Evaluation of different algorithms for automatic segmentation of head-and-neck lymph nodes on CT images.

Purpose: To investigate the performance of 4 atlas-based (multi-ABAS) and 2 deep learning (DL) solutions for head-and-neck (HN) elective nodes (CTVn) automatic segmentation (AS) on CT images.

Material And Methods: Bilateral CTVn levels of 69 HN cancer patients were delineated on contrast-enhanced planning CT. Ten and 49 patients were used for atlas library and for training a mono-centric DL model, respectively.

Pseudocystic inflammatory demyelinating lesions in multiple sclerosis: A clinical, radiological, and pathological description.

Background: Pseudocystic inflammatory demyelinating lesions (PIDLs) are poorly described in MS and might represent a diagnostic challenge.

Objectives: We described the clinical, radiological, pathological, and follow-up characteristics of 13 PIDL in 9 MS patients.

Methods: We constituted a single-center retrospective case series of PIDLs in MS, defined on MRI as expansive cyst-like lesions, with a fluid-signal content, and a diameter of 1 cm or more.

A simplified mesoscale 3D model for characterizing fibrinolysis under flow conditions.

One of the routine clinical treatments to eliminate ischemic stroke thrombi is injecting a biochemical product into the patient's bloodstream, which breaks down the thrombi's fibrin fibers: intravenous or intravascular thrombolysis. However, this procedure is not without risk for the patient; the worst circumstances can cause a brain hemorrhage or embolism that can be fatal. Improvement in patient management drastically reduced these risks, and patients who benefited from thrombolysis soon after the onset of the stroke have a significantly better 3-month prognosis, but treatment success is highly variable.

Deep-learning predicted PET can be subtracted from the true clinical fluorodeoxyglucose PET co-registered to MRI to identify the epileptogenic zone in focal epilepsy.

Objective: Normal interictal [ F]FDG-PET can be predicted from the corresponding T1w MRI with Generative Adversarial Networks (GANs). A technique we call SIPCOM (Subtraction Interictal PET Co-registered to MRI) can then be used to compare epilepsy patients' predicted and clinical PET. We assessed the ability of SIPCOM to identify the Resection Zone (RZ) in patients with drug-resistant epilepsy (DRE) with reference to visual and statistical parametric mapping (SPM) analysis.

MD-SGT: Multi-dilation spherical graph transformer for unsupervised medical image registration.

Deformable medical image registration is an essential preprocess step for several clinical applications. Even though the existing convolutional neural network and transformer based methods achieved the promising results, the limited long-range spatial dependence and non-uniform attention span of these models prohibit further improving the registration performance. To deal with this issue, we proposed a multi-dilation spherical graph transformer (MD-SGT), in which the encoder combined the advantages of convolutional and graph transformer blocks to distinguish effectively the differences between the reference and the template images at various scales.

Insights on the carbon footprint of radiotherapy in France.

The French healthcare system is responsible for 8% of the national footprint. Achieving a net zero emissions scenario will require a 4-5 fold decrease of carbon emissions in the coming years. The carbon footprint of radiation therapy has not been specifically studied to date.

Limited applicability and implementation of the international oncology treatments guidelines in low- and middle-income countries, an example from the Mediterranean area borders.

The quality of cancer care in the modern era is based on a precise diagnosis and personalized therapy according to patients and their disease based on validated guidelines with a high level of evidence. During cancer patients' management, the objective is first to make an accurate diagnosis and then offer the best treatment, validated beforehand in a multidisciplinary board meeting, with the best benefit/risk ratio. In the context of many low- and middle-income countries, the limited available means do not allow an adequate offer, resulting in non-optimal patients' care.

Modeling and hexahedral meshing of cerebral arterial networks from centerlines.

Computational fluid dynamics (CFD) simulation provides valuable information on blood flow from the vascular geometry. However, it requires extracting precise models of arteries from low-resolution medical images, which remains challenging. Centerline-based representation is widely used to model large vascular networks with small vessels, as it encodes both the geometric and topological information and facilitates manual editing.

Quantification of short echo time MRS signals with improved version of QUantitation based on quantum ESTimation algorithm.

Magnetic resonance spectroscopy offers information about metabolite changes in the organism, which can be used in diagnosis. While short echo time proton spectra exhibit more distinguishable metabolites compared with proton spectra acquired with long echo times, their quantification (and providing estimates of metabolite concentrations) is more challenging. They are hampered by a background signal, which originates mainly from macromolecules (MM) and mobile lipids.

Characterization of Breast Tumors from MR Images Using Radiomics and Machine Learning Approaches.

Determining histological subtypes, such as invasive ductal and invasive lobular carcinomas (IDCs and ILCs) and immunohistochemical markers, such as estrogen response (ER), progesterone response (PR), and the HER2 protein status is important in planning breast cancer treatment. MRI-based radiomic analysis is emerging as a non-invasive substitute for biopsy to determine these signatures. We explore the effectiveness of radiomics-based and CNN (convolutional neural network)-based classification models to this end.

Radiomics combined with transcriptomics to predict response to immunotherapy from patients treated with PD-1/PD-L1 inhibitors for advanced NSCLC.

