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Purpose: The proposed work aims to develop an algorithm to precisely segment the lung parenchyma in thoracic CT scans. To achieve this goal, the proposed technique utilized a combination of deep learning and traditional image processing algorithms. The initial step utilized a trained convolutional neural network (CNN) to generate preliminary lung masks, followed by the proposed post-processing algorithm for lung boundary correction. Methods: First, the proposed method trained an improved 2D U-Net CNN model with Inception-ResNet-v2 as its backbone. The model was trained on 32 CT scans from two different sources: one from the VESSEL12 grand challenge and the other from AIIMS Delhi. Further, the model's performance was evaluated on a test dataset of 16 CT scans with juxta-pleural nodules obtained from AIIMS Delhi and the LUNA16 challenge. The model's performance was assessed using evaluation metrics such as average volumetric dice coefficient (DSCavg), average IoU score (IoUavg), and average F1 score (F1avg). Finally, the proposed post-processing algorithm was implemented to eliminate false positives from the model's prediction and to include juxta-pleural nodules in the final lung masks. Results: The trained model reported a DSCavg of 0.9791 ± 0.008, IoUavg of 0.9624 ± 0.007, and F1avg of 0.9792 ± 0.004 on the test dataset. Applying the post-processing algorithm to the predicted lung masks obtained a DSCavg of 0.9713 ± 0.007, IoUavg of 0.9486 ± 0.007, and F1avg of 0.9701 ± 0.008. The post-processing algorithm successfully included juxta-pleural nodules in the final lung mask. Conclusions: Using a CNN model, the proposed method for lung parenchyma segmentation produced precise segmentation results. Furthermore, the post-processing algorithm addressed false positives and negatives in the model's predictions. Overall, the proposed approach demonstrated promising results for lung parenchyma segmentation. The method has the potential to be valuable in the advancement of computer-aided diagnosis (CAD) systems for automatic nodule detection. [ABSTRACT FROM AUTHOR]

Objectives: To translate the Pediatric Nausea Assessment Tool (PeNAT) into Hindi and validate it in Indian pediatric cancer patients and survivors. Methods: The PeNAT-Hindi was finalized by forward and backward translations, and pilot testing. The PeNAT-Hindi was administered to 200 Hindi-speaking pediatric (4–18 y) cancer patients/survivors, in three groups. These included pediatric cancer patients who had recently received chemotherapy (n = 150); who received no chemotherapy within 5 d (n = 25) and survivors (n = 25). Construct validity was tested by comparing scores among the three groups. Test–retest reliability and criterion validity were estimated by the correlation of the first PeNAT score with the second (taken 1 h later) PeNAT score and the number of vomiting/retching episodes, respectively. Convergent validity and discriminant validity were estimated by correlating PeNAT scores with parent-assessed nausea severity, and pain, respectively. The responsiveness was tested by comparing second PeNAT scores with subsequent divergent PeNAT scores among patients reporting subjective change (improvement and worsening, respectively) in nausea severity. Results: Test–retest reliability of PeNAT-Hindi was good (intraclass correlation = 0.791). The initial PeNAT score had moderate correlation with the number of vomiting/retching episodes (Spearman ρ = 0.401). Median PeNAT scores in group 1 versus groups 2 and 3 were significantly different (p < 0.001). Initial PeNAT scores showed a moderate correlation with parent-assessed nausea (Spearman ρ = 0.657) and a weak correlation with parent-assessed pain (Spearman ρ = 0.319). The responsiveness (standardized response mean) of PeNAT-Hindi to the change in nausea severity was −1.79 (improvement) and 2.19 (worsening), respectively. Conclusion: PeNAT-Hindi showed good reliability and acceptable validity. It may be used among Hindi-speaking children for measuring nausea. The responsiveness of PeNAT-Hindi needs further evaluation. [ABSTRACT FROM AUTHOR]

Philadelphia chromosome positive (Ph+) acute lymphoblastic lymphoma (ALL) is an uncommon subtype of ALL in children, seen in 2–5% cases. Diagnostic evaluation includes conventional karyotyping and detection of BCR-ABL1 translocation by fluorescence in-situ hybridization (FISH) or reverse transcriptase polymerase chain reaction (RT-PCR). For children, the frontline management includes combination of intensive chemotherapy along with imatinib (300–340 mg/m2/d) or dasatinib (60–80 mg/m2/d). Imatinib/dasatinib should be introduced in induction as soon as results for BCR-ABL are available. Minimal residual disease (MRD) monitoring is essential; multi-parametric flowcytometry and immunoglobulin/T-cell receptor rearrangement PCR are the preferred methods. Intrathecal therapy with at least 12 doses of methotrexate is adequate for central nervous system (CNS) prophylaxis, but cranial radiation is necessary for CNS3 involvement. Allogeneic hematopoietic stem cell transplantation (HSCT) in first remission may be considered in high-risk cases (persistent MRD positivity/induction failure). Maintenance therapy with tyrosine kinase inhibitors (TKI) in children is debatable, with potential concerns for long term adverse effects. At relapse, the choice of TKI is guided by the presence of BCR-ABL tyrosine kinase domain resistance mutations, although the frequency of resistance mutations in children are lower. Allogeneic HSCT is essential for consolidation in second remission, if not done. Ph-like ALL is a newly recognized molecular entity, with gene expression profile similar to Ph+ALL and poor survival outcomes. In resource-constrained settings, a stepwise cost-effective diagnostic evaluation should be considered among high-risk patients without recurrent genetic abnormalities. Current treatment strategies remain similar to Ph-negative ALL. Enrolment in clinical trials is encouraged for such children to evaluate potential targeted agents in this subtype. [ABSTRACT FROM AUTHOR]

Osteosarcoma (OGS) is the most common primary bone tumor in children and adolescents which requires a multidisciplinary approach to management. Although chemotherapy and surgery can cure more than half of localized OGS cases, the unique challenges faced by resource-limited countries like India make this outcome difficult to achieve. Various questions in the management of OGS including role of high-dose methotrexate (HDMTX) in neoadjuvant setting, triplet vs doublet chemotherapy, intensification of chemotherapy based on response in setting of doublet, and indigenous prosthesis in setting of limb salvage need to be defined. Similarly, in the metastatic and recurrent setting, questions regarding intent of treatment, indications of chemotherapy, timing of surgery, and role of targeted therapies need clarification. Lack of randomized trials from India makes definite conclusions difficult, but an attempt can be made to define the best approach in the Indian scenario from available evidence. Hence, a critical review of literature from India and the West was done to define possible management approaches and highlight the lacuna for future research. [ABSTRACT FROM AUTHOR]

Visceral leishmaniasis (VL) is endemic in many parts of India. Rarely, it may be complicated by hemophagocytic lymphohistiocytosis (HLH) that has varied presentation and course. We describe two cases of VL complicated by HLH that were markedly different in clinical presentation, course and management. First case presented with Fever of unknown origin whereas second case had fever with severe bleeding manifestations. VL was diagnosed by bone marrow aspiration and serum rk39 immunodiagnostic test respectively in these cases. HLH was diagnosed by HLH 2004 diagnostic criteria. VL was treated by intravenous amphotericin B in both cases. HLH was managed by treating primary disease in the first case whereas steroid was given for management in the second case. High index of suspicion is crucial for early diagnosis of HLH to reduce morbidity and mortality. [ABSTRACT FROM AUTHOR]