Successful Outcome of Metastatic Pancreatoblastoma in an Adolescent: A Case Report and Review of the Literature.

Pancreatoblastoma, an orphan disease, is the most common malignant epithelial neoplasm of the pancreas in children. With vague clinical features, diagnosis is made by radiological suggestions and histopathology. The presence of metastatic disease and inoperable/incomplete excision remains the poor prognostic markers. We present a rare instance of an adolescent who has survived metastatic pancreatoblastoma after neoadjuvant chemoreduction/complete surgical excision.

Prognostic significance of metabolic tumour volume and maximum standard uptake value of fluor-18-fluorodeoxyglucose positron emission tomography with computed tomography in nasopharyngeal carcinoma.

AIM OF THE STUDY: To evaluate the prognostic role of markers of fluor-18-fluorodeoxyglucose positron emission tomography with computed tomography (18F-FDG-PET-CT), such as maximum standard uptake value (SUVmax) and metabolic tumour volume (MTV) measured at primary and nodal disease, and their clinical significance in terms of predicting treatment outcomes and survival. MATERIAL AND METHODS: Between January 2017 and January 2020, 20 case records of nasopharyngeal carcinoma patients who underwent 18F-FDG-PET-CT as part of staging workup before radiotherapy and as a part of response evaluation after radiotherapy were retrospectively reviewed. RESULTS: At a median follow-up of 34.7 months, the 2-year progression-free survival (PFS) was 70% and 2-year overall survival (OS) was 79%. Patients with a lower nodal SUVmax (SUVmax-N) had a better 2-year PFS (91% vs. 46%; p = 0.035) and 2-year OS (95% vs. 58%; p = 0.015). A high SUVmax-N of > 10.58 was a negative predictor of OS (95% confidence interval [CI]: 0.93-1; p = 0.003) as well as PFS (95% CI: 0.64-1; p = 0.017). Also, a high MTV > 25.8 cm3 was a negative predictor of PFS (95% CI: 0.58-0.98; p = 0.048). MTV was an independent predictor of PFS and OS on univariate analysis, whereas it was not significant in the Cox regression multivariate analysis. CONCLUSIONS: High values of MTV and SUVmax-N can be considered as independent prognostic factors of OS and PFS in nasopharyngeal cancer patients treated with concurrent chemoradiation, highlighting the need for more intensified treatment.

Radiomics analysis for distinctive identification of COVID-19 pulmonary nodules from other benign and malignant counterparts.

This observational study investigated the potential of radiomics as a non-invasive adjunct to CT in distinguishing COVID-19 lung nodules from other benign and malignant lung nodules. Lesion segmentation, feature extraction, and machine learning algorithms, including decision tree, support vector machine, random forest, feed-forward neural network, and discriminant analysis, were employed in the radiomics workflow. Key features such as Idmn, skewness, and long-run low grey level emphasis were identified as crucial in differentiation. The model demonstrated an accuracy of 83% in distinguishing COVID-19 from other benign nodules and 88% from malignant nodules. This study concludes that radiomics, through machine learning, serves as a valuable tool for non-invasive discrimination between COVID-19 and other benign and malignant lung nodules. The findings suggest the potential complementary role of radiomics in patients with COVID-19 pneumonia exhibiting lung nodules and suspicion of concurrent lung pathologies. The clinical relevance lies in the utilization of radiomics analysis for feature extraction and classification, contributing to the enhanced differentiation of lung nodules, particularly in the context of COVID-19.

Radiomics as a non-invasive adjunct to Chest CT in distinguishing benign and malignant lung nodules.

In an observational study conducted from 2016 to 2021, we assessed the utility of radiomics in differentiating between benign and malignant lung nodules detected on computed tomography (CT) scans. Patients in whom a final diagnosis regarding the lung nodules was available according to histopathology and/or 2017 Fleischner Society guidelines were included. The radiomics workflow included lesion segmentation, region of interest (ROI) definition, pre-processing, and feature extraction. Employing random forest feature selection, we identified ten important radiomic features for distinguishing between benign and malignant nodules. Among the classifiers tested, the Decision Tree model demonstrated superior performance, achieving 79% accuracy, 75% sensitivity, 85% specificity, 82% precision, and 90% F1 score. The implementation of the XGBoost algorithm further enhanced these results, yielding 89% accuracy, 89% sensitivity, 89% precision, and an F1 score of 89%, alongside a specificity of 85%. Our findings highlight tumor texture as the primary predictor of malignancy, emphasizing the importance of texture-based features in computational oncology. Thus, our study establishes radiomics as a powerful, non-invasive adjunct to CT scans in the differentiation of lung nodules, with significant implications for clinical decision-making, especially for indeterminate nodules, and the enhancement of diagnostic and predictive accuracy in this clinical context.

