Hypoxia inhibits colonic uptake of the microbiota-generated forms of vitamin B1 via HIF-1α-mediated transcriptional regulation of their transporters.

Hypoxia exerts profound effects on cell physiology, but its effect on colonic uptake of the microbiota-generated forms of vitamin B1 (i.e., thiamin pyrophosphate [TPP] and free thiamine) has not been described. Here, we used human colonic epithelial NCM460 cells and human differentiated colonoid monolayers as in vitro and ex vivo models, respectively, and were subjected to either chamber (1% O2, 5% CO2, and 94% N2) or chemically (desferrioxamine; 250 µM)-induced hypoxia followed by determination of different physiological-molecular parameters. We showed that hypoxia causes significant inhibition in TPP and free thiamin uptake by colonic NCM460 cells and colonoid monolayers; it also caused a significant reduction in the expression of TPP (SLC44A4) and free thiamin (SLC19A2 and SLC19A3) transporters and in activity of their gene promoters. Furthermore, hypoxia caused a significant induction in levels of hypoxia-inducible transcription factor (HIF)-1α but not HIF-2α. Knocking down HIF-1α using gene-specific siRNAs in NCM460 cells maintained under hypoxic conditions, on the other hand, led to a significant reversal in the inhibitory effect of hypoxia on TPP and free thiamin uptake as well as on the expression of their transporters. Finally, a marked reduction in level of expression of the nuclear factors cAMP responsive element-binding protein 1 and gut-enriched Krüppel-like factor 4 (required for activity of SLC44A4 and SLC19A2 promoters, respectively) was observed under hypoxic conditions. In summary, hypoxia causes severe inhibition in colonic TPP and free thiamin uptake that is mediated at least in part via HIF-1α-mediated transcriptional mechanisms affecting their respective transporters.

High frequency of Depressive Disorders and Suicidal Phenomena in Late-Stage Parkinson´s Disease - A Cross-Sectional Study.

BACKGROUND: Depressive disorders (DD) are widely recognized as one of the most frequent neuropsychiatric disorders in Parkinson´s disease. Patients with late-stage Parkinson´s disease (LSPD) continue to be a neglected population, and little is known about DD frequency in LSPD. OBJECTIVES: To determine the frequency of DD in LSPD patients through a clinical diagnostic interview (CDI) and according to diagnostic DSM- 5 criteria. Secondary objectives were to determine the predictive ability of depressive scales to detect DD, to identify potential predictors of DD in LSPD and, to evaluate suicidal phenomena in LSPD. METHODS: A cross-sectional study including LSPD patients (≥7 years from symptom onset and Hoehn and Yahr scale score >3 or a Schwab and England scale score <50% in the ON condition) was conducted. Patients were subjected to psychiatric, neurological, and neuropsychological evaluations. Six depression scales were applied. RESULTS: 92 LSPD patients were included. 59.78% of LSPD patients had a current diagnosis of DD according to CDI, 38.04% patients had a diagnosis of major depressive disorder, and 21.72% non-major depressive disorder. Suicidal ideation was present in 36.96% of patients. All applied scales were able to detect depressive disorders. CONCLUSIONS: More than half of LSPD patients met DD diagnostic criteria and over one-third were diagnosed with major depressive disorder. Overall, the LSPD population seem to have a unique clinical phenotype regarding the frequency and features of DD, whose early identification and treatment could improve the quality of life of patients and caregivers.

CT radiomics models are unable to predict new liver metastasis after successful thermal ablation of colorectal liver metastases.

