Imaging of Osteosarcoma: Presenting Findings, Metastatic Patterns, and Features Related to Prognosis.

Background: Osteosarcomas are rare malignancies (<1% of all cancers) that produce an osteoid matrix. Osteosarcomas are the second most frequent type of primary bone tumor after multiple myeloma and the most prevalent primary bone tumor in children. The spectrum of imaging findings of these malignancies varies significantly, reflecting different histological subtypes. For instance, conventional osteosarcoma typically presents with a mixed radiological pattern (lytic and bone mineralization) or with a completely eburneous one; aggressive periosteal reactions such as sunburst, Codman triangle, and soft-tissue components are frequently displayed. On the other hand, telangiectatic osteosarcoma usually presents as a purely lytic lesion with multiple fluid-fluid levels on MRI fluid-sensitive sequences. Other typical and atypical radiological patterns of presentation in other subtypes of osteosarcomas are described in this review. In addition to the characteristics associated with osteosarcoma subtyping, this review article also focuses on imaging features that have been associated with patient outcomes, namely response to chemotherapy and event-free and overall survivals. This includes simple semantic radiological features (such as tumor dimensions, anatomical location with difficulty of radical surgery, occurrence of pathological fractures, and presence of distant metastases), but also quantitative imaging parameters from diffusion-weighted imaging, dynamic contrast-enhanced MRI, and 18F-FDG positron emission tomography and radiomics approaches. Other particular features are described in the text. Overall, this comprehensive literature review aims to be a practical tool for oncologists, pathologists, surgeons, and radiologists involved in these patients' care.

Imaging in France: 2024 Update.

Radiology in France has made major advances in recent years through innovations in research and clinical practice. French institutions have developed innovative imaging techniques and artificial intelligence applications in the field of diagnostic imaging and interventional radiology. These include, but are not limited to, a more precise diagnosis of cancer and other diseases, research in dual-energy and photon-counting computed tomography, new applications of artificial intelligence, and advanced treatments in the field of interventional radiology. This article aims to explore the major research initiatives and technological advances that are shaping the landscape of radiology in France. By highlighting key contributions in diagnostic imaging, artificial intelligence, and interventional radiology, we provide a comprehensive overview of how these innovations are improving patient outcomes, enhancing diagnostic accuracy, and expanding the possibilities for minimally invasive therapies. As the field continues to evolve, France's position at the forefront of radiological research ensures that these innovations will play a central role in addressing current healthcare challenges and improving patient care on a global scale.

Tumor fraction-based prognostic tool for cancer patients referred to early phase clinical trials.

Selecting patients for phase I cancer trials is crucial to ensure a sufficient life expectancy. Frail patients, better suited for palliative care, should not be exposed to new drugs with minimal benefit. Enrolling patients at high risk of early death can jeopardize the study. Our analysis of two large precision medicine studies used tumor fraction from ctDNA to develop a predictive model, demonstrating notable predictive accuracy and aiding in patient selection.

Assessment of large-scale imaging practices in patients with acute brain hemorrhage in French emergency departments: Emergency imaging practices in hemorrhagic stroke.

OBJECTIVE: Intracerebral hemorrhage (ICH) is a life-threatening condition, where imaging plays a crucial role but remains poorly standardized. Our main objective was to analyze the imaging protocols used during the acute phase of ICH and ascertain the proportion of patients diagnosed with secondary hemorrhage. PATIENTS AND METHODS: A multicenter retrospective observational study was conducted across over 100 French hospitals affiliated with a national tele-imaging network dedicated to emergency imaging. Among patients managed in the "Stroke Alert" pathway for suspected acute stroke from March 2021 to April 2023, those with ICH diagnosed within 24 h of symptoms onset were identified. Their imaging reports were reviewed to identify the imaging modality used and protocols performed and investigate whether a secondary cause was identified. RESULTS: Of the 18,356 patients included in the "Stroke Alert" pathway, 662 cerebral hemorrhages were identified (3.6 %). Computed tomography (CT) was the most widely used imaging modality in the acute phase (71.8 % of examinations). Vascular imaging was performed in 78 % of patients with cerebral hemorrhage, most often CT angiography or TOF magnetic resonance angiography. A secondary cause was identified in 8.2 % (54/662) of cerebral hemorrhages, including vascular imaging in the vast majority of cases (92.6 %). CONCLUSION: Optimization and standardization of imaging protocols in the acute phase of ICH is essential to improve the detection of its secondary causes, particularly vascular, requiring urgent treatment. Vascular imaging improves their early detection.

