results: Thirty patients were enrolled between February and March 2018. Their mean age was 81.4 ± 3.4 years (range 75–88). Radiotherapy intent was curative in 26 patients; 14 patients were considered frail at screening tests before radiotherapy. Twelve items were identified as clinically significant for the setup of the MASTER score (MRI-Guided Radiotherapy Selection Elderly Score) score. Validation of the score showed 100% reliability, with no patient discharged after selection. Conclusions: MRgRT appears to be feasible in elderly patients and the MASTER score is proposed to support clinical decision-making in recommending elderly patients for this technology.

Background: Local excision might represent an alternative to total mesorectal excision for patients with locally advanced rectal cancer who achieve a major or complete clinical response after neoadjuvant chemoradiotherapy. Methods: Between August 2005 and July 2011, 63 patients with mid-low rectal adenocarcinoma who had a major/complete clinical response after neoadjuvant chemoradiotherapy were enrolled in a multicenter prospective phase 2 trial and underwent transanal full thickness local excision. The main endpoint of this study was to evaluate the 5- and 10-year overall, relapse-free, local, and distant relapse-free survival, which were calculated by applying the Kaplan–Meier method. The rate of patients with rectum preserved and without stoma were also calculated. Results: Of 63 patients, 38 (60%) were male and 25 (40%) were female, with a median (range) age of 64 (25–82) years. At baseline, the following clinical stages were found: cT2, n = 21 (33.3%); cT3, n = 42 (66.6%), 39 (61.9%) patients were cN+. At a median (range) follow-up of 108 (32–166) months, the estimated cumulative 5- and 10-year overall survival, relapse-free survival, local recurrence-free survival, and distant recurrence-free survival were 87% (95% CI 76–93) and 79% (95% CI 66–87), 89% (95% CI 78–94) and 82% (95% CI 66–91), both 91% (95% CI 81–96), and 90% (95% CI 80–95) and 86% (95% CI 73–93), respectively. Overall, 49 (77.8%) patients had their rectum preserved, and 54 (84.1%) were stoma-free. Conclusion: In highly selected patients, the local excision approach after neoadjuvant chemoradiotherapy is associated with excellent long-term outcomes, high rates of rectum preservation and absence of permanent stoma.

N/A

Purpose: Optimal timing of surgery after neoadjuvant chemoradiotherapy (Nad-CRT) is still controversial in locally advanced rectal cancer (LARC). The primary goal of this study was to determine the best surgical interval (SI) to achieve the highest rate of pathological complete response (pCR) and secondly to evaluate the effect on survival outcomes according to the SI. Patients and methods: Patients data were extracted from the international randomized trials: Accord12/0405, EORTC22921, FFCD9203, CAO/ARO/AIO-94, CAO-ARO-AIO-04, INTERACT and TROG01.04. Inclusion criteria were: age≥ 18, cT3–T4 and cN0–2, no clinical evidence of distant metastasis at diagnosis, Nad-CRT followed by surgery. Pearson's Chi-squared test with Yates’ continuity correction for categorical variables, the Mann–Whitney test for continuous variables, Mann–Kendall test, Kaplan–Meier curves with log-rank test, univariate and multivariate logistic regression model was used for data analysis. Results: 3085 patients met the inclusion criteria. Overall, the pCR rate was 14% at a median SI of 6 weeks (range 1–31). The cumulative pCR rate increased significantly when SI lengthened, with 95% of pCR events within 10 weeks from Nad-CRT. At univariate and multivariate logistic regression analysis, lengthening of SI (p< 0.01), radiotherapy dose (p< 0.01), and the addition of oxaliplatin to Nad-CRT (p< 0.01) had a favorable impact on pCR. Furthermore, lengthening of SI was not impact on local recurrences, distance metastases, and overall survival. Conclusion: This pooled analysis suggests that the best time to achieve pCR in LARC is at 10 weeks, considering that the lengthening of SI is not detrimental concerning survival outcomes.