BACKGROUND: Patients with colorectal liver metastases (CRLM) who undergo thermal ablation are at risk of developing new CRLM after ablation. Identification of these patients might enable individualized treatment. PURPOSE: To investigate whether an existing machine-learning model with radiomics features based on pre-ablation computed tomography (CT) images of patients with colorectal cancer can predict development of new CRLM. MATERIAL AND METHODS: In total, 94 patients with CRLM who were treated with thermal ablation were analyzed. Radiomics features were extracted from the healthy liver parenchyma of CT images in the portal venous phase, before thermal ablation. First, a previously developed radiomics model (Original model) was applied to the entire cohort to predict new CRLM after 6 and 24 months of follow-up. Next, new machine-learning models were developed (Radiomics, Clinical, and Combined), based on radiomics features, clinical features, or a combination of both. RESULTS: The external validation of the Original model reached an area under the curve (AUC) of 0.57 (95% confidence interval [CI]=0.56-0.58) and 0.52 (95% CI=0.51-0.53) for 6 and 24 months of follow-up. The new predictive radiomics models yielded a higher performance at 6 months compared to 24 months. For the prediction of CRLM at 6 months, the Combined model had slightly better performance (AUC=0.60; 95% CI=0.59-0.61) compared to the Radiomics and Clinical models (AUC=0.55-0.57), while all three models had a low performance for the prediction at 24 months (AUC=0.52-0.53). CONCLUSION: Both the Original and newly developed radiomics models were unable to predict new CLRM based on healthy liver parenchyma in patients who will undergo ablation for CRLM.

Cuticular Waxes and Cutin in Terminalia catappa Leaves from the Equatorial São Tomé and Príncipe Islands.

This study presents for the first time an analysis of the content and chemical composition of the cuticular waxes and cutin in the leaves of the widespread and important tropical species Terminalia catappa. The leaves were collected in the equatorial Atlantic islands of São Tomé and Príncipe, in the Gulf of Guinea. The epicuticular and intracuticular waxes were determined via dichloromethane extraction and their chemical composition via GC-MS analysis, and the content and monomeric composition of cutin were determined after depolymerization via methanolysis. The leaves contained an epidermal cuticular coverage of 52.8 µg cm-2 of the cuticular waxes (1.4% of mass) and 63.3 µg cm-2 (1.5% of mass) of cutin. Cuticular waxes include mainly n-alkanols and fatty acids, with a substantial proportion of terpenes in the more easily solubilized fraction, and sterols in the more embedded waxes. Cutin is mostly constituted by C16 fatty acids and dihydroxyacids, also including aromatic monomers, suggesting a largely linear macromolecular arrangement. The high proportion of triacontanol, α-amyrin, ß-amyrin, germanicol, and lupeol in the easily solubilized cuticular fraction may explain the bioactive properties attributed to the T. catappa leaves via the popular medicine, which allows us to consider them as a potential source for the extraction of these compounds.

Enterotoxigenic Escherichia coli Degrades the Host MUC2 Mucin Barrier To Facilitate Critical Pathogen-Enterocyte Interactions in Human Small Intestine.

Enterotoxigenic Escherichia coli (ETEC) isolates are genetically diverse pathological variants of E. coli defined by the production of heat-labile (LT) and/or heat-stable (ST) toxins. ETEC strains are estimated to cause hundreds of millions of cases of diarrheal illness annually. However, it is not clear that all strains are equally equipped to cause disease, and asymptomatic colonization with ETEC is common in low- to middle-income regions lacking basic sanitation and clean water where ETEC are ubiquitous. Recent molecular epidemiology studies have revealed a significant association between strains that produce EatA, a secreted autotransporter protein, and the development of symptomatic infection. Here, we demonstrate that LT stimulates production of MUC2 mucin by goblet cells in human small intestine, enhancing the protective barrier between pathogens and enterocytes. In contrast, using explants of human small intestine as well as small intestinal enteroids, we show that EatA counters this host defense by engaging and degrading the MUC2 mucin barrier to promote bacterial access to target enterocytes and ultimately toxin delivery, suggesting that EatA plays a crucial role in the molecular pathogenesis of ETEC. These findings may inform novel approaches to prevention of acute diarrheal illness as well as the sequelae associated with ETEC and other pathogens that rely on EatA and similar proteases for efficient interaction with their human hosts.

Cutin extraction and composition determined under differing depolymerisation conditions in cork oak leaves.

