POS1315 USEFULNESS OF SYNOVIAL BIOPSY IN THE DIFFERENTIAL DIAGNOSIS AND AS POSSIBLE PREDICTOR OF RESPONSE TO TREATMENT IN JUVENILE IDIOPATHIC ARTHRITIS

Background:While synovial biopsy is an invasive procedure and is not required for the diagnosis of juvenile idiopathic arthritis (JIA), it may be useful in doubtful cases.Objectives:Aims of the study were i.to verify the role of synovial biopsy in the differential diagnosis of JIA and ii. to review the pathology slides in order to evaluate possible associations of a histologic pattern with response to treatment.Methods:We reviewed data from medical records of patients under the age of 18 years who underwent a synovial biopsy requested by our Pediatric Rheumatology Unit over the last 10 years. We collected information on demographic, clinical, laboratory, radiological, histopathological characteristics, as well as treatment response (in particular, remission at the last visit and number of examination, number of biologic drugs used). Among variables in the histologic score, number of layers in the synovial lining and inflammatory infiltrate (0-5) were compared to clinical status at last visit. Potential differences in variables between responders and non responders were assessed by unpaired t-test or non-parametric Mann-Whitney test, as appropriate.Results:We identified 64 patients (40F, 24M) with a median age at disease onset of 9 years (range 1-15) and a median follow-up time of 161 months (range 8-1160). We recognized two groups of interest: patients with a known JIA diagnosis (28/64) and patients with unknown diagnosis (36/64) at the moment of synovial biopsy. In the group with known JIA, most underwent the procedure during orthopedic surgery, and in all cases the histology was consistent with JIA. Among the unknown diagnosis group, in 19 cases results were consistent with a chronic synovitis, while among the other 17 histology could lead to a diagnosis of other conditions in 6 cases (foreign body and villonodular synovitis n=2 each, sarcoidosis and osteochondromatosis n=1 each). In the remaining 11 the final diagnoses were varied (mostly genetic forms eg skeletal dysplasia, CACP, Thiemann disease).Between the two groups we identified 46 patients with a definite JIA diagnosis. At the last follow-up visit 29 of them were in clinical remission, albeit on medication. The remaining 17 had a severe course of disease, with persistent activity and use of at least two biologic drugs. In 26 cases we could evaluate the correlation between status at last visit and number of layers/inflammatory infiltrate, but no statistical significant correlation was found.Conclusion:Despite its limited use nowadays, synovial biopsy may still be a useful tool in patients whose diagnosis is unclear. In our study, while it confirmed the suspicion in most cases, in other instances it allowed the diagnosis of rare conditions that would have been otherwise missed. No association between disease course and histological features in a small JIA cohort was found. We are currently expanding the study with a larger series.Disclosure of Interests:None declare

Expression profiling of microRNAs and isomiRs in conventional central chondrosarcoma

Conventional central chondrosarcoma (CCC) is a malignant bone tumor that is characterized by the production of chondroid tissue. Since radiation therapy and chemotherapy have limited effects on CCC, treatment of most patients depends on surgical resection. This study aimed to identify the expression profiles of microRNAs (miRNAs) and isomiRs in CCC tissues to highlight their possible participation to the regulation of pathways critical for the formation and growth of this type of tumor. Our study analyzed miRNAs and isomiRs from Grade I (GI), Grade II (GII), and Grade III (GIII) histologically validated CCC tissue samples. While the different histological grades shared a similar expression profile for the top abundant miRNAs, we found several microRNAs and isomiRs showing a strong different modulation in GII + GIII vs GI grade samples and their involvement in tumor biology could be consistently hypothesized. We then in silico validated these differently expressed miRNAs in a larger chondrosarcoma public dataset and confirmed the expression trend for 17 out of 34 miRNAs. Our results clearly suggests that the contribution of miRNA deregulation, and their targeted pathways, to the progression of CCC could be relevant and strongly indicates that when studying miRNA deregulation in tumors, not only the canonical miRNAs, but the whole set of corresponding isomiRs should be taken in account. Improving understanding of the precise roles of miRNAs and isomiRs over the course of central chondrosarcoma progression could help identifying possible targets for precision medicine therapeutic intervention

Sternal reconstruction for unusual chondrosarcoma : innovative technique

The authors report a clinical case of a primary sternal chondrosarcoma, presented as a mass in the anterior mediastinum. The patient was treated with subtotal sternectomy and sternal transplantation followed by radiotherapy. Twelve months after surgery, the patient is in good clinical condition, without any sign of tumor relapse and with normal respiratory mechanics. Primary malignant tumors of the sternum are uncommon and a presentation mimicking thymoma is rare and unreported. The stermal replacement with a cryopreserved allograft sternum is an innovative technique that overcomes the problems related to the prosthetic biocompatibility or to the bone autograft

Proton pump inhibitor chemosensitization in human osteosarcoma: from the bench to the patients' bed.

