Moddicom: a Complete and Easily Accessible Library for Prognostic Evaluations Relying on Image Features

Decision Support Systems (DSSs) are increasingly exploited in the area of prognostic evaluations. For predicting the effect of therapies on patients, the trend is now to use image features, i.e. information that can be automatically computed by considering images resulting by analysis. The DSSs application as predictive tools is particularly suitable for cancer treatment, given the peculiarities of the disease –which is highly localised and lead to significant social costs– and the large number of images that are available for each patient. At the state of the art, there exists tools that allow to handle image features for prognostic evaluations, but they are not designed for medical experts. They require either a strong engineering or computer science background since they do not integrate all the required functions, such as image retrieval and storage. In this paper we fill this gap by proposing Moddicom, a user-friendly complete library specifically designed to be exploited by physicians. A preliminary experimental analysis, performed by a medical expert that used the tool, demonstrates the efficiency and the effectiveness of Moddicom

The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights

Standardizing convolutional filters that enhance specific structures and patterns in medical imaging enables reproducible radiomics analyses, improving consistency and reliability for enhanced clinical insights. Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts reproducibility and clinical translation of radiomics decision support tools. In this special report, teams of researchers who developed radiomics software participated in a three-phase study (September 2020 to December 2022) to establish a standardized set of filters. The first two phases focused on finding reference filtered images and reference feature values for commonly used convolutional filters: mean, Laplacian of Gaussian, Laws and Gabor kernels, separable and nonseparable wavelets (including decomposed forms), and Riesz transformations. In the first phase, 15 teams used digital phantoms to establish 33 reference filtered images of 36 filter configurations. In phase 2, 11 teams used a chest CT image to derive reference values for 323 of 396 features computed from filtered images using 22 filter and image processing configurations. Reference filtered images and feature values for Riesz transformations were not established. Reproducibility of standardized convolutional filters was validated on a public data set of multimodal imaging (CT, fluorodeoxyglucose PET, and T1-weighted MRI) in 51 patients with soft-tissue sarcoma. At validation, reproducibility of 486 features computed from filtered images using nine configurations × three imaging modalities was assessed using the lower bounds of 95% CIs of intraclass correlation coefficients. Out of 486 features, 458 were found to be reproducible across nine teams with lower bounds of 95% CIs of intraclass correlation coefficients greater than 0.75. In conclusion, eight filter types were standardized with reference filtered images and reference feature values for verifying and calibrating radiomics software packages. A web-based tool is available for compliance checking

Radiotherapy during the COVID-19: a review about management and treatment strategies

Background: The administration of radiotherapy should be encouraged despite the emergency of COVID-19; therefore, our aim is to analyze management and therapeutic interventions to be implemented in a Radiotherapy department to allow patients to continue their treatment and health professionals to continue their work safely. Material and methods: A Pubmed search was performed, in which all articles specific to Radiotherapy and COVID-19 were included. Those articles that were too specific about the COVID-19, surgery and chemiotherapy, were excluded. Results: 315 articles were selected, of which 35 were about therapeutic strategies and 25 about management strategies. In the first category, 5 articles were about how radiotherapy could be a weapon to be used for COVID-19 positive patients with important lung problems. While 30 articles described priorities and new treatment plans for oncology patients who have to undergo radiotherapy during the pandemic. In the second category, almost all the articles explained how triage can be a preventive and monitoring way against COVID-19 in an operating unit with many patients and professionals, and other articles developed a telemedicine system, too, which allows patients to make scheduled visits without coming to the hospital and also for the staff, who can work remotely. In addition, 5 articles concerning psychological aspects of both patients and health care providers were included. Conclusion: This document can be used as a summary in the coming months/years, during the recovery phase from COVID19 pandemic outbreak and as a starting point to be used in case of further pandemic break-out

Efficacy of an eye movement desensitization and reprocessing (EMDR) intervention for a head and neck cancer patient with intolerable anxiety undergoing radiotherapy

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The future of predictive models in radiation oncology: from extensive data mining to reliable modeling of the results