Single- and multi-site radiomics may improve overall survival prediction for patients with metastatic lung adenocarcinoma.

PURPOSE: The purpose of this study was to assess whether single-site and multi-site radiomics could improve the prediction of overall survival (OS) of patients with metastatic lung adenocarcinoma compared to clinicopathological model. MATERIALS AND METHODS: Adults with metastatic lung adenocarcinoma, pretreatment whole-body contrast-enhanced computed tomography examinations, and performance status (WHO-PS) ≤ 2 were included in this retrospective single-center study, and randomly assigned to training and testing cohorts. Radiomics features (RFs) were extracted from all measurable lesions with volume ≥ 1 cm3. Radiomics prognostic scores based on the largest tumor (RPSlargest) and the average RF values across all tumors per patient (RPSaverage) were developed in the training cohort using 5-fold cross-validated LASSO-penalized Cox regression. Intra-patient inter-tumor heterogeneity (IPITH) metrics were calculated to quantify the radiophenotypic dissimilarities among all tumors within each patient. A clinicopathological model was built in the training cohort using stepwise Cox regression and enriched with combinations of RPSaverage, RPSlargest and IPITH. Models were compared with the concordance index in the independent testing cohort. RESULTS: A total of 300 patients (median age: 63.7 years; 40.7% women; median OS, 16.3 months) with 1359 lesions were included (200 and 100 patients in the training and testing cohorts, respectively). The clinicopathological model included WHO-PS = 2 (hazard ratio [HR] = 3.26; P < 0.0001), EGFR, ALK, ROS1 or RET mutations (HR = 0.57; P = 0.0347), IVB stage (HR = 1.65; P = 0.0211), and liver metastases (HR = 1.47; P = 0.0670). In the testing cohort, RPSaverage, RPSlargest and IPITH were associated with OS (HR = 85.50, P = 0.0038; HR = 18.83, P = 0.0082 and HR = 8.00, P = 0.0327, respectively). The highest concordance index was achieved with the combination of clinicopathological variables and RPSaverage, significantly better than that of the clinicopathological model (concordance index = 0.7150 vs. 0.695, respectively; P = 0.0049) CONCLUSION: Single-site and multi-site radiomics-based scores are associated with OS in patients with metastatic lung adenocarcinoma. RPSaverage improves the clinicopathological model.

Enhancing Immunotherapy Response Prediction in Metastatic Lung Adenocarcinoma: Leveraging Shallow and Deep Learning with CT-Based Radiomics across Single and Multiple Tumor Sites.

This study aimed to evaluate the potential of pre-treatment CT-based radiomics features (RFs) derived from single and multiple tumor sites, and state-of-the-art machine-learning survival algorithms, in predicting progression-free survival (PFS) for patients with metastatic lung adenocarcinoma (MLUAD) receiving first-line treatment including immune checkpoint inhibitors (CPIs). To do so, all adults with newly diagnosed MLUAD, pre-treatment contrast-enhanced CT scan, and performance status ≤ 2 who were treated at our cancer center with first-line CPI between November 2016 and November 2022 were included. RFs were extracted from all measurable lesions with a volume ≥ 1 cm3 on the CT scan. To capture intra- and inter-tumor heterogeneity, RFs from the largest tumor of each patient, as well as lowest, highest, and average RF values over all lesions per patient were collected. Intra-patient inter-tumor heterogeneity metrics were calculated to measure the similarity between each patient lesions. After filtering predictors with univariable Cox p < 0.100 and analyzing their correlations, five survival machine-learning algorithms (stepwise Cox regression [SCR], LASSO Cox regression, random survival forests, gradient boosted machine [GBM], and deep learning [Deepsurv]) were trained in 100-times repeated 5-fold cross-validation (rCV) to predict PFS on three inputs: (i) clinicopathological variables, (ii) all radiomics-based and clinicopathological (full input), and (iii) uncorrelated radiomics-based and clinicopathological variables (uncorrelated input). The Models' performances were evaluated using the concordance index (c-index). Overall, 140 patients were included (median age: 62.5 years, 36.4% women). In rCV, the highest c-index was reached with Deepsurv (c-index = 0.631, 95%CI = 0.625-0.647), followed by GBM (c-index = 0.603, 95%CI = 0.557-0.646), significantly outperforming standard SCR whatever its input (c-index range: 0.560-0.570, all p < 0.0001). Thus, single- and multi-site pre-treatment radiomics data provide valuable prognostic information for predicting PFS in MLUAD patients undergoing first-line CPI treatment when analyzed with advanced machine-learning survival algorithms.