Aims: Pediatric patients may experience considerable distress during radiotherapy. Combining psychological interventions with standard therapies can reduce the need for sedation. The RADAR Project aims to use a systematic method of recording data that can reveal patients' difficulties and fragility during treatment. In this context, the aim of our study was to investigate the ability of a multidimensional assessment tool (M.A.P.-RT schedule) to predict the need for sedation during radiotherapy. The schedule, which is administered during the first evaluation, was created to collect information on patients and their families in a standardized way. Materials and Methods: The study enrolled pediatric patients (aged 0–18 years or 18–21 with cognitive impairment). Data were collected by means of the M.A.P.-RT module; this explores various thematic areas, and is completed by the radiation oncologist, psychologist and nurse during their first evaluation. Features were selected by means of the Boruta method (random forest classifier), and the totals of the significant partial scores on each subsection of the module were inserted into a logistic model in order to test for their correlation with the use of anesthesia and with the frequency of psychological support. The results of logistic regression (LR) were used to identify the best predictors. The AUC was used to identify the best threshold for the scores in the evaluation. Results: A total of 99 patients were considered for this analysis. The feature that best predicted both the need for anesthesia and the frequency of psychological support was the total score (TS), the AUC of the ROC being 0.9875 for anesthesia and 0.8866 for psychological support. Conclusion: During the first evaluation, the M.A.P.-RT form can predict the need for anesthesia in pediatric patients, and is a potential tool for personalizing therapeutic and management procedures.

Background: Population of oldest old will grow dramatically in the next future and cancer, physiologically related to aging, will be very prevalent among them. Lack of evidence is a huge problem to manage cancer in oldest old and will be more and more in the next years. Aims: Our purpose was to investigate the characteristics of a population of oldest old patients with cancer treated in the Radiation Oncology Unit of Fondazione Policlinico A. Gemelli IRCCS. Methods: We conducted a retrospective study. The primary outcome was to evaluate which characteristics of the population could influence the choice of oncological treatment (with radical or non-radical intent). Results: We identified a total of 348 patients: 140 were on follow-up; 177 were under treatment; 31 were considered not eligible for treatments. Patients under treatment had a high comorbidity index (mean Charlson Comorbidity Index 5.4), and a high prevalence of polypharmacy (mean number of drugs 5.6). More than half (53.1%) was treated with radical intent. Patients treated with radical intent were 1 year younger (87.1 years old vs 88.1 years old), more performant (ECOG 0.7 vs 1.3), and had less prevalence of metastatic neoplasia (6.4% vs 34.9%); comorbidities and drugs did not show differences in the two groups. Conclusion: Oldest old, usually not considered in international guidelines, are treated for oncological disease, often with radical intent. The treatment seems not to be tailored considering comorbidities but on performance status.

Background: The aim of this study was to quantify the incidence of short-term postoperative complications and functional disorders at 1 year from transanal endoscopic microsurgery (TEM) for rectal neoplasms, to compare patients treated with TEM alone and with TEM after preoperative chemoradiotherapy (CRT) and to analyse factors influencing postoperative morbidity and functional outcomes. Methods: A retrospective study was conducted on all patients treated with TEM for rectal neoplasms at our institution in January 2000–December 2017. Data from a prospectively maintained database were retrospectively analysed. Patients were divided into two groups: adenoma or early rectal cancer (no CRT group) and locally advanced extraperitoneal rectal cancer with major or complete clinical response after preoperative CRT (CRT group). Short-term postoperative mortality and morbidity and the functional results at 1 year were recorded. The two groups were compared, and a statistical analysis of factors influencing postoperative morbidity and functional outcomes was performed. Functional outcome was also evaluated with the low anterior resection syndrome (LARS) score (0–20 no LARS, 21–29 minor LARS and 30–42 major LARS). Results: One hundred and thirteen patients (71 males, 42 females, median age 64 years [range 41–80 years]) were included in the study (46 in the CRT group). The overall postoperative complication rate was 23.0%, lower in the noCRT group (p < 0.001), but only 2.7% were grade ≥ 3. The most frequent complication was suture dehiscence (17.6%), which occurred less frequently in the noCRT group (p < 0.001). At 1 year from TEM, the most frequent symptoms was urgency (11.9%, without significant differences between the CRT group and the noCRT group); the noCRT group experienced a lower rate of soiling than the CRT group (0% vs. 7.7%; p: 0.027). The incidence of LARS was evaluated in 47 patients from May 2012 on and was 21.3% occurring less frequen

Vincenzo Canzonieri’s affiliations are corrected as reflected here.