BACKGROUND: Major goals in translational oncology are to reduce systemic toxicity of current anticancer strategies and improve effectiveness. An extremely efficient cancer cell mechanism to avoid and/or reduce the effects of highly cytotoxic drugs is the establishment of an acidic microenvironment, an hallmark of all malignant tumors. The H\u2009+-rich milieu that anticancer drugs meet once they get inside the tumor leads to their protonation and neutralization, therefore hindering their access into tumor cells. We have previously shown that proton pump inhibitors (PPI) may efficiently counterattack this tumor advantage leading to a consistent chemosensitization of tumors. In this study, we investigated the effects of PPI in chemosensitizing osteosarcoma. METHOD: MG-63 and Saos-2 cell lines were used as human osteosarcoma models. Cell proliferation after pretreatment with PPI and subsequent treatment with cisplatin was evaluated by using erythrosin B dye vital staining. Tumour growth was evaluated in xenograft treated with cisplatin after PPI pretreatment. Subsequently, a multi-centre historically controlled trial, was performed to evaluate the activity of a pre-treatment administration of PPIs as chemosensitizers during neoadjuvant chemotherapy based on methotrexate, cisplatin, and adriamycin. RESULTS: Preclinical experiments showed that PPI sensitize both human osteosarcoma cell lines and xenografts to cisplatin. A clinical study subsequently showed that pretreatment with PPI drug esomeprazole leads to an increase in the local effect of chemotherapy, as expressed by percentage of tumor necrosis. This was particularly evident in chondroblastic osteosarcoma, an histological subtype that normally shows a poor histological response. Notably, no significant increase in toxicity was recorded in PPI treated patients. CONCLUSION: This study provides the first evidence that PPI may be beneficially added to standard regimens in combination to conventional chemotherapy

Increased p21 expression in chondrocytes of achondroplasic children independently from the presence of the G380R FGFR3 mutation

Background. Achondroplasia (ACH) represents the major cause of dwarfi sm and is due to mutations in the fi broblast growth factor receptor 3 (FGFR3) gene. The cellular mechanisms involved in the reduced growth have been mainly described for in vitro or in vivo models, but few data have been obtained for humans. Methods. Thirteen children with ACH were enrolled in the study; the presence of FGFR3 mutations was determined by restriction fragment length polymorphism analysis and sequencing, whereas protein expression in cartilage biopsy was assessed by immunohistochemistry. Results. Chondrocytes in cartilage biopsies of ACH children were characterized by the presence of growth arrest mediated by STAT activation (both STAT1 and STAT5) and increased expression of p21 and cyclin D1, whereas no expression of either p53 or cyclin D3 could be detected. This mechanism was present in ACH children carrying the G380R mutation but also in a patient in whom no mutation could be detected in the entire coding region of the FGFR3 gene. Conclusions. These data thus demonstrate the presence of a common fi nal mechanism involving p21 and possibly leading to a block in chondrocyte proliferation

A robust and powerful green light photoemission source: The ferroelectric ceramics

The photoemission characteristics of ceramic disks of lead zirconate titanate lanthanum doped (PLZT), have been investigated. We observe 1 nC of extracted charge under an accelerating field of 20 kV/cm in poor vacuum conditions. The emission is clearly limited by space charge effects. The extrapolated quantum efficiency results in ≈10−6. The yield of a PLZT ceramic in the ferroelectric state and its slope versus light intensity have turned out higher than those of antiferroelectric ceramic. Samples in different experimental configurations have shown different nonlinear yields

Diffusion-weighted MRI radiomics of spine bone tumors: feature stability and machine learning-based classification performance