Metastatic Lung Adenocarcinomas: Development and Evaluation of Radiomic-Based Methods to Measure Baseline Intra-Patient Inter-Tumor Lesion Heterogeneity.

Radiomics has traditionally focused on individual tumors, often neglecting the integration of metastatic disease, particularly in patients with non-small cell lung cancer. This study sought to examine intra-patient inter-tumor lesion heterogeneity indices using radiomics, exploring their relevance in metastatic lung adenocarcinoma. Consecutive adults newly diagnosed with metastatic lung adenocarcinoma underwent contrast-enhanced CT scans for lesion segmentation and radiomic feature extraction. Three methods were devised to measure distances between tumor lesion profiles within the same patient in radiomic space: centroid to lesion, lesion to lesion, and primitive to lesion, with subsequent calculation of mean, range, and standard deviation of these distances. Associations between HIs, disease control rate, objective response rate to first-line treatment, and overall survival were explored. The study included 167 patients (median age 62.3 years) between 2016 and 2019, divided randomly into experimental (N = 117,546 lesions) and validation (N = 50,232 tumor lesions) cohorts. Patients without disease control/objective response and with poorer survival consistently systematically exhibited values of all heterogeneity indices. Multivariable analyses revealed that the range of primitive-to-lesion distances was associated with disease control in both cohorts and with objective response in the validation cohort. This metrics showed univariable associations with overall survival in the experimental. In conclusion, we proposed original methods to estimate the intra-patient inter-tumor lesion heterogeneity using radiomics that demonstrated correlations with patient outcomes, shedding light on the clinical implications of inter-metastases heterogeneity. This underscores the potential of radiomics in understanding and potentially predicting treatment response and prognosis in metastatic lung adenocarcinoma patients.

Integration of pre-treatment computational radiomics, deep radiomics, and transcriptomics enhances soft-tissue sarcoma patient prognosis.

Our objective was to capture subgroups of soft-tissue sarcoma (STS) using handcraft and deep radiomics approaches to understand their relationship with histopathology, gene-expression profiles, and metastatic relapse-free survival (MFS). We included all consecutive adults with newly diagnosed locally advanced STS (N = 225, 120 men, median age: 62 years) managed at our sarcoma reference center between 2008 and 2020, with contrast-enhanced baseline MRI. After MRI postprocessing, segmentation, and reproducibility assessment, 175 handcrafted radiomics features (h-RFs) were calculated. Convolutional autoencoder neural network (CAE) and half-supervised CAE (HSCAE) were trained in repeated cross-validation on representative contrast-enhanced slices to extract 1024 deep radiomics features (d-RFs). Gene-expression levels were calculated following RNA sequencing (RNAseq) of 110 untreated samples from the same cohort. Unsupervised classifications based on h-RFs, CAE, HSCAE, and RNAseq were built. The h-RFs, CAE, and HSCAE grouping were not associated with the transcriptomics groups but with prognostic radiological features known to correlate with lower survivals and higher grade and SARCULATOR groups (a validated prognostic clinical-histological nomogram). HSCAE and h-RF groups were also associated with MFS in multivariable Cox regressions. Combining HSCAE and transcriptomics groups significantly improved the prognostic performances compared to each group alone, according to the concordance index. The combined radiomic-transcriptomic group with worse MFS was characterized by the up-regulation of 707 genes and 292 genesets related to inflammation, hypoxia, apoptosis, and cell differentiation. Overall, subgroups of STS identified on pre-treatment MRI using handcrafted and deep radiomics were associated with meaningful clinical, histological, and radiological characteristics, and could strengthen the prognostic value of transcriptomics signatures.

