Effects of the Coronavirus disease 2019 pandemic on mortality in patients with lung cancer: A multiple mediation analysis in Japan.

COVID-19 pandemic has had a substantial effect on healthcare systems worldwide, including the care of patients with lung cancer. The impact of healthcare disruptions and behavioral changes on lung cancer mortality is unclear. Patients newly diagnosed with lung cancer during the pandemic period 2020-2021 were compared with those diagnosed in the pre-pandemic 2018-2019. The primary outcome was all-cause mortality within 1 year. Cox proportional hazards regression analyses were conducted to estimate the changes in mortality between pandemic and pre-pandemic. Multiple mediation analyses were performed to determine the factors that accounted for the changes in mortality. In total, 5785 patients with lung cancer were included in this study. The overall mortality rate was significantly higher during the pandemic compared with the pre-pandemic (crude hazard ratio [HR]: 1.19, 95% confidence interval [CI]: 1.05, 1.29). Mediation analyses showed that not receiving tumor-directed treatment, diagnosis at an older age, and decreased diagnosis through cancer screening significantly accounted for 17.5% (95%CI: 4.2, 30.7), 13.9% (95%CI: 0.8, 27.0), and 12.4% (95%CI: 3.0, 21.8) of the increased mortality, respectively. This study revealed a significant increase in mortality risk in patients with lung cancer who have not received tumor-directed treatment or cancer screening, despite potential selection bias for follow-up status. Efforts should be focused on ensuring timely access to healthcare services, optimizing treatment delivery, and addressing the unique challenges faced by patients with lung cancer during the pandemic to mitigate the impact of the pandemic on lung cancer outcomes and provide clinical care to vulnerable populations.

Assessing the Influence of the COVID-19 Pandemic on Gastric Cancer Mortality Risk.

BACKGROUND: The global impact of the coronavirus disease 2019 (COVID-19) pandemic on public health has been significant. Upper gastrointestinal endoscopy for screening and diagnosis decreased along with new gastric cancer (GC) diagnoses. METHODS: This study assesses how the pandemic affected GC mortality using data from Hiroshima Prefecture, comparing mortality rates between patients diagnosed during the pandemic (2020 and 2021) and pre-pandemic (2018 and 2019) periods. The crude hazard ratios (HRs) and HRs adjusted for age, sex, clinical stage, treatment status, and travel distance to the nearest GC screening facility were estimated using Cox regression models. Subgroup and sensitivity analyses were also performed. RESULTS: A total of 9571 patients were diagnosed, with 4877 eligible for follow-up. The median age was 74 years, and 69% were male. The median follow-up period was 157 days, with events per 1000 person-years at 278 and 374 in the pre-pandemic and pandemic periods, respectively (crude HR, 1.37; adjusted HR, 1.17). The sensitivity and subgroup analyses yielded consistent results. CONCLUSIONS: The COVID-19 pandemic increased mortality risk in patients with GC. Further studies are required to observe long-term outcomes and identify the disparities contributing to the increased mortality risk.

Impact of the COVID-19 pandemic on the mortality among patients with colorectal cancer in Hiroshima, Japan: A large cancer registry study.

BACKGROUND: This retrospective cohort study aimed to evaluate the impact of the COVID-19 pandemic on colorectal cancer care and mortality using a large cancer registry in Hiroshima Prefecture, Japan. The study aimed to estimate the all-cause mortality rates within 1 year of diagnosis among colorectal cancer patients diagnosed during the pandemic period (2020 and 2021) compared to those diagnosed during the pre-pandemic period (2018 and 2019). METHODS: The day of diagnosis was set as Day 0 and Cox regression models were utilized to estimate crude hazard ratios (HRs) and adjusted HRs, accounting for age, sex, cancer stage, and treatment status. Two sensitivity analyses of overall survival were performed with different cutoffs of the pre-pandemic/pandemic periods and year-to-year comparisons. Subgroup analyses were performed using likelihood ratio tests. RESULTS: A total of 15,085 colorectal cancer patients were included, with 6499 eligible for follow-up. A median age of included patients was 72 years old, of which 59% were male. The distribution of cancer stages showed little variation between the pre-pandemic and pandemic periods. With a median follow-up of 177 days, the number of events was 316/3111 (173 events per 1000 person-years [E/1000PY], 95% confidence interval [CI]: 154-192 E/1000PY) in the pre-pandemic period, and 326/2746 (245 E/1000PY, 95% CI: 220-274 E/1000PY) in the pandemic period (crude HR: 1.42, 95% CI: 1.22-1.66; adjusted HR: 1.25, 95% CI: 1.07-1.46). The two sensitivity analyses and subgroup analyses consistently supported these findings. CONCLUSIONS: The study revealed an increased colorectal cancer mortality during the pandemic period, suggesting a continuous impact of the COVID-19 pandemic on the known and unknown risk factors for colorectal cancer for several years. Further studies are necessary to mitigate the adverse effects on patient outcomes.