Purpose To evaluate stability and machine learning-based classification performance of radiomic features of spine bone tumors using diffusion- and T2-weighted magnetic resonance imaging (MRI). Material and methods This retrospective study included 101 patients with histology-proven spine bone tumor (22 benign; 38 primary malignant; 41 metastatic). All tumor volumes were manually segmented on morphologic T2-weighted sequences. The same region of interest (ROI) was used to perform radiomic analysis on ADC map. A total of 1702 radiomic features was considered. Feature stability was assessed through small geometrical transformations of the ROIs mimicking multiple manual delineations. Intraclass correlation coefficient (ICC) quantified feature stability. Feature selection consisted of stability-based (ICC > 0.75) and significance-based selections (ranking features by decreasing Mann-Whitney p-value). Class balancing was performed to oversample the minority (i.e., benign) class. Selected features were used to train and test a support vector machine (SVM) to discriminate benign from malignant spine tumors using tenfold cross-validation. Results A total of 76.4% radiomic features were stable. The quality metrics for the SVM were evaluated as a function of the number of selected features. The radiomic model with the best performance and the lowest number of features for classifying tumor types included 8 features. The metrics were 78% sensitivity, 68% specificity, 76% accuracy and AUC 0.78. Conclusion SVM classifiers based on radiomic features extracted from T2- and diffusion-weighted imaging with ADC map are promising for classification of spine bone tumors. Radiomic features of spine bone tumors show good reproducibility rates

3D vs. 2D MRI radiomics in skeletal Ewing sarcoma: Feature reproducibility and preliminary machine learning analysis on neoadjuvant chemotherapy response prediction

ObjectiveThe extent of response to neoadjuvant chemotherapy predicts survival in Ewing sarcoma. This study focuses on MRI radiomics of skeletal Ewing sarcoma and aims to investigate feature reproducibility and machine learning prediction of response to neoadjuvant chemotherapy. Materials and methodsThis retrospective study included thirty patients with biopsy-proven skeletal Ewing sarcoma, who were treated with neoadjuvant chemotherapy before surgery at two tertiary sarcoma centres. 7 patients were poor responders and 23 were good responders based on pathological assessment of the surgical specimen. On pre-treatment T1-weighted and T2-weighted MRI, 2D and 3D tumour segmentations were manually performed. Features were extracted from original and wavelet-transformed images. Feature reproducibility was assessed through small geometrical transformations of the regions of interest mimicking multiple manual delineations, and intraclass correlation coefficient >0.75 defined feature reproducibility. Feature selection also consisted of collinearity and significance analysis. After class balancing in the training cohort, three machine learning classifiers were trained and tested on unseen data using hold-out cross-validation. Results1303 (77%) 3D and 620 (65%) 2D radiomic features were reproducible. 4 3D and 4 2D features passed feature selection. Logistic regression built upon 3D features achieved the best performance with 85% accuracy (AUC=0.9) in predicting response to neoadjuvant chemotherapy. ConclusionCompared to 2D approach, 3D MRI radiomics of Ewing sarcoma had superior reproducibility and higher accuracy in predicting response to neoadjuvant chemotherapy, particularly when using logistic regression classifier

MRI radiomics-based machine learning classification of atypical cartilaginous tumour and grade II chondrosarcoma of long bones

Background: Atypical cartilaginous tumour (ACT) and grade II chondrosarcoma (CS2) of long bones are respectively managed with watchful waiting or curettage and wide resection. Preoperatively, imaging diagnosis can be challenging due to interobserver variability and biopsy suffers from sample errors. The aim of this study is to determine diagnostic performance of MRI radiomics-based machine learning in differentiating ACT from CS2 of long bones. Methods: One-hundred-fifty-eight patients with surgically treated and histology-proven cartilaginous bone tumours were retrospectively included at two tertiary bone tumour centres. The training cohort consisted of 93 MRI scans from centre 1 (n=74 ACT; n=19 CS2). The external test cohort consisted of 65 MRI scans from centre 2 (n=45 ACT; n=20 CS2). Bidimensional segmentation was performed on T1-weighted MRI. Radiomic features were extracted. After dimensionality reduction and class balancing in centre 1, a machine-learning classifier (Extra Trees Classifier) was tuned on the training cohort using 10-fold cross-validation and tested on the external test cohort. In centre 2, its performance was compared with an experienced musculoskeletal oncology radiologist using McNemar's test. Findings: After tuning on the training cohort (AUC=0.88), the machine-learning classifier had 92% accuracy (60/ 65, AUC=0.94) in identifying the lesions in the external test cohort. Its accuracies in correctly classifying ACT and CS2 were 98% (44/45) and 80% (16/20), respectively. The radiologist had 98% accuracy (64/65) with no difference compared to the classifier (p=0.134). Interpretation: Machine learning showed high accuracy in classifying ACT and CS2 of long bones based on MRI radiomic features. Copyright (C) 2021 The Authors. Published by Elsevier B.V.Orthopaedics, Trauma Surgery and Rehabilitatio