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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

What is the benefit of gadolinium-chelate injection for the diagnosis of local recurrence of clear cell renal cell carcinoma after percutaneous thermal ablation with MRI?

PURPOSE: The purpose of this study was to compare the diagnostic capabilities of contrast-enhanced (CE)-MRI to those of non-CE-MRI to diagnose local recurrence of clear cell renal cell carcinoma (ccRCC) after percutaneous thermal ablation (TA). MATERIALS AND METHODS: This institutional, review board-approved, case-control, single-center retrospective study included all consecutive adult patients with at least two post-TA MRIs showing local recurrence of ccRCC after TA validated by multidisciplinary board. 'Control' patients without recurrence were randomly-selected with a case:control ratio of 2/3. Four senior radiologists reviewed in a double-blinded fashion non-CE sequences of last two consecutive MRI examinations (non-CE-MRIs), assessed the presence of recurrence of ccRCC, then reviewed the CE sequences (CE-MRI) and determined again the presence of a recurrence. Area under the receiver operating characteristic curve (AUROC), sensitivity, specificity and accuracy were compared for each reader for non-CE-MRI and CE-MRI. RESULTS: Fifty-one patients (41 men; mean age, 77.5 years) who underwent percutaneous TA for ccRCC were included. There were a total of 21 recurrences and 35 scars. Whoever the reader, AUROC was not significantly different (mean, 0.86 with-CE-MRI vs. 0.81 with non-CE-MRI; P values ranging between 0.08 and 0.98), neither sensitivity (mean, 76.2% with CE-MRI vs. 71.4% with non-CE-MRI; P values ranging between 0.06 and >0.99), nor accuracy (85.8% with CE-MRI vs. 80.8% with non-CE-MRI; P values ranging between 0.07 and >0.99). Change in specificity depended on the reader with a significant increase for one reader (+20%; P = 0.02) and a significant decrease for another reader (-17.2%; P = 0.03). CONCLUSION: Non-CE MRI has good diagnostic performance for the follow-up of patients with ccRCC treated using percutaneous TA, questioning the systematic use of GBCA injection.

Radiofrequency ablation of lung metastases of colorectal cancer: could early radiomics analysis of the ablation zone help detect local tumor progression?

OBJECTIVES: To determine whether radiomics data can predict local tumor progression (LTP) following radiofrequency ablation (RFA) of colorectal cancer (CRC) lung metastases on the first revaluation chest CT. METHODS: This case-control single-center retrospective study included 95 distinct lung metastases treated by RFA (in 39 patients, median age: 63.1 years) with a contrast-enhanced CT-scan performed 3 months after RFA. Forty-eight radiomics features (RFs) were extracted from the 3D-segmentation of the ablation zone. Several supervised machine-learning algorithms were trained in 10-fold cross-validation on reproducible RFs to predict LTP, with/without denoising CT-scans. An unsupervised classification based on reproducible RFs was built with k-means algorithm. RESULTS: There were 20/95 (26.7%) relapses within a median delay of 10 months. The best model was a stepwise logistic regression on raw CT-scans. Its cross-validated performances were: AUROC = 0.72 (0.58-0.86), area under the Precision-Recall curve (AUPRC) = 0.44. Cross-validated balanced-accuracy, sensitivity and specificity were 0.59, 0.25 and 0.93, respectively, using p = 0.5 to dichotomize the model predicted probabilities (vs 0.71, 0.70 and 0.72, respectively using p = 0.188 according to Youden index). The unsupervised approach identified two clusters, which were not associated with LTP (p = 0.8211) but with the occurrence of per-RFA intra-alveolar hemorrhage, post-RFA cavitations and fistulizations (p = 0.0150). CONCLUSION: Predictive models using RFs from the post-RFA ablation zone on the first revaluation CT-scan of CRC lung metastases seemed moderately informative regarding the occurrence of LTP. ADVANCES IN KNOWLEDGE: Radiomics approach on interventional radiology data is feasible. However, patterns of heterogeneity detected with RFs on early re-evaluation CT-scans seem biased by different healing processes following benign RFA complications.