Imaging of Spondylodiscitis: A Comprehensive Updated Review-Multimodality Imaging Findings, Differential Diagnosis, and Specific Microorganisms Detection.

Spondylodiscitis is defined by infectious conditions involving the vertebral column. The incidence of the disease has constantly increased over the last decades. Imaging plays a key role in each phase of the disease. Indeed, radiological tools are fundamental in (i) the initial diagnostic recognition of spondylodiscitis, (ii) the differentiation against inflammatory, degenerative, or calcific etiologies, (iii) the disease staging, as well as (iv) to provide clues to orient towards the microorganisms involved. This latter aim can be achieved with a mini-invasive procedure (e.g., CT-guided biopsy) or can be non-invasively supposed by the analysis of the CT, positron emission tomography (PET) CT, or MRI features displayed. Hence, this comprehensive review aims to summarize all the multimodality imaging features of spondylodiscitis. This, with the goal of serving as a reference for Physicians (infectious disease specialists, spine surgeons, radiologists) involved in the care of these patients. Nonetheless, this review article may offer starting points for future research articles.

Are DNA Repair Gene Alterations Associated With the Response to Platinum-Based Regimen and Immune Checkpoint Inhibitors in Patients With Solid Tumors?

We analyzed the antitumor activity of platinum-based chemotherapies and then immune checkpoint inhibitors (ICI) in all-comers patients with solid tumors having a somatic DNA damage repair gene alteration (DDR-GA) identified through a prospective precision medicine study (NCT02534649). Each DDR-GA was classified as pathogenic (Pa), probably pathogenic (PPa), and unknown pathogenicity (UPa) according to OncoKB and ClinVAR databases. Between January 2018 and May 2020, 662 patients were screened. One hundred ninety-nine tumors with DDR-GA were found in 121 (18.3%) patients. Ninety-six patients received platinum-based chemotherapy in the advanced setting. No difference in objective response rate (ORR) under platinum regimen was observed between the 3 DDR-GA groups. The only predictor of worse progression-free survival (PFS) in Cox regression was the existence of a Pa alteration compared to the UPa group: HR = 2.11 (95% CI = 1.2-3.7), P = .009. Forty-eight patients received ICI alone or in combination. We observed a significant trend in better ORR to ICI according to the DDR-GA status: 1/11 (9%) patients in UPa, 5/17 (29.4%) patients in PPa, and 9/20 (45%) patients in Pa (P = .003, Cochran-Armitage trend test), and an increased 6-month PFS probability of 11%, 44%, and 50% in the UPa, PPa, and Pa groups, respectively (P = .37, log-rank test). Overall, somatic pathogenic DDR-GAs were not associated with ORR or PFS to platinum-based chemotherapy in patients with unselected advanced solid tumors. However, DDR-GA seemed to impact ORR and PFS to ICI, paving the way for a therapeutic combination with ICI and molecules targeting the DDR mechanisms, which are currently evaluated in ongoing clinical trials.

Using the Textual Content of Radiological Reports to Detect Emerging Diseases: A Proof-of-Concept Study of COVID-19.

Changes in the content of radiological reports at population level could detect emerging diseases. Herein, we developed a method to quantify similarities in consecutive temporal groupings of radiological reports using natural language processing, and we investigated whether appearance of dissimilarities between consecutive periods correlated with the beginning of the COVID-19 pandemic in France. CT reports from 67,368 consecutive adults across 62 emergency departments throughout France between October 2019 and March 2020 were collected. Reports were vectorized using time frequency-inverse document frequency (TF-IDF) analysis on one-grams. For each successive 2-week period, we performed unsupervised clustering of the reports based on TF-IDF values and partition-around-medoids. Next, we assessed the similarities between this clustering and a clustering from two weeks before according to the average adjusted Rand index (AARI). Statistical analyses included (1) cross-correlation functions (CCFs) with the number of positive SARS-CoV-2 tests and advanced sanitary index for flu syndromes (ASI-flu, from open-source dataset), and (2) linear regressions of time series at different lags to understand the variations of AARI over time. Overall, 13,235 chest CT reports were analyzed. AARI was correlated with ASI-flu at lag = + 1, + 5, and + 6 weeks (P = 0.0454, 0.0121, and 0.0042, respectively) and with SARS-CoV-2 positive tests at lag = - 1 and 0 week (P = 0.0057 and 0.0001, respectively). In the best fit, AARI correlated with the ASI-flu with a lag of 2 weeks (P = 0.0026), SARS-CoV-2-positive tests in the same week (P < 0.0001) and their interaction (P < 0.0001) (adjusted R2 = 0.921). Thus, our method enables the automatic monitoring of changes in radiological reports and could help capturing disease emergence.

