PURPOSE Metaiodobenzylguanidine (MIBG) scans are a radionucleotide imaging modality that undergo Curie scoring to semiquantitatively assess neuroblastoma burden, which can be used as a marker of therapy response. We hypothesized that a convolutional neural network (CNN) could be developed that uses diagnostic MIBG scans to predict response to induction chemotherapy. METHODS We analyzed MIBG scans housed in the International Neuroblastoma Risk Group Data Commons from patients enrolled in the Children's Oncology Group high-risk neuroblastoma study ANBL12P1. The primary outcome was response to upfront chemotherapy, defined as a Curie score ≤ 2 after four cycles of induction chemotherapy. We derived and validated a CNN using two-dimensional whole-body MIBG scans from diagnosis and evaluated model performance using area under the receiver operating characteristic curve (AUC). We also developed a clinical classification model to predict response on the basis of age, stage, and MYCN amplification. RESULTS Among 103 patients with high-risk neuroblastoma included in the final cohort, 67 (65%) were responders. Performance in predicting response to upfront chemotherapy was equivalent using the CNN and the clinical model. Class-activation heatmaps verified that the CNN used areas of disease within the MIBG scans to make predictions. Furthermore, integrating predictions using a geometric mean approach improved detection of responders to upfront chemotherapy (geometric mean AUC 0.73 v CNN AUC 0.63, P < .05; v clinical model AUC 0.65, P < .05). CONCLUSION We demonstrate feasibility in using machine learning of diagnostic MIBG scans to predict response to induction chemotherapy for patients with high-risk neuroblastoma. We highlight improvements when clinical risk factors are also integrated, laying the foundation for using a multimodal approach to guiding treatment decisions for patients with high-risk neuroblastoma.
We read with interest the recent report in Blood by Griffin et al, 1 which provided a detailed description of the topographical immune landscape of T-cell/histiocyte-rich large B-cell lymphoma (T/HRLBCL) and implicated the programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) pathway as a key driver of immune escape in this disease. T/HRLBCL is an uncommon variant of diffuse large B-cell lymphoma (DLBCL) that frequently presents at advanced stages with extranodal involvement in young to middle-aged men. 2 T/HRLBCL shares molecular and genomic characteristics with nodular lymphocytepredominant Hodgkin lymphoma, 3,4 and the T/HRLBCL environment is also reminiscent of classical Hodgkin lymphoma. For instance, in contrast to most DLBCLs, which appear histologically as sheets of malignant B cells, T/HRLBCL is characterized by rare tumor cells scattered among a dense background of reactive T cells and macrophages (histiocytes).
In addition to being a major source of cancer-related pain, metastatic osseous lesions are frequently at risk for pathologic fracture and its accompanying morbidity. While bony metastases are commonly thought of as occurring within the vertebral column, over 80% are found outside the spine. Percutaneous interventional treatment options for nonspinal metastases offer a broad array of minimally invasive, image-guided procedures that are rapidly effective, reduce the need for opioids, and often work in complementary fashion with adjunct treatments in radiation oncology, orthopaedic surgery, and/or medical oncology. This article presents an approach to assess extraspinal metastases, reviews available interventional techniques in use today, and offers example cases as an introductory primer to the thought process used for selecting the appropriate interventional treatment.
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