Optimal index for detecting splenic involvement on 18F-fluorodeoxyglucose positron emission tomography/computed tomography imaging in diffuse large B-cell lymphoma.

Accurate clinical staging is important in diffuse large B-cell lymphoma (DLBCL) to adapt to optimal therapy. Splenic involvement of DLBCL has been recently more detectable with the advancement of a diagnostic scan by 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT). Our clinical question is whether splenic involvement was adequately diagnosed by FDG-PET/CT imaging. This retrospective study aimed to determine the optimal index for evaluating splenic involvement in patients with DLBCL. Patients with newly diagnosed DLBCL who were examined with FDG-PET/CT at diagnosis and the end of induction chemotherapy (EOI) was enrolled. The splenic involvement with the splenic FDG uptake value higher than that of the liver at diagnosis or with the decrease of splenic uptake at EOI by visual evaluation was evaluated as positive. The calculative evaluation of splenic involvement, based on the data of standardized uptake value (SUV) of the spleen, used maximum SUV (SUVmax), mean SUV (SUVmean), spleen total lesion glycolysis (spleen TLG), and spleen length. A change in each index following induction chemotherapy was expressed as an index. Receiver operating characteristic analysis was used to set the cutoff value for each index. This study included 52 patients. Spleen TLG (0.904) showed the best accuracy, followed by SUVmax (0.885) and SUVmean (0.885), among the 5 indexes for splenic involvement at diagnosis. Splenic involvement was predicted with a higher accuracy level (0.923) when selecting the cases with values higher than the cutoff level on both spleen TLG and SUVmax. The decision at EOI was more suitable by selecting both positive cases of ∆ TLG and ∆ SUVmax. Obtaining both the positive spleen TLG and SUVmax is recommended at diagnosis to predict splenic involvement. The assessment by ∆ spleen TLG and ∆ SUVmax seems to be optimal.

Monitoring the gasification area and its behavior in underground coal gasification by acoustic emission technique instead of temperature measurement.

Underground Coal Gasification (UCG) requires monitoring of the gasification area because the gasification process is invisible and the reaction temperature exceeds 1000 °C. Many fracturing events that occurred due to coal heating can be captured with Acoustic Emission (AE) monitoring technique during UCG. However, the temperature conditions to generate fracturing events during UCG have not yet been clarified. Therefore, the coal heating experiment and small-scale UCG experiment are conducted by measuring the temperature and AE activities in this research to examine the applicability of the AE technique instead of temperature measurement as a monitoring method during UCG. As a result, many fracturing events are generated when the temperature of coal is changed drastically, especially during coal gasification. Besides, AE events increase in the sensor near the heat source and AE sources are expanded widely with the expansion of the high-temperature region. AE monitoring is an effective technique for the estimation of the gasification area during UCG instead of temperature monitoring.

Deep learning model for the automatic classification of COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy: a multi-center retrospective study.

This retrospective study aimed to develop and validate a deep learning model for the classification of coronavirus disease-2019 (COVID-19) pneumonia, non-COVID-19 pneumonia, and the healthy using chest X-ray (CXR) images. One private and two public datasets of CXR images were included. The private dataset included CXR from six hospitals. A total of 14,258 and 11,253 CXR images were included in the 2 public datasets and 455 in the private dataset. A deep learning model based on EfficientNet with noisy student was constructed using the three datasets. The test set of 150 CXR images in the private dataset were evaluated by the deep learning model and six radiologists. Three-category classification accuracy and class-wise area under the curve (AUC) for each of the COVID-19 pneumonia, non-COVID-19 pneumonia, and healthy were calculated. Consensus of the six radiologists was used for calculating class-wise AUC. The three-category classification accuracy of our model was 0.8667, and those of the six radiologists ranged from 0.5667 to 0.7733. For our model and the consensus of the six radiologists, the class-wise AUC of the healthy, non-COVID-19 pneumonia, and COVID-19 pneumonia were 0.9912, 0.9492, and 0.9752 and 0.9656, 0.8654, and 0.8740, respectively. Difference of the class-wise AUC between our model and the consensus of the six radiologists was statistically significant for COVID-19 pneumonia (p value = 0.001334). Thus, an accurate model of deep learning for the three-category classification could be constructed; the diagnostic performance of our model was significantly better than that of the consensus interpretation by the six radiologists for COVID-19 pneumonia.