Emergency department CT examinations demonstrate no evidence of early viral circulation at the start of the COVID-19 pandemic-a multicentre epidemiological study.

BACKGROUND: Biological studies suggested that the COVID-19 outbreak in France occurred before the first official diagnosis on January 24, 2020. We investigated this controversial topic using a large collection of chest CTs performed throughout French emergency departments within 6 months before the 1st lockdown. RESULTS: Overall, 49,311 consecutive patients (median age: 60 years, 23,636/49,311 [47.9%] women) with available chest CT images and reports from 61 emergency departments between September 1, 2020, and March 16, 2020 (day before the 1st French lockdown), were retrospectively included in this multicentre study. In the macroscopic analysis of reports automatically (labelled for presence of ground glass opacities [GGOs], reticulations, and bilateral and subpleural abnormalities), we found a significant breakpoint on February 17, 2020, for the weekly time series with 1, 2 and ≥ 3 of these 4 radiological features, with 146/49,311 (0.3%) patients showing bilateral abnormalities and ground glass opacities (GGOs) from that day. According to radiologists, 22/146 (15.1%) CT images showed typical characteristics of COVID-19, including 4/146 (2.7%) before February 2020. According to hospital records, one patient remained without microbial diagnosis, two patients had proven influenza A and one patient had concomitant influenza A and mycoplasma infection. CONCLUSION: These results suggest that SARS-CoV-2 was not circulating in the areas covered by the 61 emergency departments involved in our study before the official beginning of the COVID-19 outbreak in France. In emergency patients, the strong resemblance among mycoplasma, influenza A and SARS-CoV-2 lung infections on chest CT and the nonspecificity of CT patterns in low prevalence periods is stressed. CRITICAL RELEVANCE STATEMENT: We proposed here an innovative approach to revisit a controversial 'real' start of the COVID-19 pandemic in France based on (1) a population-level approach combining text mining, time series analysis and an epidemiological dataset and (2) a patient-level approach with careful retrospective reading of chest CT scans complemented by analysis of samples performed contemporarily to the chest CT. We showed no evidence that SARS-CoV-2 was actively circulating in France before February 2020.

Deciphering the correlation between metabolic activity through 18F-FDG-PET/CT and immune landscape in soft-tissue sarcomas: an insight from the NEOSARCOMICS study.

Metabolic elevation in soft-tissue sarcomas (STS), as documented with 18F-Fluorodeoxyglucose positron emission tomography (18F-FDG-PET/CT) has been linked with cell proliferation, higher grade, and lower survivals. However, the recent diagnostic innovations (CINSARC gene-expression signature and tertiary lymphoid structure [TLS]) and therapeutic innovations (immune checkpoint inhibitors [ICIs]) for STS patients underscore the need to re-assess the role of 18F-FDG-PET/CT. Thus, in this correspondence, our objective was to investigate the correlations between STS metabolism as assessed by nuclear imaging, and the immune landscape as estimated by transcriptomics analysis, immunohistochemistry panels, and TLS assessment. Based on a prospective cohort of 85 adult patients with high-grade STS recruited in the NEOSARCOMICS trial (NCT02789384), we identified 3 metabolic groups according to 18F-FDG-PET/CT metrics (metabolic-low [60%], -intermediate [15.3%] and high [24.7%]). We found that T-cells CD8 pathway was significantly enriched in metabolic-high STS. Conversely, several pathways involved in antitumor immune response, cell differentiation and cell cycle, were downregulated in extreme metabolic-low STS. Next, multiplex immunofluorescence showed that densities of CD8+, CD14+, CD45+, CD68+, and c-MAF cells were significantly higher in the metabolic-high group compared to the metabolic-low group. Lastly, no association was found between metabolic group and TLS status. Overall, these results suggest that (i) rapidly proliferating and metabolically active STS can instigate a more robust immune response, thereby attracting immune cells such as T cells and macrophages, and (ii) metabolic activity and TLS could independently influence immune responses.