Virtual Interpolation Images of Tumor Development and Growth on Breast Ultrasound Image Synthesis With Deep Convolutional Generative Adversarial Networks.

OBJECTIVES: We sought to generate realistic synthetic breast ultrasound images and express virtual interpolation images of tumors using a deep convolutional generative adversarial network (DCGAN). METHODS: After retrospective selection of breast ultrasound images of 528 benign masses, 529 malignant masses, and 583 normal breasts, 20 synthesized images of each were generated by the DCGAN. Fifteen virtual interpolation images of tumors were generated by changing the value of the input vector. A total of 60 synthesized images and 20 virtual interpolation images were evaluated by 2 readers, who scored them on a 5-point scale (1, very good; to 5, very poor) and then answered whether the synthesized image was benign, malignant, or normal. RESULTS: The mean score of overall quality for synthesized images was 3.05, and that of the reality of virtual interpolation images was 2.53. The readers classified the generated images with a correct answer rate of 92.5%. CONCLUSIONS: A DCGAN can generate high-quality synthetic breast ultrasound images of each pathologic tissue and has the potential to create realistic virtual interpolation images of tumor development.

Granulocyte Colony-stimulating Factor-induced Aortitis with Lung Injury, Splenomegaly, and a Rash During Treatment for Recurrent Extraosseous Mucinous Chondrosarcoma.

We herein report a case of aortitis induced by granulocyte colony-stimulating factor (G-CSF) that coincided with lung injury, splenomegaly, and cutaneous manifestations during treatment for recurrent extraosseous mucinous chondrosarcoma. Computed tomography revealed large-vessel vasculitis, splenomegaly, and pulmonary interstitial changes. Treatment with prednisolone was successful. Because sarcoma is a rare disease, this case is valuable for showing clinicians that G-CSF preparations could cause aortitis regardless of the patient's underlying diseases or therapeutic pharmacological backgrounds.

Quantitative measures of vortex veins in the posterior pole in eyes with pachychoroid spectrum diseases.

Pachychoroid spectrum diseases have attracted increasing attention, though their pathophysiology has yet to be fully elucidated. In this study, we assessed the vascular diameters of vortex veins in pachychoroid spectrum diseases such as central serous chorioretinopathy (CSC), pachychoroid neovasculopathy without polypoidal lesions (PNV), and pachychoroid neovasculopathy with polypoidal lesions (polypoidal choroidal vasculopathy: PCV). In a retrospective case series of 94 eyes with CSC, 60 eyes with PNV and 57 with PCV, we binarized en face optical coherence tomography (OCT) images of choroidal vortex veins and analyzed the mean diameter of vortex veins. The presence of anastomosis between the superior and inferior vortex veins and central choroidal thickness (CCT) were also evaluated using OCT images. CSC showed significantly larger mean diameter of vortex veins than PCV (P < 0.05). Anastomosis between superior and inferior vortex veins was observed in over 90% of eyes with each pachychoroid spectrum disease. The patients with CSC were the youngest, followed by PNV patients, and then patients with PCV. The largest CCT values were observed in CSC eyes, followed by PNV eyes, and then PCV eyes. CCT correlated with the mean diameter of vortex veins (rs = 0.51, P < 0.01). These findings suggest that congestion of vortex veins might show gradual amelioration corresponding to the development of anastomosis between the superior and inferior vortex veins during the course of progression of pachychoroid spectrum diseases. Moreover, the mean diameter of vortex veins can be used as a parameter indicating choroidal congestion.

Feasibility of ultrafast dynamic magnetic resonance imaging for the diagnosis of axillary lymph node metastasis: A case report.

A 74 year old Japanese woman was diagnosed with invasive breast carcinoma. Her axillary lymph node was slightly swollen and had a short-axis diameter of 8 mm, but fine-needle aspiration did not lead to the diagnosis of metastasis. Subsequent 18F-fluorodeoxyglucose positron emission tomography/computed tomography showed no abnormal accumulation on the lymph node. Ultrafast dynamic magnetic resonance imaging yielded a very fast contrast enhancement like that of the primary lesion based on which we suspected lymph node metastasis. To our knowledge, this is the first report that shows that ultrafast imaging has contributed to the diagnosis of axillary lymph node metastasis.

