Towards patient-tailored care for soft tissue sarcoma

Over the past few decades, there has been a paradigm shift in cancer research from focusing on the homogeneity within a patient population to emphasizing the diversity or heterogeneity in presentation and clinical outcomes among patients. This concept has been commonly referred to as personalised medicine. The foundation of personalised medicine lies in delivering effective care tailored to each individual patient. In this thesis, we aimed to contribute to a more personalised and patient-tailored approach in the management of patients with soft tissue sarcoma (STS), a rare type of cancer. We achieved this goal by developing and validating different prediction tools and assessing how prediction tools could play a role in the clinical decision making process for STS. The following three main questions were addressed in this thesis:1. PART I: Given the current practice,what is the variation in clinical presentation and oncological outcome of patients with STS? which factors influence this variation in oncological outcome?2. PART II: How to better identify patients at risk and predict oncological outcome in patients with STS?3. PART III: How could prognostic tools play a role in the clinical decision making and management of STS?<br/

Towards patient-tailored care for soft tissue sarcoma

Over the past few decades, there has been a paradigm shift in cancer research from focusing on the homogeneity within a patient population to emphasizing the diversity or heterogeneity in presentation and clinical outcomes among patients. This concept has been commonly referred to as personalised medicine. The foundation of personalised medicine lies in delivering effective care tailored to each individual patient. In this thesis, we aimed to contribute to a more personalised and patient-tailored approach in the management of patients with soft tissue sarcoma (STS), a rare type of cancer. We achieved this goal by developing and validating different prediction tools and assessing how prediction tools could play a role in the clinical decision making process for STS. The following three main questions were addressed in this thesis:1. PART I: Given the current practice,what is the variation in clinical presentation and oncological outcome of patients with STS? which factors influence this variation in oncological outcome?2. PART II: How to better identify patients at risk and predict oncological outcome in patients with STS?3. PART III: How could prognostic tools play a role in the clinical decision making and management of STS?<br/

Experimental study of fire containment using water mist curtains in a reduced-scale deck of a ro-ro ship

Experiments have been conducted to evaluate the containment of smoke and heat using water mist curtains in a model setup of a ro-ro ship's cargo deck with a scale of 1:13, providing practical insights into the application of such fire protection systems in the cargo deck as well as valuable data for future numerical simulations. In this regard, the requirements of the international convention of Safety of Life at Sea (SOLAS) are studied for the side openings of so-called ‘open decks’ in comparison with ‘closed decks’, especially to examine the feasibility of using water mist curtains for creating isolated subdivisions in the ro-ro space as a fire management strategy. The water mist curtains are created with one or two rows of water mist nozzles at pressures ranging from 3 to 8 bar, while the source of smoke and heat is a liquid pool fire, and inert cargo items are used in some experiments. Correspondingly, the interaction between the water mist curtain(s) and the fire is evaluated in terms of its heat release rate, and the containment effect is quantified via measurements of smoke flow through the deck and through the windows, concentrations of gaseous species, as well as gas temperatures at various key locations. The study shows that water mist curtains have a strong effect on fire dynamics and smoke propagation, but containment is dependent on the configuration of side openings and the location of fire, among other important factors

ASO author reflections: towards patient-tailored management of extremity soft tissue sarcoma

Orthopaedics, Trauma Surgery and Rehabilitatio

Preoperative Classification of Peripheral Nerve Sheath Tumors on MRI Using Radiomics

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive soft-tissue tumors prevalent in neurofibromatosis type 1 (NF1) patients, posing a significant risk of metastasis and recurrence. Current magnetic resonance imaging (MRI) imaging lacks decisiveness in distinguishing benign peripheral nerve sheath tumors (BPNSTs) and MPNSTs, necessitating invasive biopsies. This study aims to develop a radiomics model using quantitative imaging features and machine learning to distinguish MPNSTs from BPNSTs. Clinical data and MRIs from MPNST and BPNST patients (2000–2019) were collected at a tertiary sarcoma referral center. Lesions were manually and semi-automatically segmented on MRI scans, and radiomics features were extracted using the Workflow for Optimal Radiomics Classification (WORC) algorithm, employing automated machine learning. The evaluation was conducted using a 100× random-split cross-validation. A total of 35 MPNSTs and 74 BPNSTs were included. The T1-weighted (T1w) MRI radiomics model outperformed others with an area under the curve (AUC) of 0.71. The incorporation of additional MRI scans did not enhance performance. Combining T1w MRI with clinical features achieved an AUC of 0.74. Experienced radiologists achieved AUCs of 0.75 and 0.66, respectively. Radiomics based on T1w MRI scans and clinical features show some ability to distinguish MPNSTs from BPNSTs, potentially aiding in the management of these tumors.</p