Clinical, Technical, and MRI Features Associated with Patients' Outcome at 3 Months and 2 Years following Prostate Artery Embolization: Is There an Added Value of Radiomics?

Our aim was to investigate which features were associated with clinical successes at short- and mid-terms following prostate artery embolization (PAE) for symptomatic benign prostate hypertrophy (BPH). All adults treated by PAE for BPH at our referral center between January 2017 and March 2021, with pre-treatment MRI, technical success, and follow-up at 3 months and 2 years were included in this single-center retrospective study. Radiologists reviewed the prostatic protrusion index (PPI), adenomatous dominant BPH (adBPH), and Wasserman classification on pre-treatment MRI. Radiomics analysis was achieved on the transitional zone on pre-treatment T2-weighted imaging (WI) and ADC, and comprised reproducibility assessment, unsupervised classifications, and supervised radiomics scores obtained with cross-validated Elasticnet regressions. Eighty-eight patients were included (median age: 65 years), with 81.8% clinical successes at 3 months and 60.2% at 2 years. No feature was associated with success at 3 months, except the radiomics score trained on T2-WI and ADC (AUROC = 0.694). Regarding success at 2 years, no radiomics approaches provided significant performances; however, Wasserman type-1 and change in international prostate symptom score (IPSS) at 3 months ≤ -35% were associated with success in multivariable analysis (OR = 5.82, p = 0.0296, and OR = 9.04, p = 0.0002). Thus, while radiomics provided limited interest, Wasserman classification and early IPSS changes appeared predictive of mid-term outcomes.

A new comprehensive MRI classification and grading system for lumbosacral central and lateral stenosis: clinical application and comparison with previous systems.

PURPOSE: The purpose of our study was to provide a novel schematized and comprehensive classification of causes and severity grading system for lumbosacral stenosis. MATERIALS AND METHODS: The MRI system proposed consisted of a severity grading scale for central and lateral (recess and foramen) stenosis, together with a schematized indication of the main causes of the disease (disc, arthritis, epidural lipomatosis, and their combinations). The system was applied to a cohort of patients from a single Institution in the last 2-years. Two radiologists evaluated all the MRIs to determine intra- and inter-observer reliability according to Cohen Kappa (Kc, for non-ordered categorical variables) and weighted Kappa (Kw, for ordered variables). Two orthopaedic surgeons clinically evaluated all patients and provided a schematic grading system with a central and lateral stenosis clinical score (CS-CS and LS-CS). Associations between ordinals were tested with chi-square test and measured with the Goodman and Kruskal's gamma index (Gi, with 95% confidence interval [95% CI]). Lastly, the most used previous MRI systems were applied, and their performances were compared to the new system proposed. RESULTS: One hundred and twelve patients were included (55 females-mean age 63.3 ± 10.7 years). An almost perfect intra-observer agreement for the assessment of central stenosis, foramen stenosis, and lateral recess stenosis was found (Kw = 0.929, 0.928, and 0.924, respectively). The inter-observer agreement was almost perfect for central stenosis and foramen stenosis and substantial for lateral recess stenosis (Kw = 0.863, 0.834, and 0.633, respectively). Whatever the aetiologies involved in central and lateral stenosis, the intra-observer agreement was perfect (all Kc = 1), whereas the inter-observer agreements were almost perfect for arthritis (Kc = 0.838) and lipomatosis (Kc = 0.955) and substantial for disc (Kc = 0.691) regarding central stenosis. The inter-observer agreement for the causes of lateral stenosis was lower and variable, ranging from perfect (lipomatosis) to fair (disc, Kc = 0.224). The grading system revealed a strong association with CS-CS for both readers, with GI = 0.671 (95% CI 0.535-0.807) and 0.603 (95% CI = 0.457-0.749), respectively. The association with MRI grading and LS-CS was moderate for foraminal stenosis and for the concomitant presence of foraminal and lateral recess stenosis, with Gi = 0.337 (95% CI 0.121-0.554) and Gi = 0.299 (95% CI 0.098-0.500), respectively. A weak association was found between lateral recess grading alone and LS-CS with Gi = 0.102 (95% CI 0.193-0.397). The new grading systems showed higher Gi for associations with clinical symptoms, compared with previous ones, both for CS-CS and LS-CS. CONCLUSIONS: A standardized visual grading system for lumbar spinal stenosis that takes into account all of the major contributing factors-including disc, arthritis, and lipomatosis, for the central canal, lateral recess, and neural foramina could be a useful and practical tool for defining the stenosis, lowering inter-observer variability, and directing the various treatment options.

