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Purpose: To evaluate deep learning (DL)-based deformable image registration (DIR) for dose accumulation during radiotherapy of prostate cancer patients.Methods and materials: Data including 341 CBCTs (209 daily, 132 weekly) and 23 planning CTs from 23 patients was retrospectively analyzed. Anatomical deformation during treatment was estimated using free-form deformation (FFD) method from Elastix and DL-based VoxelMorph approaches. The VoxelMorph method was investigated using anatomical scans (VMorph_Sc) or label images (VMorph_Msk), or the combination of both (VMorph_Sc_Msk). Accumulated doses were compared with the planning dose.Results: The DSC ranges, averaged for prostate, rectum and bladder, were 0.60-0.71, 0.67-0.79, 0.93-0.98, and 0.89-0.96 for the FFD, VMorph_Sc, VMorph_Msk, and VMorph_Sc_Msk methods, respectively. When including both anatomical and label images, VoxelMorph estimated more complex deformations resulting in heterogeneous determinant of Jacobian and higher percentage of deformation vector field (DVF) folding (up to a mean value of 1.90% in the prostate). Large differences were observed between DL-based methods regarding estimation of the accumulated dose, showing systematic overdosage and underdosage of the bladder and rectum, respectively. The difference between planned mean dose and accumulated mean dose with VMorph_Sc_Msk reached a median value of +6.3 Gy for the bladder and -5.1 Gy for the rectum.Conclusion: The estimation of the deformations using DL-based approach is feasible for male pelvic anatomy but requires the inclusion of anatomical contours to improve organ correspondence. High variability in the estimation of the accumulated dose depending on the deformable strategy suggests further investigation of DL-based techniques before clinical deployment.

STUDY OBJECTIVES: To assess the responsiveness of the Idiopathic Hypersomnia Severity Scale (IHSS) to medications and estimate the minimum clinically important difference, to report clinically relevant score ranges, and to confirm its psychometric properties and whether items need to be weighted in drug-free and treated patients with idiopathic hypersomnia (IH). METHODS: Two-hundred twenty-six (166 drug-free and 60 treated) patients with IH (cross-sectional sample) completed the 14-item IHSS to quantify the severity of the 3 major IH symptoms (excessive daytime sleepiness, prolonged nighttime sleep, and sleep inertia) and consequences; 77 untreated patients were evaluated again after treatment (longitudinal sample). Patients filled in the Epworth Sleepiness Scale, Beck Depression Inventory II, and European Quality of Life questionnaires. RESULTS: The IHSS confirmed adequate psychometric properties with a factor analysis indicating a 3-component solution. IHSS total score was lower in treated than untreated patients, with a mean difference of 4–5 points in the cross-sectional and longitudinal samples. Distribution-based methods were used to estimate that 4 points represented the minimum clinically important difference. Four severity levels were defined with between-group differences related to treatment. The probability of having severe sleepiness, depressive symptoms, and low quality of life increased with the severity level. Our results showed that IHSS item-weighting was not necessary. CONCLUSIONS: The IHSS is a valid and reliable tool to quantify IH symptoms, with 4 severity score levels of clinical importance. The IHSS has adequate psychometric properties and can detect symptom changes after treatment. These findings should stimulate its use in clinical settings and in research studies. CITATION: Rassu AL, Evangelista E, Barateau L, et al. Idiopathic Hypersomnia Severity Scale to better quantify symptoms severity and their consequences in idiopathic hypersomnia. J Clin Sleep Med. 2022;18(2):617–629.

The diversity of vaccination modalities and infection history are both variables that have an impact on the immune memory of individuals vaccinated against SARS-CoV-2. To gain more accurate knowledge of how these parameters imprint on immune memory, we conducted a long-term follow-up of SARS-CoV-2 spike protein–specific immune memory in unvaccinated and vaccinated COVID-19 convalescent individuals as well as in infection-naïve vaccinated individuals. Here, we report that individuals from the convalescent vaccinated (hybrid immunity) group have the highest concentrations of spike protein–specific antibodies at 6 months after vaccination. As compared with infection-naïve vaccinated individuals, they also display increased frequencies of an atypical mucosa-targeted memory B cell subset. These individuals also exhibited enhanced T H 1 polarization of their SARS-CoV-2 spike protein–specific follicular T helper cell pool. Together, our data suggest that prior SARS-CoV-2 infection increases the titers of SARS-CoV-2 spike protein–specific antibody responses elicited by subsequent vaccination and induces modifications in the composition of the spike protein–specific memory B cell pool that are compatible with enhanced functional protection at mucosal sites.