Phase I/II Study of Radiofrequency Ablation for Painful Bone Metastases: Japan Interventional Radiology in Oncology Study Group 0208.

PURPOSE: A prospective multicenter phase I/II trial was performed to evaluate the clinical safety and efficacy of radiofrequency ablation (RFA) for metastatic bone tumors. MATERIALS AND METHODS: Thirty-three patients (27 men, 6 women, mean age 61 years) with metastatic bone tumors were enrolled. In phase I, nine patients were enrolled, and the safety of RFA was evaluated. In phase II, 23 patients were included, and an intent-to-treat analysis was performed. The primary endpoint was to evaluate the treatment's safety. The secondary endpoint was to evaluate the efficacy of pain relief at 1 week after RFA. RESULTS: RFA was performed in 32 of 33 enrolled patients. No serious complications were observed during the phase I, so phase II was performed. Four patients exhibited adverse events, including one case each of Grade 3 pain and, Grade 2 hypotension, and one patient developed Grade 1 burns at the grounding pad and puncture site. One patient died of liver failure on day 7 after RFA due to the progression of the primary lesion. The efficacy was excellent (no increase in analgesic dosage, post-RFA VAS score of 0-2 or decreased by not less than 5 compared to before RFA) in 20 patients (60.6%), good (no increase in analgesic dosage, post-RFA VAS score decreased by not less than 2 but by < 5 compared to before RFA) in 3 (9.1%), and poor in 10 patients (30.3%). Thus, the response rate was 69.7%. CONCLUSION: RFA is a safe and effective method for treating painful metastatic bone tumors.

Endovascular Aneurysm Repair with Balloon Thrombectomy for Acute Thrombosis of Abdominal Aortic Aneurysm.

Acute occlusion of abdominal aortic aneurysm (AAA) is a rare complication and is usually treated with surgical reconstruction. We present a case of acute AAA occlusion that was successfully treated by endovascular aneurysm repair (EVAR) with Fogarty balloon thrombectomy. A 77-year-old man with a history of acute myocardial ischemia presented with limb weakness and coldness. Contrast-enhanced computed tomography showed a 42-mm-diameter infrarenal AAA that was completely thrombosed in the distal portion. The proximal neck of the aneurysm was patent, and its shape was suitable for EVAR. Therefore, we performed balloon thrombectomy of the aortoiliac thrombus that was followed by EVAR. EVAR can be a less invasive alternative than traditional treatment for acute occlusion of AAA.

High resolution CT findings of pulmonary epithelioid hemangioendothelioma: unusual manifestations in 2 cases.

Pulmonary epithelioid hemangioendotheliomas (PEH), also known as intravascular sclerosing bronchoalveolar tumor, is a rare vascular tumor of the lung common among young women. Primitive lumena lined by single cells is the characteristic pathologic feature. The endothelial nature of these cells is confirmed by positive staining with factor VIII and CD34. PEH usually presents as single or multiple pulmonary nodules. The present report describes high resolution CT (HRCT) findings of 2 cases with unusual manifestations of PEH. One case was a 54-year-old woman with multiple pulmonary nodules with irregular thickening of both the bronchovascular bundles and perilobular structures, representing intensive lymphangitic spread on HRCT. The other was an 18-year-old woman who had multiple minute peripheral nodules in the lungs bilaterally. These HRCT findings demonstrated the presence of tumor nodules in the lymphatic spaces, which is quite an unusual histologic presentation for this tumor. Both cases also showed hepatic lesions on abdominal CT; the former showing hypoattenuating masses with coarse calcifications and the latter showing multiple tiny calcifications in the hepatic parenchyma. Recognition of these features in the appropriate clinical setting may allow the clinician and the pathologist to consider this rare tumor.

[Diagnostic imaging--recent progress].

Current advances in the diagnostic imaging for lung cancer includes multidetector-row CT (MDCT), lung cancer screening using low-dose MDCT and fluorodeoxyglucose positron emission tomography (FDG-PET) imaging. There is no question about the clinical usefulness of MDCT, and the further development of the hardware and the software of MDCT will open new horizons for CT diagnosis. PET is not an alternative modality to CT but a supplementary one, which adds metabolic information to the morphology. Recently, experimental research on the refraction imaging of human lung specimens has been performed with synchrotron radiation. With progressive refinement, this technique may come to have some practical purpose in diagnosing lung cancer in vivo.