Imaging presentation of extraskeletal osteosarcomas on CT and MRI and correlation with patients outcome: A two-center retrospective study of 54 patients.

PURPOSE: The purpose of this study was to analyze the imaging features of extraskeletal osteosarcomas (ESOS) on computed tomography (CT) and magnetic resonance imaging (MRI) and to investigate their associations with overall survival (OS) using uni- and multivariable survival analyses. MATERIALS AND METHODS: This two-center retrospective study included all consecutive adult patients between 2008 and 2021 with histopathologically-proven ESOS who underwent pre-treatment CT and/or MRI. Clinical and histological characteristics, ESOS presentation on CT and MRI, treatment and outcomes were reported. Survival analyses were performed using Kaplan-Meier analysis and Cox regressions. Associations between imaging features and OS were searched using uni- and multivariable analyses. RESULTS: Fifty-four patients were included (30/54 [56%] men, median age: 67.5 years). Twenty-four died of ESOS (median OS: 18 months). ESOS were mostly deep-seated (46/54, 85%) in the lower limb (27/54, 50%) with a median size of 95 mm (interquartile range: 64, 142; range: 21-289 mm). Mineralization was seen on 26/42 (62%) patients, mainly gross-amorphous (18/26; 69%). ESOS were generally highly heterogeneous on T2-weighted images (38/48; 79%) and contrast-enhanced (CE) T1-weighted images (29/40; 72%), with necrosis (39/40; 97%), well-defined or focally infiltrative margins (39/47; 83%), with moderate peritumoral edema (39/47; 83%) and rim-like peripheral enhancement (17/40; 42%). Size, location, mineralization on CT, signal intensity heterogeneity on T1-, T2- and CE-T1-weighted images and hemorragic signal on MRI were associated with poorer OS (range of log-rank P = 0.0069-0.0485). At multivariable analysis, hemorragic signal and signal intensity heterogeneity on T2-weighted images remained predictive for poorer OS (hazard ratio [HR] = 2.68, P = 0.0299; HR = 9.85, P = 0.0262, respectively) CONCLUSION: ESOS typically presents as mineralized heterogeneous and necrotic soft tissue tumor with a possible rim-like enhancement and limited peritumoral abnormalities. MRI may help estimate outcome of patients with ESOS.

Standardized Pathology Screening of Mature Tertiary Lymphoid Structures in Cancers.

Mature tertiary lymphoid structures (mTLSs) are organized lymphoid structures containing B lymphocytes admixed to CD23+ follicular dendritic cells. Their presence has been linked to improved survival and sensitivity to immune checkpoint inhibitors in several cancers, emerging as a promising pancancer biomarker. However, the requirements for any biomarker are clear methodology, proven feasibility, and reliability. In 357 patients' samples, we studied tertiary lymphoid structures (TLSs) parameters using multiplex immunofluorescence (mIF), hematoxylin-eosin-saffron (HES) staining, double CD20/CD23 staining, and single CD23 immunohistochemistry. The cohort included carcinomas (n = 211) and sarcomas (n = 146), gathering biopsies (n = 170), and surgical specimens (n = 187). mTLSs were defined as TLSs containing either a visible germinal center on HES staining or CD23+ follicular dendritic cells. Focusing on 40 TLSs assessed using mIF, double CD20/CD23 staining was less sensitive than mIF to assess maturity in 27.5% (n = 11/40) but was rescued by single CD23 staining in 90.9% (n = 10/11). In 97 patients, several samples (n = 240) were reviewed to characterize TLS distribution. The likelihood of finding TLSs in surgical material was 6.1 higher than in biopsy and 2.0 higher in primary samples than in metastasis after adjustment with a type of sample. Interrater agreement rates over 4 examiners were 0.65 (Fleiss kappa, 95% CI [0.46, 0.90]) for the presence of TLS and 0.90 for maturity (95% CI [0.83, 0.99]). In this study, we propose a standardized method to screen mTLSs in cancer samples using HES staining and immunohistochemistry that can be applied to all specimens.