Objective. Plan-of-the-day (PoD) adaptive radiation therapy (ART) is based on a library of treatment plans, among which, at each treatment fraction, the PoD is selected using daily images. However, this strategy is limited by PoD selection uncertainties. This work aimed to propose and evaluate a workflow to automatically and quantitatively identify the PoD for cervix cancer ART based on daily CBCT images. Approach. The quantification was based on the segmentation of the main structures of interest in the CBCT images (clinical target volume [CTV], rectum, bladder, and bowel bag) using a deep learning model. Then, the PoD was selected from the treatment plan library according to the geometrical coverage of the CTV. For the evaluation, the resulting PoD was compared to the one obtained considering reference CBCT delineations. Main results. In experiments on a database of 23 patients with 272 CBCT images, the proposed method obtained an agreement between the reference PoD and the automatically identified PoD for 91.5% of treatment fractions (99.6% when considering a 5% margin on CTV coverage). Significance. The proposed automatic workflow automatically selected PoD for ART using deep-learning methods. The results showed the ability of the proposed process to identify the optimal PoD in a treatment plan library.

Background and ObjectivesNarcolepsy type 1 (NT1) is an orphan brain disorder caused by the irreversible destruction of orexin neurons. Metabolic disturbances are common in patients with NT1 who have a body mass index (BMI) 10% to 20% higher than the general population, with one-third being obese (BMI >30 kg/m2). Besides the destruction of orexin neurons in NT1, the metabolic alterations in obese and nonobese patients with NT1 remain unknown. The aim of this study was to identify possible differences in plasma metabolic profiles between patients with NT1 and controls as a function of their BMI status.MethodsWe used a targeted liquid chromatography–mass spectrometry metabolomics approach to measure 141 circulating, low-molecular-weight metabolites in drug-free fasted plasma samples from 117 patients with NT1 (including 41 obese individuals) compared with 116 BMI-matched controls (including 57 obese individuals).ResultsCommon metabolites driving the difference between patients with NT1 and controls, regardless of BMI, were identified, namely sarcosine, glutamate, nonaylcarnitine (C9), 5 long-chain lysophosphatidylcholine acyls, 1 sphingolipid, 12 phosphatidylcholine diacyls, and 11 phosphatidylcholine acyl-akyls, all showing increased concentrations in NT1. Metabolite concentrations significantly affected by NT1 (n = 42) and BMI category (n = 40) showed little overlap (n = 5). Quantitative enrichment analysis revealed common metabolic pathways that were implicated in the NT1/control differences in both normal BMI and obese comparisons, namely glycine and serine, arachidonic acid, and tryptophan metabolism. The metabolites driving these differences were glutamate, sarcosine, and ornithine (glycine and serine metabolism); glutamate and PC aa C34:4 (arachidonic acid metabolism); and glutamate, serotonin, and tryptophan (tryptophan metabolism). Linear metabolite-endophenotype regression analyses highlight that as part of the NT1 metabolic phenotype, most of the relationships between the sleep parameters (i.e., slow-wave sleep duration, sleep latency, and periodic leg movement) and metabolite concentrations seen in the controls were lost.DiscussionThese results represent the most comprehensive metabolic profiling of patients with NT1 as a function of BMI and propose some metabolic diagnostic biomarkers for NT1, namely glutamate, sarcosine, serotonin, tryptophan, nonaylcarnitine, and some phosphatidylcholines. The metabolic pathways identified offer, if confirmed, possible targets for treatment of obesity in NT1.Classification of EvidenceThis study provides Class II evidence that a distinct metabolic profile can differentiate patients with NT1 from patients without the disorder.

Following severe adverse reactions to the AstraZeneca ChAdOx1-S-nCoV-19 vaccine1,2, European health authorities have recommended that patients under the age of 55 who received one dose of ChAdOx1-S-nCoV-19 vaccine receive a second dose of Pfizer BNT162b2 vaccine as a booster. However, the effectiveness and the immunogenicity of this vaccination regimen have not been formally tested. Here, we show that the heterologous ChAdOx1-S-nCoV-19/BNT162b2 combination confers better protection against Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection than the homologous BNT162b2/BNT162b2 combination in a real-world observational study of healthcare workers (n=13121). To understand the underlying mechanism, we conducted a longitudinal survey of the anti-spike immunity conferred by each vaccine combination. Both combinations induced strong anti-spike antibody (Ab) responses but sera from heterologous vaccinated individuals displayed a stronger neutralizing activity, regardless of the SARS-CoV-2 variant. This enhanced neutralizing potential was correlated with increased frequencies of switched and activated memory B cells recognizing the SARS-CoV-2 Receptor Binding Domain (RBD). The ChAdOx1-S-nCoV-19 vaccine induced a weaker IgG response but a stronger T cell response than the BNT162b2 vaccine after the priming dose, which could explain the complementarity of both vaccines when used in combination. The heterologous vaccination regimen could therefore be particularly suitable for immune compromised individuals.