No abstract availabl

Ipsilateral sequential arm movements after unilateral subthalamic deep-brain stimulation in patients with Parkinson's disease

Unilateral STN-DBS significantly improves the performance of contralateral sequential arm movements. Whether unilateral STN-DBS also improves ipsilateral sequential movement is unclear. In this Study in unmedicated parkinsonian patients. we tested the effect of unilateral STN-DBS on the performance of ipsilateral sequential movements and compared it with the performance of contralateral sequential movements. Three-dimensional movements were recorded with the ELITE system and three kinematic variables were considered: total movement time (TMT), total inter-onset latency (IOL), and spatial accuracy. Unilateral STN-DBS significantly decreased TMT in the contralateral arm and only tended to do so also in the ipsilateral arm, whereas it significantly decreased IOL and worsened spatial accuracy only on the contralateral side. Before unilateral STN-DBS a positive correlation was present between the clinical impairment and the TMTs in the contralateral and ipsilateral sides. After unilateral STN-DBS the UPDRS scores improved in the contralateral and to a lesser extent also in the ipsilateral side. Correlation analysis between clinical and kinematic data showed no differences between the contralateral and ipsilateral sides. Our kinematic findings show that after STN-DBS parkinsonian patients' performance of a sequential motor task improves significantly on the contralateral but only tended to do so on the ipsilateral side. Ipsilateral changes can be explained by the observation that the output structures of the basal ganglia send large ipsilateral and less dense contralateral projections to the thalamus. (C) 2008 Movement Disorder Society

An umbrella protocol for standardized data collection (SDC) in rectal cancer: A prospective uniform naming and procedure convention to support personalized medicine

Predictive models allow treating physicians to deliver tailored treatment moving from prescription by consensus to prescription by numbers. The main features of an umbrella protocol for standardizing data and procedures to create a consistent dataset useful to obtain a trustful analysis for a Decision Support System for rectal cancer are reported

Survival after radiotherapy in gastric cancer: Systematic review and meta-analysis

Background and purpose: A systematic review and meta-analysis was performed to assess the impact of radiotherapy on both 3- and 5-year survival in patients with resectable gastric cancer. Methods: Randomized Clinical Trials (RCTs) in which radiotherapy, (preoperative, postoperative and/or intraoperative), was compared with surgery alone or surgery plus chemotherapy in resectable gastric cancer were identified by searching web-based databases and supplemented by manual examination of reference lists. Meta-analysis was performed using Risk Ratios (RRs). Random or fixed effects models were used to combine data. The methodological quality was evaluated by Chalmers' score. Results: Radiotherapy had a significant impact on 5-year survival. Using an intent to treat (ITT) and a Per Protocol (PP) analysis, the overall 5-year RR was 1.26 (95% CI: 1.08-1.48; NNT = 17) and 1.31 (95% CI: 1.04-1.66; NNT = 13), respectively. Although the quality of the studies was variable, the data were consistent and no clear publication bias was found. Conclusion: This meta-analysis showed a statistically significant 5-year survival benefit with the addition of radiotherapy in patients with resectable gastric cancer. Radiotherapy remains a standard component in the treatment of resectable gastric cancer and new RCTs need to address the impact of new conformal radiotherapy technologies. © 2009 Elsevier Ireland Ltd. All rights reserved

RadioBio data: a Moddicom Module to Predict Tumor Control Probability and Normal Tissue Complication Probability in Radiotherapy

In this work a system for analysing radiotherapy treatment planning dose-volume data is proposed. The work starts from the definition of a framework inside a statistical scripting environment (R) used for creating a software package. The analysis of dose-volume data in radiotherapy of malignant tumours is mandatory for evaluating the prescribed treatment and for feedback analysis of outcome, both in the direction of tumour control and in detection of parameters for estimating and predicting toxicity outcome. The statistical analysis of large amount of clinical data can be slowed by the lack of practice in statistical tools needed, by clinicians, to perform such kind of analysis. This is the reason that lead our working group in the creation of such a tool. Finally an example of clinical application of our software is given for the analysis of the outcome of patients undergoing to radiotherapy for prostate cancer