INTRODUCTION: Cutin is a biopolyester involved in waterproofing aerial plant organs, including leaves. Cutin quantification and compositional profiling require depolymerisation, namely by methanolysis, but specific protocols are not available. OBJECTIVES: Investigate how different methanolysis conditions regarding catalyst concentration effect cutin depolymerisation and monomer release, to better define protocols for cutin content determination and composition profiling. MATERIAL AND METHODS: Cork oak (Quercus suber) dewaxed leaves were reacted with five sodium methoxide (NaOMe) concentrations. Extracts were analysed: glycerol by high-performance liquid chromatography (HPLC) and long-chain lipids by gas chromatography-mass spectrometry (GC-MS). RESULTS: Cutin was completely removed by 3% NaOMe (8.4% of dewaxed leaves), while mild 0.1% and 0.01% NaOMe methanolysis only depolymerised 14% of total cutin. Reactivity of cutin ester bonds is not homogeneous and glyceridic ester bonds are more easily cleaved, releasing the existing glycerol already under the mildest conditions (0.53% with 0.01% NaOMe and 0.41% with 3% NaOMe). The composition of cutin extracts varies with depolymerisation extent, with easier release of alkanoic acids and alkanols, respectively, 34.9% and 8.8% of total monomers at 0.1% NaOMe, while ω-hydroxyacids (49.3% of total monomers) and α,ω-diacids (9.0% of the monomers) are solubilised under more intensive reactive conditions. CONCLUSION: Cutin of Quercus suber leaves is confirmed as a glyceridic polyester of ω-hydroxyacids and alkanoic acids, with minor content of α,ω-diacids, and including coumarate moieties. The protocol for the determination of cutin content and compositional profiling was established regarding catalyst concentration. The molar composition of cutin suggests a macromolecular assembly based on glycerol linked to lipid oligomeric chains with moderate cross-linking.

Effect of chronic alcohol exposure on gut vitamin B7 uptake: involvement of epigenetic mechanisms and effect of alcohol metabolites.

Vitamin B7 (biotin) is essential for normal health and its deficiency/suboptimal levels occur in a variety of conditions including chronic alcoholism. Mammals, including humans, obtain biotin from diet and gut-microbiota via absorption along the intestinal tract. The absorption process is carrier mediated and involves the sodium-dependent multivitamin transporter (SMVT; SLC5A6). We have previously shown that chronic alcohol exposure significantly inhibits intestinal/colonic biotin uptake via suppression of Slc5a6 transcription in animal and cell line models. However, little is known about the transcriptional/epigenetic factors that mediate this suppression. In addition, the effect of alcohol metabolites (generated via alcohol metabolism by gut microbiota and host tissues) on biotin uptake is still unknown. To address these questions, we first demonstrated that chronic alcohol exposure inhibits small intestinal and colonic biotin uptake and SMVT expression in human differentiated enteroid and colonoid monolayers. We then showed that chronic alcohol exposures of both, Caco-2 cells and mice, are associated with a significant suppression in expression of the nuclear factor KLF-4 (needed for Slc5a6 promoter activity), as well as with epigenetic alterations (histone modifications). We also found that chronic exposure of NCM460 human colonic epithelial cells as well as human differentiated colonoid monolayers, to alcohol metabolites (acetaldehyde, ethyl palmitate, ethyl oleate) significantly inhibited biotin uptake and SMVT expression. These findings shed light onto the molecular/epigenetic mechanisms that mediate the inhibitory effect of chronic alcohol exposure on intestinal biotin uptake. They further show that alcohol metabolites are also capable of inhibiting biotin uptake in the gut.NEW & NOTEWORTHY Using complementary models, including human differentiated enteroid and colonoid monolayers, this study shows the involvement of molecular and epigenetic mechanisms in mediating the inhibitory effect of chronic alcohol exposure on biotin uptake along the intestinal tract. The study also shows that alcohol metabolites (generated by gut microbiota and host tissues) cause inhibition in gut biotin uptake.

A distinct neuromelanin magnetic resonance imaging pattern in parkinsonian multiple system atrophy.