Purpose: To evaluate the 1-year visual acuity predictive performance of an artificial intelligence (AI) based model applied to optical coherence tomography angiography (OCT-A) vascular layers scans from eyes with a full-thickness macular hole (FTMH). Methods: In this observational cross-sectional, single-center study, 35 eyes of 35 patients with FTMH were analyzed by OCT-A before and 1-year after surgery. Superficial vascular plexus (SVP) and deep vascular plexus (DVP) images were collected for the analysis. AI approach based on convolutional neural networks (CNN) was used to generate a continuous predictive variable based on both SVP and DPV. Different pre-trained CNN networks were used for feature extraction and compared for predictive accuracy. Results: Among the different tested models, the inception V3 network, applied on the combination of deep and superficial OCT-A images, showed the most significant differences between the two obtained image clusters defined in C1 and C2 (best-corrected visual acuity [BCVA] C1 = 49.10 [±18.60 SD] and BCVA C2 = 66.67 [±16.00 SD, p = 0.005]). Conclusions: The AI-based analysis of preoperative OCT-A images of eyes affected by FTMH may be a useful support system in setting up visual acuity recovery prediction. The combination of preoperative SVP and DVP images showed a significant morphological predictive performance for visual acuity recovery.

Background: Patient’s satisfaction is recognized as an indicator to monitor quality in healthcare services. Patient-reported experience measures (PREMs) may contribute to create a benchmark of hospital performance by assessing quality and safety in cancer care. Methods: The areas of interest assessed were: patient-centric welcome perception (PCWP), punctuality, professionalism and comfort using the Lean Six Sigma (LSS) methodology. The RAMSI (Radioterapia Amica Mia SmileINTM (SI) My Friend RadiotherapySI), project provided for the placement of SI totems with four push buttons using HappyOrNot technology in a high-volume radiation oncology (RO) department. The SI technology was implemented in the RO department of the Fondazione Policlinico Universitario A. Gemelli IRCCS. SI totems were installed in different areas of the department. The SI Experience Index was collected, analyzed and compared. Weekly and monthly reports were created showing hourly, daily and overall trends. Results: From October 2017 to November 2019, a total of 42,755 votes were recorded: 8687, 10,431, 18,628 and 5009 feedback items were obtained for PCWP, professionalism, punctuality, and comfort, respectively. All areas obtained a SI-approved rate ≥ 8.0 Conclusions: The implementation of the RAMSI system proved to be doable according to the large amount of feedback items collected in a high-volume clinical department. The application of the LSS methodology led to specific corrective actions such as modification of the call-in-clinic system during operations planning. In order to provide healthcare optimization, a multicentric and multispecialty network should be defined in order to set up a benchmark.

Melanoma is an extremely aggressive tumor and is considered to be an extremely immunogenic tumor because compared to other cancers it usually presents a well-expressed lymphoid infiltration. The aim of this paper is to perform a multidisciplinary comprehensive review of the evidence available about the combination of radiotherapy and immunotherapy for melanoma. Radiation, in fact, can increase tumor antigens visibility and promote priming of T cells but can also exert immunosuppressive action on tumor microenvironment. Combining radiotherapy with immunotherapy provides an opportunity to increase immunostimulatory potential of radiation. We therefore provide the latest clinical evidence about radiobiological rationale, radiotherapy techniques, timing, and role both in advanced and systemic disease (with a special focus on ocular melanoma and brain, liver, and bone metastases) with a particular attention also in geriatric patients. The combination of immunotherapy and radiotherapy seems to be a safe therapeutic option, supported by a clear biological rationale, even though the available data confirm that radiotherapy is employed more for metastatic than for non-metastatic disease. Such a combination shows promising results in terms of survival outcomes; however, further studies, hopefully prospective, are needed to confirm such evidence.

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 COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters to help to identify patients with COVID-19 who are at higher risk of death. The training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020, to November 5, 2020. Afterward, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020, to February 5, 2021. The primary outcome was in-hospital case-fatality risk. The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of fivefold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48 h after the baseline measurement was plotted against its baseline value. Among the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the fivefold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n = 1463) in which the case-fatality rate was 22.6%. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk sc