Preoperative Classification of Peripheral Nerve Sheath Tumors on MRI Using Radiomics

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive soft-tissue tumors prevalent in neurofibromatosis type 1 (NF1) patients, posing a significant risk of metastasis and recurrence. Current magnetic resonance imaging (MRI) imaging lacks decisiveness in distinguishing benign peripheral nerve sheath tumors (BPNSTs) and MPNSTs, necessitating invasive biopsies. This study aims to develop a radiomics model using quantitative imaging features and machine learning to distinguish MPNSTs from BPNSTs. Clinical data and MRIs from MPNST and BPNST patients (2000–2019) were collected at a tertiary sarcoma referral center. Lesions were manually and semi-automatically segmented on MRI scans, and radiomics features were extracted using the Workflow for Optimal Radiomics Classification (WORC) algorithm, employing automated machine learning. The evaluation was conducted using a 100× random-split cross-validation. A total of 35 MPNSTs and 74 BPNSTs were included. The T1-weighted (T1w) MRI radiomics model outperformed others with an area under the curve (AUC) of 0.71. The incorporation of additional MRI scans did not enhance performance. Combining T1w MRI with clinical features achieved an AUC of 0.74. Experienced radiologists achieved AUCs of 0.75 and 0.66, respectively. Radiomics based on T1w MRI scans and clinical features show some ability to distinguish MPNSTs from BPNSTs, potentially aiding in the management of these tumors.</p

Conocimiento y destrezas iniciales de los alumnos que acceden a cursos introductorios de física en 6 universidades iberoamericanas : cambio a lo largo del primer curso e incidencia en el éxito académi

Este trabajo forma parte de un estudio más extenso, financiado por la AECID, sobre la formación inicial de los alumnos que acceden a cursos de Física en varias universidades iberoamericanas, y de su influencia en el rendimiento académico en el primer curso. La muestra incluye alumnos de las universidades de Alcalá (España), Católica del Norte (Antofagasta, Chile), Santiago (Chile), San Luis (Argentina), San Juan (Argentina) y Tecnológico de Monterrey (México). En primer lugar se ilustra el grado alcanzado en la comprensión de conceptos físicos básicos, en destrezas relevantes para el estudio de la Física y en la capacidad de razonamiento científico. En la segunda parte se muestra como varía la comprensión de los conceptos en el primer año universitario y se analiza mediante un estudio correlacional la influencia de la formación inicial en el éxito académico

Multimodality treatment of undifferentiated pleomorphic soft tissue sarcoma of the extremity (eUPS) in the elderly

Introduction: This subgroup analysis of undifferentiated pleomorphic soft tissue sarcoma of the extremity (eUPS) from the PERSARC collaborative group aimed to achieve a more personalized multimodality treatment approach for primary eUPS in elderly patients. Material and methods: A multicenter retrospective study including primary high-grade eUPS surgically treated with curative intent between 2000 and 2016. Overall survival (OS), local recurrence (LR) and distant metastasis (DM) curves were calculated by Kaplan Meier analysis. Cox proportional hazard models were used to determine the effect of radiotherapy. Results: From a total of 2511 patients with extremity soft tissue sarcoma (eSTS) of the PERSARC study collaborative; 703 patients with eUPS were included in this study. In elderly patients with eUPS 5-year OS, LR and DM were 35.4 (95%CI 29.3–42.8), 17.7 (95%CI 12.7–22.6) and 24.6 (95%CI 19.1–30.1). eUPS was significantly less treated with radiotherapy compared with other eSTS, especially in elderly patients. Patients with R1-R2 margins treated with radiotherapy had about half the risk of developing LR compared with patients treated without radiotherapy (HR = 0.454, p = 0.033). Conclusion: Elderly patients with eUPS were less often treated with radiotherapy and showed higher LR. Nowadays, given an increasing life expectancy in elderly patients, multimodality treatment should be considered