BACKGROUND: Parkinsonian variant of multiple system atrophy is a neurodegenerative disorder frequently misdiagnosed as Parkinson's disease. No early imaging biomarkers currently differentiate these disorders. METHODS: Simple visual imaging analysis of the substantia nigra and locus coeruleus in neuromelanin-sensitive magnetic resonance imaging and nigrosome 1 in susceptibility-weighted sequences was performed in thirty patients with parkinsonian variant of multiple system atrophy fulfilling possible/probable second consensus diagnostic criteria. The neuromelanin visual pattern was compared to patients with Parkinson's disease with the same disease duration (n = 10) and healthy controls (n = 10). Substantia nigra semi-automated neuromelanin area/signal intensity was compared to the visual data. RESULTS: Groups were similar in age, sex, disease duration, and levodopa equivalent dose. Hoehn & Yahr stage was higher in parkinsonian multiple system atrophy patients, 69% of whom had normal neuromelanin size/signal, significantly different from Parkinson's disease patients, and similar to controls. Nigrosome 1 signal was lost in 74% of parkinsonian multiple system atrophy patients. Semi-automated neuromelanin substantia nigra signal, but not area, measurements were able to differentiate groups. CONCLUSIONS: In patients with parkinsonism, simple visual magnetic resonance imaging analysis showing normal neuromelanin substantia nigra and locus coeruleus, combined with nigrosome 1 loss, allowed the distinction of the parkinsonian variant of multiple system atrophy from Parkinson's disease and healthy controls. This easy and widely available method was superior to semi-automated measurements in identifying specific imaging changes in substantia nigra and locus coeruleus.

The electroclinical spectrum, etiologies, treatment and outcome of nonconvulsive status epilepticus in the elderly.

BACKGROUND: Nonconvulsive status epilepticus (NCSE) in the elderly is particularly difficult to diagnose, mainly due to subtle clinical manifestations and associated comorbidities. The recently validated electroencephalography (EEG) diagnostic criteria for NCSE and the proposed operational classification of status epilepticus provide tools that can allow an earlier diagnosis and better management of NCSE in this age group, possibly contributing to reduce its high mortality. MATERIAL AND METHODS: we used these tools to identify and characterize a cohort of elderly (>60year-old) patients admitted at our institution in a 3-year period; the video-EEG and clinical files of the patients fulfilling EEG diagnostic criteria for NCSE were reviewed, being in this study described their electroclinical spectrum, etiologies, treatment, inhospital mortality, and status epilepticus severity score (STESS). RESULTS: Fourty patients (23 women; mean age 76.6years) were identified. Although dyscognitive NCSE associated with >2.5Hz of epileptiform discharges (ED) was the most frequent electroclinical phenotype, this was quite heterogeneous, ranging from patients with aura continua to patients in coma, associated with frequent ED or rhythmic slow activities. Acute symptomatic (45%) and multifactorial (27.5%) etiologies were the most common, and associated with the worst prognosis. There was a trend to use newer antiepileptic drugs in the early steps of NCSE treatment. The inhospital mortality was high (22.5%) and predicted by STESS scores ≥3. CONCLUSION: In the elderly, NCSE has heterogeneous electroclinical phenotypes and etiologies. In spite of the treatment limitations conditioned by the comorbidities, more aggressive treatments could be justified to reduce mortality in patients with high STESS scores.

Classification and localization of early-stage Alzheimer's disease in magnetic resonance images using a patch-based classifier ensemble.

INTRODUCTION: Classification methods have been proposed to detect Alzheimer's disease (AD) using magnetic resonance images. Most rely on features such as the shape/volume of brain structures that need to be defined a priori. In this work, we propose a method that does not require either the segmentation of specific brain regions or the nonlinear alignment to a template. Besides classification, we also analyze which brain regions are discriminative between a group of normal controls and a group of AD patients. METHODS: We perform 3D texture analysis using Local Binary Patterns computed at local image patches in the whole brain, combined in a classifier ensemble.We evaluate our method in a publicly available database including very mild-to-mild AD subjects and healthy elderly controls. RESULTS: For the subject cohort including only mild AD subjects, the best results are obtained using a combination of large (30×30×30 and 40×40×40 voxels) patches. A spatial analysis on the best performing patches shows that these are located in the medial-temporal lobe and in the periventricular regions. When very mild AD subjects are included in the dataset, the small (10×10×10 voxels) patches perform best, with the most discriminative ones being located near the left hippocampus. CONCLUSION: We show that our method is able not only to perform accurate classification, but also to localize dis-criminative brain regions, which are in accordance with the medical literature. This is achieved without the need to segment-specific brain structures and without performing nonlinear registration to a template, indicating that the method may be suitable for a clinical implementation that can help to diagnose AD at an earlier stage.