Ilio-femoral venous stenting for post-thrombotic syndrome in women of childbearing age: efficacy and impact of pregnancy-a multi-center study by the French Society of Cardiovascular Imaging.

OBJECTIVE: We investigated the efficacy of iliofemoral venous stenting in women of childbearing age treated for post-thrombotic syndrome (PTS) and assessed the influence of pregnancy on stent occlusion. METHODS: A retrospective analysis was conducted on women of childbearing age who underwent endovascular stenting for PTS due to chronic iliocava occlusion across 15 centers from 2009 to 2020. The study assessed pregnancy rates, primary patency rates, secondary patency rates, and clinical efficacy using the Villalta score for PTS severity and the Chronic Venous Disease Quality of Life Questionnaire - version 20 (CIVIQ-20), 6-12 months after the procedure. The impact of pregnancy on stent occlusion was analyzed using classical and multi-state survival analyses. Prophylactic low-molecular-weight heparin or fondaparinux was administered to patients during pregnancy until 6 weeks post-partum. RESULTS: In total, 211 women with PTS underwent endovascular stenting, with a median age of 31 years (range: 16-42). Following recanalization, significant improvements were observed in the Villalta score (p < 0.0001) and the CIVIQ-20 score (p < 0.0001). Thirty-seven (17.6%) women became pregnant and 49 (23.2%) experienced stent occlusions. The 1-year and 5-year occlusion-free survival probabilities were 80.6% (95% confidence interval [CI]: 75.1-86.4%) and 66.6% (95% CI: 57.4-77.4%), respectively. There was no significant association between pregnancy and stent occlusion-free survival (hazard ratio = 1.00 [95% CI: 0.11-8.92], p = 0.9930). CONCLUSION: Iliofemoral venous stenting in women of childbearing age was an effective treatment for post-thrombotic syndrome, and it did not increase the risk for stent occlusion during pregnancy when accompanied by appropriate anticoagulation. CLINICAL RELEVANCE STATEMENT: This study demonstrates that pregnancy following iliofemoral venous stenting for post-thrombotic syndrome does not elevate the risk for stent occlusion. KEY POINTS: • The severity of post-thrombotic syndrome and the quality of life, as measured using the Villalta score and Chronic Venous Disease Quality of Life Questionnaire - version 20, respectively, showed significant improvements 6-12 months after iliofemoral venous stenting. • The occurrence of pregnancy after recanalization in women of childbearing age did not lead to a significant increase in the risk for stent occlusion.

Aneurysmal bone cyst-like changes developed in melorheostosis with epiphyseal osteopoikilosis.

Aneurysmal bone cyst (ABC) is a rare and usually painful condition, representing about 1% of all bone tumors. A geographical lytic, expansile, and septated radiological pattern, with fluid-fluid levels on MRI, is classically displayed. ABC can be a primary bone lesion (70% of patients) or can arise in an underlying condition and is subsequently named "ABC-like changes" (30%). ABC-like changes are more frequently encountered in skeletal segments affected by chondroblastoma, fibrous dysplasia, giant cell tumor, osteoblastoma, non-ossifying fibroma, and osteosarcoma. In this article, we describe the first case of ABC-like changes developed in association with an ultra-rare sclerosing bone disease: melorheostosis. Melorheostosis is characterized by recognizable patterns on radiological studies with a pathological increased bone density and a cortical thickening within the periosteal or endosteal space, usually with a "dripping candle wax" appearance. More rarely, other different radiological patterns can be observed, such as "osteopatia striata-like," "osteoma-like," "myositis ossificans-like," and mixed patterns. Pain and limb hypotrophy are the most common clinical manifestations. We report the case of a Caucasian male with a clinic-radiological diagnosis of melorheostosis (with epiphyseal osteopoikilosis) since the age of twelve. At the age of nineteen, he suffered from increased pain in the proximal right thigh, and the radiological control revealed an expansive septated lesion at the right proximal femoral bone. The diagnosis of ABC-like changes developed in melorheostosis was obtained after CT-guided bone biopsy and confirmed by open-incisional biopsy.