Unusual sites of Rosai-Dorfman disease in children: 5 years experience from tertiary care paediatric haemato-oncology centre.

Rosai-Dorfman disease (RDD) is a rare histiocytic disorder, usually presenting with massive lymphadenopathy. The involvement of extra nodal sites, bone and nodal sites like mediastinum are rare. Clinical data of three cases of extra nodal RDD who were admitted in our paediatric haemato-oncology unit were analysed in the last 5 years. The extra nodal RDD (maxillary sinus, nasal pharyngeal focus, and external auditory meatus) were diagnosed based on histopathology and positron emission tomography scan. They were treated with steroids but were refractory hence requiring salvage chemotherapy. Currently all three of them are in complete remission. Extra nodal RDD is difficult to diagnose, histopathology and radiology play an important role. Here, we present three cases, of which two were steroid-refractory which were treated with salvage chemotherapy and are in complete remission.

Radiomic Analysis of Positron-Emission Tomography and Computed Tomography Images to Differentiate between Multiple Myeloma and Skeletal Metastases.

Context: Multiple myeloma and extensive lytic skeletal metastases may appear similar on positron-emission tomography and computed tomography (PET-CT) in the absence of an obvious primary site or occult malignancy. Radiomic analysis extracts a large number of quantitative features from medical images with the potential to uncover disease characteristics below the human visual threshold. Aim: This study aimed to evaluate the diagnostic capability of PET and CT radiomic features to differentiate skeletal metastases from multiple myeloma. Settings and Design: Forty patients (20 histopathologically proven cases of multiple myeloma and 20 cases of a variety of bone metastases) underwent staging 18F-fluorodeoxyglucose PET-CT at our institute. Methodology: A total of 138 PET and 138 CT radiomic features were extracted by manual semi-automatic segmentation and standardized. The original dataset was subject separately to receiver operating curve analysis and correlation matrix filtering. The former showed 16 CT and 19 PET parameters to be significantly related to the outcome at 5%, whereas the latter resulted in 16 CT and 14 PET features. Feature selection was done with 7 evaluators with stratified 10-fold cross-validation. The selected features of each evaluator were subject to 14 machine-learning algorithms. In view of small sample size, two approaches for model performance were adopted: The first using 10-fold stratified cross-validation and the second using independent random training and test samples (26:14). In both approaches, the highest area under the curve (AUC) values were selected for 5 CT and 5 PET features. These 10 features were combined and the same process was repeated. Statistical Analysis Used: The quality of the performance of the models was assessed by MSE, RMSE, kappa statistic, AUC, area under the precision-recall curve, F-measure, and Matthews correlation coefficient. Results: In the first approach, the highest AUC = 0.945 was seen with 5 CT parameters. In the second approach, the highest AUC = 0.9538 was seen with 4 CT and one PET parameter. CT neighborhood gray-level different matrix coarseness and CT gray-level run-length matrix LGRE were common parameters in both approaches. Comparison of AUC of the above models showed no significant difference (P = 0.9845). Feature selection by principal components analysis and feature classification by the multilayer perceptron machine-learning model using independent training and test samples yielded the overall highest AUC. Conclusions: Machine-learning models using CT parameters were found to differentiate bone metastases from multiple myeloma better than models using PET parameters. Combined models using PET and CECT data showed better overall performance than models using only either PET or CECT data. Machine-learning models using independent training and test sets were performed on par with those using 10-fold stratified cross-validation with the former incorporating slightly more PET features. Certain first- and second-order CT and PET texture features contributed in differentiating these two conditions. Our findings suggested that, in general, metastases were finer in CT and PET texture and myelomas were more compact.

Case report: Metastatic myxoid liposarcoma arising from the right atrium extends as cardiac tamponade-A rare case of atrial oncology.

The reported incidence of liposarcomas in ~2,000 cases annually results in about 30% of myxoid liposarcomas. Cardiac myoxid liposarcomas are very rare; their presentation could be cardiac tamponade, due to direct compression of the tumor and/or pericardial effusion. In this report, we describe a patient who presented with pericardial effusion secondary to myoxid liposarcomas from the right atrium, an extremely rare presentation of liposarcomas in the heart. We also present non-invasive imaging through echocardiography, CECT thorax and FDG PET scans, followed by a CT-guided mass biopsy. Histopathology of the right atrial mass demonstrated myxoid liposarcoma positive for the S100 tumor marker.