Choosing the right questions - A systematic review of patient reported outcome measures used in radiotherapy and proton beam therapy.

The implementation of PROMs into clinical practice has been shown to improve quality of care. This systematic review aims to identify which PROMs are suitable for implementation within routine clinical practice in a radiotherapy or PBT service.The bibliographic databases MEDLINE, EMBASE and EMCARE were searched. Articles published between 1st January 2008 to 1st June 2023, that reported PROMs being utilised as an outcome measure were included. Inclusion criteria also included being written in English, involving human patients, aged 16 and above, receiving external beam radiotherapy or PBT for six defined tumour sites. PROMs identified within the included articles were subjected to quality assessment using the COSMIN reporting guidelines. Results are reported as per PRISMA guidelines. A total of 268 studies were identified in the search, of which 52 fulfilled the inclusion criteria. The use of 39 different PROMs was reported. The PROMs identified were mostly tumour or site-specific quality of life (n = 23) measures but also included generic cancer (n = 3), health-related quality-of-life (n = 6), and symptom specific (n = 7) measures.None of the PROMs identified received a high GRADE score for good content. There were 13 PROMs that received a moderate GRADE score. The remaining PROMs either had limited evidence of development and validation within the patient cohorts investigated, or lacked relevance or comprehensiveness needed for routine PROMs collection in a radiotherapy or PBT service.This review highlights that there are a wide variety of PROMs being utilised within radiotherapy research, but most lack specificity to radiotherapy side-effects. There is a risk that by using non-specific PROMs in clinical practice, patients might not receive the supportive care that they need.

Deep learning-based tools to distinguish plan-specific from generic deviations in EPID-based in vivo dosimetry.

BACKGROUND: Dose distributions calculated with electronic portal imaging device (EPID)-based in vivo dosimetry (EIVD) differ from planned dose distributions due to generic and plan-specific deviations. Generic deviations are characteristic to a class of plans. Examples include limitations in EIVD dose reconstruction, inaccuracies in treatment planning system (TPS) calculations and systematic machine deviations. Plan-specific deviations have an unpredictable character. Examples include discrepancies between the patient model used for dose calculation and the patient position or anatomy during delivery, random machine deviations, and data transfer, human or software errors. During the inspection work performed with traditional γ-evaluation statistical methods: (i) generic deviations raise alerts that need to be inspected but that rarely lead to action as their root cause is usually understood and (ii) the detection of relevant plan-specific deviations may be hindered by the presence of generic deviations. PURPOSE: To investigate whether deep learning-based tools can help in identifying γ-alerts raised by generic deviations and in improving the detectability of plan-specific deviations. METHODS: A 3D U-Net was trained as an autoencoder to reconstruct underlying patterns of generic deviations in γ-distributions. The network was trained for four treatment disease sites differently affected by generic deviations: volumetric modulated arc therapy (VMAT) lung (no known deviations), VMAT prostate (TPS inaccuracies), VMAT head-and-neck (EIVD limitations) and intensity modulated radiation therapy (IMRT) breast (large EIVD limitations). The network was trained with virtual non-transit γ-distributions: 60 train/10 validation for the VMAT sites and 30 train/10 validation for IMRT breast. It was hypothesized that in vivo γ-distributions obtained in the presence of plan-specific deviations would differ from those seen during training. For each disease site, the sensitivity of γ-analysis and the network to detect (synthetically introduced) patient-related deviations was compared by receiver operator characteristic analysis. The investigated deviations were patient positioning errors, weight gain or loss, and tumor volume changes. The clinical relevance was illustrated qualitatively with 793 in vivo clinical cases (141 lung, 136 head-and-neck, 209 prostate and 307 breast). RESULTS: Error detectability of patient-related deviations was better with the network than with γ-analysis. The average area under the curve values over all sites were 0.86 ± 0.12(1SD) and 0.69 ± 0.25(1SD), respectively. Regarding in vivo clinical results, the percentage of cases differently classified by γ-analysis and the network was 1%, 19%, 18% and 64% for lung, head-and-neck, prostate, and breast, respectively. In head-and-neck and breast cases, 45 γ-only alerts were examined, of which 43 were attributed to EPID dose reconstruction limitations. For prostate, all 15 investigated γ-only alerts were due to known TPS inaccuracies. All 59 investigated network alerts were explained by either patient-related deviations or EPID acquisition incidents. Some patient-related deviations detected by the network were not detected by γ-analysis. CONCLUSIONS: Deep learning-based tools trained to reconstruct underlying patterns of generic deviations in γ-distributions can be used to (i) automatically identify false positives within the set of γ-alerts and (ii) improve the detection of plan-specific deviations, hence minimizing the likelihood of false negatives. The presented method provides clear additional value to the γ-alert management process for large scale EIVD systems.