Despite progress in the prevention of pressure injuries (PIs), they remain a challenging public health problem because of their frequency and morbidity. Protection of the skin by multilayer silicone foam dressings may be an adjuvant measure to prevent PIs in high-risk patients. Despite the available clinical data and published recommendations on this measure, caregivers face difficulties in identifying patients who would benefit from this adjuvant measure. The objective of this work was to define the profiles of high-risk patients who would benefit optimally from this measure in combination with basic preventive procedures. This consensual expert opinion was drawn up using two methods: the Nominal Group Technique with eight medical and paramedical experts, and the Delphi process with 16 experts. The bases for this expert consensual opinion were a formal search and analysis of the published literature regarding evidence on the prevention of PIs using multilayer silicone foam dressings. The consensual expert opinion reported here addresses five proposals mostly intended to define patients who would benefit from the use of a multilayer silicone foam dressing (≥4 layers) to prevent PIs (sacrum and heels).

Symptoms of restless legs syndrome are relieved by movement. Whether a cognitive task decreases sensory discomfort remains understudied. We aimed to assess the frequency of patients with restless legs syndrome who report decreased sensory discomfort during cognitive activities, and quantify this decrease during a cognitive task. Three-hundred and fifty-eight consecutive adults with restless legs syndrome (age 55.17 ± 14.62 years; 55.87% women; 27.65% treated) answered the question: "Does the intensity of your restless legs syndrome symptoms decrease when you perform activities other than moving your legs?" rated on a nine-point Likert scale (from fully-agree to totally-disagree). A subgroup of 65 consecutive drug-free patients underwent an 80-min suggested immobilisation test at 20:00 hours to quantify legs discomfort on a visual analogue scale before polysomnography, including 40 patients performing a cognitive task (balloon analogue risk task) from the 60 to 80 min. A total of 130 (36.3%) patients reported a decrease, 158 (44.1%) no decrease, and 70 (19.5%) uncertain changes in severity of restless legs syndrome symptoms during cognitive activities, with a similar proportion whether treated or not. Patients experiencing a decrease had less severe restless legs syndrome symptoms. In the suggested immobilisation test, mixed-effect regression models showed that legs discomfort decreased in patients performing the cognitive task while it continued to increase in those without task, with a larger difference in patients reporting a self-reported decrease in restless legs syndrome during cognitive activities. In conclusion, one-third of patients reported a self-reported decrease of restless legs syndrome symptoms during cognitive activities, this improvement in restless legs syndrome was confirmed during a sustained cognitive task. Cognitive strategies could be implemented for the management of restless legs syndrome.

International audience

International audience; PURPOSE: The first aim was to generate and compare synthetic-CT (sCT) images using a conditional generative adversarial network (cGAN) method (Pix2Pix) for MRI-only prostate radiotherapy planning by testing several generators, loss functions, and hyper-parameters. The second aim was to compare the optimized Pix2Pix model with five other architectures (bulk-density, atlas-based, patch-based, U-Net, and GAN). METHODS: For 39 patients treated by VMAT for prostate cancer, T2-weighted MRI images were acquired in addition to CT images for treatment planning. sCT images were generated using the Pix2Pix model. The generator, loss function, and hyper-parameters were tuned to improve sCT image generation (in terms of imaging endpoints). The final evaluation was performed by 3-fold cross-validation. This method was compared to five other methods using the following imaging endpoints: the mean absolute error (MAE) and mean error (ME) between sCT and reference CT images (rCT) of the whole pelvis, bones, prostate, bladder, and rectum. For dose planning analysis, the dose-volume histogram metric differences and 3D gamma analysis (local, 1 %/1 mm) were calculated using the sCT and reference CT images. RESULTS: Compared with the other architectures, Pix2Pix with Perceptual loss function and generator ResNet 9 blocks showed the lowest MAE (29.5, 107.7, 16.0, 13.4, and 49.1 HU for the whole pelvis, bones, prostate, bladder, and rectum, respectively) and the highest gamma passing rates (99.4 %, using the 1 %/1mm and 10 % dose threshold criterion). Concerning the DVH points, the mean errors were -0.2% for the planning target volume V(95%), 0.1 % for the rectum V(70Gy), and -0.1 % for the bladder V(50Gy). CONCLUSION: The sCT images generated from MRI data with the Pix2Pix architecture had the lowest image errors and similar dose uncertainties (in term of gamma pass-rate and dose-volume histogram metric differences) than other deep learning methods.

National audience; During the joint SFRO/SFPM session of the 2019 congress, a state of the art of adaptive radiotherapy announced a strong impact in our clinical practice, in particular with the availability of treatment devices coupled to an MRI system. Three years later, it seems relevant to take stock of adaptive radiotherapy in practice, and especially the “online” strategy because it is indeed more and more accessible with recent hardware and software developments, such as coupled accelerators to a three-dimensional imaging device and algorithms based on artificial intelligence. However, the deployment of this promising strategy is complex because it contracts the usual time scale and upsets the usual organizations. So what do we need to deliver adapted treatment plans with an “online” strategy?