Correlation between Reference Tissue Normalized 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Standardized Uptake Value Max of Nodal and Extranodal Sites in Lymphomas: An Empirical Study.

CONTEXT: Extranodal (EN) lymphomas involve sites other than lymph nodes (LNs), spleen, thymus, and the pharyngeal lymphatic ring. The highest standardized uptake value (SUV) max of the LN can aid in the diagnosis of EN site lymphomatous infiltrations over inflammation or infection especially when there are no contrast-enhanced computed tomography (CT) changes. AIMS: The purpose of this study was to find the significance of correlation between absolute SUVmax and mediastinal blood pool (mbSUVmax) and liver (lvSUVmax) normalized SUVmax of EN sites and the most fluorodeoxyglucose (FDG) avid LN in patients with primary and secondary EN involvement in Non-Hodgkin's and Hodgkin's Lymphoma. SETTINGS AND DESIGN: This was a retrospective study of 70 patients with histopathologically proven lymphoma in whom 18F-FDG positron emission tomography CT was performed for pretherapy staging. MATERIALS AND METHODS: Images were used to detect EN sites of disease and SUVmax of mediastinal blood pool, liver, highest SUVmax LN, and highest SUVmax EN site were calculated. STATISTICAL ANALYSIS USED: Karl Pearson's coefficient of correlation (r) was used to correlate the highest SUV max of LN and EN site and corresponding highest blood pool corrected and liver corrected SUV max. In view of small sample size, t-test for paired samples at 5% and 10% significance was conducted to validate the findings. Two-tailed t-test for independent samples was also used to compare means of SUVmax values between data grouped according to gender and lymphoma subtype (Non-Hodgkin lymphoma and Hodgkin lymphoma). RESULTS: r = 0.54 for the highest LN SUVmax-highest EN SUVmax values and on further validation by one- and two-tailed paired t-test at significance levels of 5% and 10%, P = 0.00052 and 0.00103 respectively which denoted significant positive and moderate correlation. r = 0.59 for highest LN lvSUVmax-highest EN vSUVmax and P = 0.00032 and 0.00065 showing positive and moderate correlation. r = 0 0.82 for highest LN mbSUVmax-highest EN mbSUVmax values and P = 0.00034 and 0.00068 revealing positive and strong correlation. CONCLUSION: Significant positive and strong correlation exists between nodal and EN mbsUVmax. This is stronger than the correlation between nodal and EN absolute SUVmax and lvSUVmax. Since normalization of lesion SUVmax to reference tissues reduces the variability of SUV, this can be a useful adjunct to determine whether high SUVmax of the EN site is due to lymphomatous infiltration.

Telangiectatic Osteosarcoma in a Young Child - A Case Report and Review of the Literature.

Introduction: Osteosarcoma (OS) is one of the most common primary malignant bone tumors in children and adolescents. OS incidence varies significantly with age and peak incidence is in adolescent age group. Telangiectatic osteosarcoma (TOS) is an unusual variant of OS, forming 3-10% of all OSs. Only few case reports of this rare variant of OS are described in the literature. Case Report: We report a 6-year-girl who presented with fracture of the left proximal humerus after a trivial trauma. X-ray left shoulder showed osteolytic lesions in the left proximal humerus with fracture of proximal humerus. Open biopsy from the left proximal humerus osteolytic lesion suggested clusters of highly atypical cells like osteoid material and focal areas of hemorrhage and necrosis suggestive of TOS. The child was started on chemotherapy followed by limb-salvage surgery with wide resection of the tumor in the left proximal humerus. She completed her adjuvant chemotherapy and is currently doing well for the past 4 years. Conclusion: OS occurs more frequently in adolescents around the knee in the metaphyses. The most common histologic type is osteoblastic/fibroblastic or chondroblastic type. Very few cases have been reported in <5 years age group and it's relatively rare in 5-10-year-old children. Rare histologic variants, especially telangiectatic variant, are more common in younger children and occur more in upper limbs. Imaging reveals mainly osteolytic lesions, unlike in conventional OS. This case highlights the utmost role of histopathology in the diagnosis of the bone tumors which would guide the management appropriately.