Imaging Features of Alveolar Soft Part Sarcoma: Single Institution Experience and Literature Review.

Alveolar soft part sarcoma (ASPS) is an extremely rare and aggressive soft-tissue sarcoma (STS) subtype with poor prognosis and limited response to radiation therapy and chemotherapy. Prompt recognition and referral to sarcoma centers for appropriate management are crucial for patients' survival. The purpose of this study was to report ASPS pre-treatment imaging features and to examine the existing literature on this topic. Twelve patients (7 women, 5 men-mean age 27.1 ± 10.7 years) were included from our single-center experience. Ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) available were reviewed according to an analysis grid incorporating features from the latest research on STS. Clinical, histological, and outcome data were collected. MRI was available in 10 patients (83.3%), US in 7 patients (58.3%), and CT in 3 patients (25%). Mean longest tumor diameter was 7.6 ± 2.9 cm, and all tumors were deeply seated. Large peritumoral feeding vessels were systematically found and identified on ultrasonography (7/7), MRI (10/10), and CT (3/3). US revealed a well-defined heterogeneous hypoechoic pattern, with abundant flow signals in all patients (7/7). In all patients, MRI showed mildly high signal intensity (SI) on T1-WI and high SI on T2-WI and peritumoral edema. Moreover, flow-voids (due to arteriosus high-flow) into the peritumoral/intratumoral feeding vessels were detected in the MRI fluid-sensitive sequences of all patients. At baseline, whole-body contrast-enhanced CT revealed metastases in 8/12 (66.7%) patients. A pre-treatment longest diameter > 5 cm was significantly associated with distant metastases at diagnosis (p = 0.01). A maximum diameter > 5 cm represents a risk of metastatic disease at diagnosis (odds ratio = 45.0000 (95% CI: 1.4908-1358.3585), p = 0.0285). In the comprehensive literature review, we found 14 articles (case series or original research) focusing on ASPS imaging, with a total of 151 patients included. Merging our experience with the data from the existing literature, we conclude that the hallmark of ASPS imaging at presentation are the following characteristics: deep location, a slight hyperintense MRI SI on T1-WI and a hyperintense SI on T2-WI, numerous MRI flow voids, high internal vascularization, and large peritumoral feeding vessels.

Radiomics and artificial intelligence for soft-tissue sarcomas: Current status and perspectives.

This article proposes a summary of the current status of the research regarding the use of radiomics and artificial intelligence to improve the radiological assessment of patients with soft tissue sarcomas (STS), a heterogeneous group of rare and ubiquitous mesenchymal malignancies. After a first part explaining the principle of radiomics approaches, from raw image post-processing to extraction of radiomics features mined with unsupervised and supervised machine-learning algorithms, and the current research involving deep learning algorithms in STS, especially convolutional neural networks, this review details their main research developments since the formalisation of 'radiomics' in oncologic imaging in 2010. This review focuses on CT and MRI and does not involve ultrasonography. Radiomics and deep radiomics have been successfully applied to develop predictive models to discriminate between benign soft-tissue tumors and STS, to predict the histologic grade (i.e., the most important prognostic marker of STS), the response to neoadjuvant chemotherapy and/or radiotherapy, and the patients' survivals and probability for presenting distant metastases. The main findings, limitations and expectations are discussed for each of these outcomes. Overall, after a first decade of publications emphasizing the potential of radiomics through retrospective proof-of-concept studies, almost all positive but with heterogeneous and often non-replicable methods, radiomics is now at a turning point in order to provide robust demonstrations of its clinical impact through open-science, independent databases, and application of good and standardized practices in radiomics such as those provided by the Image Biomarker Standardization Initiative, without forgetting innovative research paths involving other '-omics' data to better understand the relationships between imaging of STS, gene-expression profiles and tumor microenvironment.