Soft-tissue sarcoma in adults: Imaging appearances, pitfalls and diagnostic algorithms.

This article provides an overview of the current knowledge regarding diagnostic imaging of patients with soft-tissue sarcomas, which is a heterogeneous group of rare mesenchymal malignancies. After an initial contextualization, diagnostic flow-chart based on initial radiological findings of soft-tissue masses (with specific focus on adipocytic soft-tissue tumors [STTs], hemorragic STTs and retroperitoneal STTs) are provided considering relevant results from novel researches, guidelines, and experts' viewpoints, with the aim to help radiologists and clinicians in their practice. Particularly, the central place of sarcoma reference centers in the diagnostic and therapeutic management is highlighted, as well as the pivotal role that radiologists should play to correctly identify patients with soft-tissue sarcoma at the initial stage of the disease. Indications and methods for performing imaging-guided biopsies are also discussed, as well as clues to improve soft-tissue sarcoma grading with conventional and quantitative imaging.

Role of Imaging in Initial Prognostication of Locally Advanced Soft Tissue Sarcomas.

BACKGROUND: Although imaging is central in the initial staging of patients with soft tissue sarcomas (STS), it remains underused and few radiological features are currently used in practice for prognostication and to help guide the best therapeutic strategy. Yet, several prognostic qualitative and quantitative characteristics from magnetic resonance imaging (MRI) and positron emission tomography (PET) have been identified over these last decades. OBJECTIVE: After an overview of the current validated prognostic features based on baseline imaging and their integration into prognostic tools, such as nomograms used by clinicians, the aim of this review is to summarize more complex and innovative MRI, PET, and radiomics features, and to highlight their role to predict indirectly (through histologic grade) or directly the patients' outcomes.

Primary Soft-Tissue Lymphomas: MRI Features Help Discriminate From Other Soft-Tissue Tumors.

OBJECTIVES: MRI presentation of extra-nodal soft-tissue lymphomas (STLs) is scarcely reported and lacks of comparison with other soft-tissue tumors (STTs) including sarcomas (STS). Yet, suggesting this diagnosis on MRI would considerably reduce diagnostic intervals. Our aim was to investigate if conventional MRI could discriminate STLs from other STTs. METHODS: MRIs of STL patients were compared with those of patients addressed to a sarcoma reference center for the diagnosis of a STT. MRI characteristics depicting the tumor (size, signal, habitats, shape, surrounding tissues) were reported. Uni- and multivariate associations with STL diagnosis were evaluated in the entire cohort, and in the subgroups of benign and malignant STTs patients. Diagnostic performances of MRI features combinations were tested. RESULTS: We included 39 patients with STLs (median age: 69 years) and 368 patients with other STTs (122 benign STTs and 246 STS; median age: 58 years). Six MRI features were independent predictors of STL compared to all other STTs: intermediate SI on T1-WI, homogeneous enhancement (without necrotic areas), no blood signal, no fibrotic signal, no peritumoral enhancement and lack of abnormal intra- and peritumoral vasculature (p-value range: <0.0001-0.0163). Their simultaneous presence had a sensitivity of 0.88 (0.71-0.96) and a specificity of 0.88 (0.84-0.91). Other relevant MRI features were: no fat signal to discriminate against STS (p = 0.0409), the infiltrative growth pattern and the vessel and nerve encasement to discriminate against benign STTs (p = 0.0016 and 0.0011, respectively). CONCLUSION: Our research demonstrates that conventional MRI can help discriminating STLs from other STTs. Indeed, radiologists can help suggesting the possible diagnosis of STL, which could speed-up the subsequent proper histopathological analysis in light of MRI findings.