Insights into cork weathering regarding colour, chemical and cellular changes in view of outdoor applications.

A comprehensive analysis of outdoor weathering and soil burial of cork during 1-year experiments was carried out with measurements of CIELAB color parameters, cellular observations by scanning electron microscopy, and surface chemical features analysed by ATR-FTIR and wet chemical analysis. Cork applied in outdoor conditions above and below ground retained its physical structure and integrity without signs of deterioration or fracturing. The cellular structure was maintained with some small changes at the one-cell layer at the surface, featuring cellular expansion and minute cell wall fractures. Surface color and chemistry showed distinct results for outdoor exposure and soil burial. The weathered cork surfaces acquired a lighter color while the soil buried cork surfaces became darker. With outdoor weathering, the cork polar solubles increased (13.0% vs. 7.6% o.d. mass) while a substantial decrease of lignin occurred (about 28% of the original lignin was removed) leading to a suberin-enriched cork surface. The chemical impact on lignin is therefore responsible for the surface change towards lighter colors. Soil-burial induced hydrolysis of ester bonds of suberin and xylan, and the lignin-enriched cork surface displayed a dark brown color. FTIR and wet chemical results were consistent. Overall cork showed a considerable structural and physical stability that allows its application in outdoor conditions, namely for building façades or other surfacing applications. Architects and designers should take into account the color dynamics of the cork surfaces.

Living with Parkinson's disease in Portugal: Findings from PRISM study.

BACKGROUND: Parkinson's disease (PD) ranks second in global neurodegenerative disorders. The "Parkinson's Real-world Impact assesSMent (PRISM)" study addressed the disease burden and treatment of European PD patients. Yet, the burden on Portuguese PD patients remains unexplored. Here, we outline the demographics, clinical features, and impact of PD in the Portuguese PRISM cohort. METHODS: Descriptive analysis of the PRISM Portuguese cohort (80 patients) was performed, emphasizing socio-demographic data, anti-PD medication usage, PD impact on patients' lives and healthcare resources utilization. RESULTS: The predominant comorbidities in the Portuguese PD cohort (55 % male; mean age 66.2 years; mean disease duration 8.8 years) included depression (26.3 %) and anxiety (26.3 %). Levodopa was the initial prescribed anti-PD medication for 88 % of patients. Among Portuguese PDP, dopamine agonists (DA), monoamine oxidase-B (MAO-B) inhibitors, and catechol-O-methyltransferase (COMT) inhibitors were used by 50 %, 44.4 %, and 18.3 %, respectively. Portuguese PDP experienced impaired quality of life (PDQ-39 score: 31.3 ± 16.8), various non-motor symptoms, namely sadness/blues (65.4 %), urinary urgency (63.5 %), high/low sex interest (57.7 %), while 56 % reported at least one impulse control behavior. Additionally, 30.8 % retired early due to PD and 31.8 % reduced hours in daily activities. Mental health appointments were attended by 31 %, primarily in psychiatry (19 %) and psychology (6 %), and psychotherapy. CONCLUSION: This study uncovers the burden of PD among Portuguese patients, revealing current treatment methods, impact on daily life and healthcare resources employed in Portugal. It emphasizes the need for personalized clinical strategies at national and international levels to improve long-term health outcomes and quality of life of PD patients.

Evaluation of Deep Learning Clinical Target Volumes Auto-Contouring for Magnetic Resonance Imaging-Guided Online Adaptive Treatment of Rectal Cancer.