Introduction: In this study, we aim to build radiomics and multiomics models based on transcriptomics and radiomics to predict the response from patients treated with the PD-L1 inhibitor.

Materials And Methods: One hundred and ninety-five patients treated with PD-1/PD-L1 inhibitors were included. For all patients, 342 radiomic features were extracted from pretreatment computed tomography scans.

Intraoperative identification of functional brain areas with RGB imaging using statistical parametric mapping: Simulation and clinical studies.

Complementary technique to preoperative fMRI and electrical brain stimulation (EBS) for glioma resection could improve dramatically the surgical procedure and patient care. Intraoperative RGB optical imaging is a technique for localizing functional areas of the human cerebral cortex that can be used during neurosurgical procedures. However, it still lacks robustness to be used with neurosurgical microscopes as a clinical standard.

Therapeutic potential of extracellular vesicles derived from cardiac progenitor cells in rodent models of chemotherapy-induced cardiomyopathy.

Background: Current treatments of chemotherapy-induced cardiomyopathy (CCM) are of limited efficacy. We assessed whether repeated intravenous injections of human extracellular vesicles from cardiac progenitor cells (EV-CPC) could represent a new therapeutic option and whether EV manufacturing according to a Good Manufacturing Practices (GMP)-compatible process did not impair their bioactivity.

Methods: Immuno-competent mice received intra-peritoneal injections (IP) of doxorubicin (DOX) (4 mg/kg each; cumulative dose: 12 mg/kg) and were then intravenously (IV) injected three times with EV-CPC (total dose: 30 billion).

Equal parallel and cone-beam projections: a curious property of D-symmetric object functions.

In tomographic image reconstruction, the object density function is the unknown quantity whose projections are measured by the scanner. In the three-dimensional case, we define the D-reflection of such a density function as the object obtained by a particular weighted reflection about the plane=, and a D-symmetric function as one whose D-reflection is equal to itself. D-symmetric object functions have the curious property that their parallel projection onto the detector plane=is equal to their cone-beam projection onto the same detector with x-ray source location at the origin.

Systematic Review on Learning-based Spectral CT.

Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main forms: dual-energy computed tomography (DECT) and photon-counting computed tomography (PCCT), which offer image improvement, material decomposition, and feature quantification relative to conventional CT. However, the inherent challenges of spectral CT, evidenced by data and image artifacts, remain a bottleneck for clinical applications.

Ultra-low tidal volume ventilation for COVID-19-related ARDS in France (VT4COVID): a multicentre, open-label, parallel-group, randomised trial.

Background: COVID-19-related acute respiratory distress syndrome (ARDS) is associated with a high mortality rate and longer mechanical ventilation. We aimed to assess the effectiveness of ventilation with ultra-low tidal volume (ULTV) compared with low tidal volume (LTV) in patients with COVID-19-related ARDS.

Methods: This study was a multicentre, open-label, parallel-group, randomised trial conducted in ten intensive care units in France.

The biological sample collection of the OFSEP French MS registry: An essential tool dedicated to researchers.

Today's medicine strives to be personalized, preventive, predictive and participatory. This implies to have access to multimodal data to better characterize patients groups and to combine clinical and imaging data with high-quality biological samples. Collecting such data is one of the objectives of the Observatoire français de la sclérose en plaques (OFSEP), the French MS registry.

Peripheral but not axial muscle mass is associated with early mortality in bone metastatic lung cancer patients at diagnosis.

Objectives: Identification of sarcopenia is a key issue in oncology. Several methods may be used to evaluate muscle mass in patients. Routine cancer follow-up computed tomography (CT) provides axial muscle mass whereas whole-body densitometry (DEXA) measures appendicular lean mass (ALM).

Feeling without localizing: exploring tactile misperception in a patient with uncommon parietal left brain damage.

Introduction: We report a very unique clinical presentation of a patient who complained, after a left parietal brain damage, about feeling tactile stimulations on his right upper limb without being able to localize them.

Methods: Using a single case study approach, we report three experiments relying on several custom-made tasks to explore the different levels of somatosensory information processing, ranging from somato-sensation to somato-representation.

Results: Our results showed a preserved ability to localize tactile stimuli applied on the right upper limb when using pointing responses while the ability to localize was less efficient when having to name the stimulated part (akin Numbsense).

Intramuscular capillary-type hemangioma: Diagnosis, treatment, and outcomes. A French multicentric retrospective study of 66 cases.

Purpose: Intramuscular capillary-type hemangiomas (ICTHs) are rare entities, belonging to the group of intramuscular "hemangiomas." The diagnosis remains challenging. We aimed to assess the diagnostic criteria, treatments and outcomes of ICTHs.

Quantification of cartilage and subchondral bone cysts on knee specimens based on a spectral photon-counting computed tomography.

Spectral photon-counting computed tomography (SPCCT) is a new technique with the capability to provide mono-energetic (monoE) images with high signal to noise ratio. We demonstrate the feasibility of SPCCT to characterize at the same time cartilage and subchondral bone cysts (SBCs) without contrast agent in osteoarthritis (OA). To achieve this goal, 10 human knee specimens (6 normal and 4 with OA) were imaged with a clinical prototype SPCCT.