Purpose: Segmentation of clinical target volumes (CTV) on medical images can be time-consuming and is prone to interobserver variation (IOV). This is a problem for online adaptive radiation therapy, where CTV segmentation must be performed every treatment fraction, leading to longer treatment times and logistic challenges. Deep learning (DL)-based auto-contouring has the potential to speed up CTV contouring, but its current clinical use is limited. One reason for this is that it can be time-consuming to verify the accuracy of CTV contours produced using auto-contouring, and there is a risk of bias being introduced. To be accepted by clinicians, auto-contouring must be trustworthy. Therefore, there is a need for a comprehensive commissioning framework when introducing DL-based auto-contouring in clinical practice. We present such a framework and apply it to an in-house developed DL model for auto-contouring of the CTV in rectal cancer patients treated with MRI-guided online adaptive radiation therapy. Methods and Materials: The framework for evaluating DL-based auto-contouring consisted of 3 steps: (1) Quantitative evaluation of the model's performance and comparison with IOV; (2) Expert observations and corrections; and (3) Evaluation of the impact on expected volumetric target coverage. These steps were performed on independent data sets. The framework was applied to an in-house trained nnU-Net model, using the data of 44 rectal cancer patients treated at our institution. Results: The framework established that the model's performance after expert corrections was comparable to IOV, and although the model introduced a bias, this had no relevant impact on clinical practice. Additionally, we found a substantial time gain without reducing quality as determined by volumetric target coverage. Conclusions: Our framework provides a comprehensive evaluation of the performance and clinical usability of target auto-contouring models. Based on the results, we conclude that the model is eligible for clinical use.

The IMRiS Trial: A Phase 2 Study of Intensity Modulated Radiation Therapy in Extremity Soft Tissue Sarcoma.

PURPOSE: Primary soft tissue sarcoma (STS) is rare, with many tumors occurring in extremities. Local management is limb-sparing surgery and preoperative/postoperative radiation therapy (RT) for patients at high risk of local recurrence. We prospectively investigated late normal tissue toxicity and limb function observed after intensity modulated RT (IMRT) in extremity STS. METHODS AND MATERIALS: Patients with extremity STS, age ≥16 years. Two treatment cohorts: IMRT 50 Gy in 25 × 2 Gy fractions (preoperative) or 60/66 Gy in 30/33 × 2 Gy fractions (postoperative). The primary endpoint was the rate of grade ≥2 late soft tissue fibrosis (subcutaneous tissue) at 24 months after IMRT (Radiation Therapy Oncology Group late radiation morbidity scoring). RESULTS: One hundred sixty-eight patients were registered between March 2016 and July 2017. Of those, 159 (95%) received IMRT (106, 67% preoperative RT; and 53, 33% postoperative RT) with a median follow-up of 35.2 months (IQR, 32.9-36.6); 62% men, median age 58 years. Of 111 patients assessable for the primary endpoint at 24 months, 12 (10.8%; 95% CI, 5.7%-18.1%) had grade ≥2 subcutaneous fibrosis. The overall rate at 24 months of Radiation Therapy Oncology Group late skin, bone, and joint toxicity was 7 of 112 (6.3%), 3 of 112 (2.7%), and 10 of 113 (8.8%), respectively, and for Stern's scale edema was 6 of 113 (5.3%). More wound complications were observed with preoperative than postoperative RT (29.2% vs 3.8%). Overall survival at 24 months was 84.6%, and the local recurrence event rate at 24 months was 10%. CONCLUSIONS: The rate of grade ≥2 subcutaneous fibrosis at 24 months after IMRT was 10.8%, consistent with other recent trials of IMRT and lower than historically reported rates in patients treated with 3-dimensional conformal RT. This trial provides further evidence for the benefits of IMRT in this patient population.

Incorporating patient-specific information for the development of rectal tumor auto-segmentation models for online adaptive magnetic resonance Image-guided radiotherapy.

Background and purpose: In online adaptive magnetic resonance image (MRI)-guided radiotherapy (MRIgRT), manual contouring of rectal tumors on daily images is labor-intensive and time-consuming. Automation of this task is complex due to substantial variation in tumor shape and location between patients. The aim of this work was to investigate different approaches of propagating patient-specific prior information to the online adaptive treatment fractions to improve deep-learning based auto-segmentation of rectal tumors. Materials and methods: 243 T2-weighted MRI scans of 49 rectal cancer patients treated on the 1.5T MR-Linear accelerator (MR-Linac) were utilized to train models to segment rectal tumors. As benchmark, an MRI_only auto-segmentation model was trained. Three approaches of including a patient-specific prior were studied: 1. include the segmentations of fraction 1 as extra input channel for the auto-segmentation of subsequent fractions, 2. fine-tuning of the MRI_only model to fraction 1 (PSF_1) and 3. fine-tuning of the MRI_only model on all earlier fractions (PSF_cumulative). Auto-segmentations were compared to the manual segmentation using geometric similarity metrics. Clinical impact was assessed by evaluating post-treatment target coverage. Results: All patient-specific methods outperformed the MRI_only segmentation approach. Median 95th percentile Hausdorff (95HD) were 22.0 (range: 6.1-76.6) mm for MRI_only segmentation, 9.9 (range: 2.5-38.2) mm for MRI+prior segmentation, 6.4 (range: 2.4-17.8) mm for PSF_1 and 4.8 (range: 1.7-26.9) mm for PSF_cumulative. PSF_cumulative was found to be superior to PSF_1 from fraction 4 onward (p = 0.014). Conclusion: Patient-specific fine-tuning of automatically segmented rectal tumors, using images and segmentations from all previous fractions, yields superior quality compared to other auto-segmentation approaches.

Predicting radiotherapy response, Toxicities and quality-of-life related functional outcomes in soft tissue sarcoma of the extremities (PredicT) using dose-volume constraints development: a study protocol.

INTRODUCTION: Radiotherapy improves local tumour control in patients with soft tissue sarcoma of the extremities (STSE) but it also increases the probability of long-term toxicities such as tissue fibrosis, joint stiffness and lymphoedema. The use of radiation dose and volume thresholds, called dose constraints, may potentially reduce the development of toxicities in STSE. The aim of this study is to determine predictors of radiotherapy-related side effects for STSE. METHODS AND ANALYSIS: Predicting radiotherapy response, Toxicities and quality-of-life related functional outcomes in soft tissue sarcoma of the extremities (PredicT) is a multicentre observational study comprising two cohorts (PredicT A and B). PredicT A, a retrospective analysis of the UK VorteX (NCT00423618) and IMRiS clinical trials (NCT02520128), is aimed at deriving a statistical model for development of dose-volume constraints. This model will use receiving operator characteristics and multivariate analysis to predict radiotherapy side effects and patient-reported outcomes. PredicT B, a prospective cohort study of 150 patients with STSE, is aimed at testing the validity of those dose-volume constraints. PredicT B is open and planned to complete recruitment by September 2024. ETHICS AND DISSEMINATION: PredicT B has received ethical approval from North West - Liverpool Central Research Ethics Committee (20/NW/0267). Participants gave informed consent to participate in the study before taking part. We will disseminate our findings via publications, presentations, national and international conference meetings and engage with local charities. TRIAL REGISTRATION NUMBER: NCT05978024.

RTT advanced practice and how it can change the future of radiotherapy.

The radiation therapy (RT) landscape is continuously evolving, necessitating adaptation in roles and responsibilities of radiation therapists (RTTs). Advanced Practice Radiation Therapists (APRTs) have taken on a proactive role in expanding services and assuming responsibilities within multi-professional teams. A European Society for Radiotherapy and Oncology (ESTRO) brought geographically diverse and experienced RTTs together, to discuss how advanced practice (AP) in the RTT profession should be future-proofed and create a global platform for collaboration. Challenges in achieving consensus and standardisation of APRT was identified across jurisdictions, emphasising the importance of international collaboration. Whilst highlighting the pivotal role of APRTs in driving innovation, improving patient care, and navigating the complexities of modern RT practice, this position paper presents outcomes and recommendations from the workshop. Discussions highlighted the need for standardised role definitions, education frameworks, regulatory support, and career development pathways to enable the advancement of APRT effectively. Increasing networks and collaboration is recommended to ensure APRTs can shape the future of RT.