Senescent hepatic stellate cells caused by deoxycholic acid modulates malignant behavior of hepatocellular carcinoma.

PURPOSE: Deoxycholic acid (DCA), a secondary bile acid, is reportedly increased in the serum of patients with nonalcoholic steatohepatitis and animals with experimentally induced hepatocellular carcinoma (HCC), but its contribution to malignant behaviors of HCC has not been precisely clarified. This study aimed to examine the effect of DCA on hepatic stellate cells (HSCs), a major component of nonparenchymal cells in the liver, and its subsequent indirect effect on HCC cells. METHODS: LX2 cells, a human HSC line, were treated with DCA in vitro. Then, HuH7 cells, a human hepatoma cell line, were incubated in conditioned media of DCA-treated LX2 to investigate the subsequent effect focusing on malignant behaviors. RESULTS: DCA resulted in cellular senescence in LX2 with the decreased cell proliferation via cell cycle arrest at G0/1 phase, together with the induction of senescence-associated secretory phenotype (SASP) factors. To investigate the influence of SASP factors secreted by HSCs in response to DCA, HCC cells were treated with conditioned media that promoted cell migration and invasion via induction of epithelial mesenchymal transition. These changes were attenuated in the presence of neutralizing antibody against IL8 or TGFß. Pathological analysis of surgical specimens from HCC patients revealed that senescent HSCs were detected in the stroma surrounding HCC. CONCLUSION: Our data suggest an important role of HSC senescence caused by DCA for the malignant biological behaviors of HCC via induction of SASP factors, particularly IL8 and TGFß.

Efficient Anomaly Detection with Generative Adversarial Network for Breast Ultrasound Imaging.

We aimed to use generative adversarial network (GAN)-based anomaly detection to diagnose images of normal tissue, benign masses, or malignant masses on breast ultrasound. We retrospectively collected 531 normal breast ultrasound images from 69 patients. Data augmentation was performed and 6372 (531 × 12) images were available for training. Efficient GAN-based anomaly detection was used to construct a computational model to detect anomalous lesions in images and calculate abnormalities as an anomaly score. Images of 51 normal tissues, 48 benign masses, and 72 malignant masses were analyzed for the test data. The sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of this anomaly detection model were calculated. Malignant masses had significantly higher anomaly scores than benign masses (p < 0.001), and benign masses had significantly higher scores than normal tissues (p < 0.001). Our anomaly detection model had high sensitivities, specificities, and AUC values for distinguishing normal tissues from benign and malignant masses, with even greater values for distinguishing normal tissues from malignant masses. GAN-based anomaly detection shows high performance for the detection and diagnosis of anomalous lesions in breast ultrasound images.

Feasibility of new fat suppression for breast MRI using pix2pix.

PURPOSE: To generate and evaluate fat-saturated T1-weighted (FST1W) image synthesis of breast magnetic resonance imaging (MRI) using pix2pix. MATERIALS AND METHODS: We collected pairs of noncontrast-enhanced T1-weighted an FST1W images of breast MRI for training data (2112 pairs from 15 patients), validation data (428 pairs from three patients), and test data (90 pairs from 30 patients). From the original images, 90 synthetic images were generated with 50, 100, and 200 epochs using pix2pix. Two breast radiologists evaluated the synthetic images (from 1 = excellent to 5 = very poor) for quality of fat suppression, anatomic structures, artifacts, etc. The average score was analyzed for each epoch and breast density. RESULTS: The synthetic images were scored from 2.95 to 3.60; the best was reduction in artifacts when using 100 epochs. The average overall quality scores for fat suppression were 3.63 at 50 epochs, 3.24 at 100 epochs, and 3.12 at 200 epochs. In the analysis for breast density, each score was significantly better for nondense breasts than for dense breasts; the average score was 2.88-3.18 for nondense breasts and 3.03-3.42 for dense breasts (P = 0.000-0.042). CONCLUSION: Pix2pix had the potential to generate FST1W synthesis for breast MRI.

Vortex Vein Anastomosis at the Watershed in Pachychoroid Spectrum Diseases.

PURPOSE: To evaluate the vascular changes in vortex veins at the posterior pole in pachychoroid spectrum diseases, including central serous chorioretinopathy (CSC), pachychoroid neovasculopathy without polypoidal lesions (PNV), and pachychoroid neovasculopathy with polypoidal lesions (polypoidal choroidal vasculopathy [PCV]). DESIGN: Retrospective case-control study. PARTICIPANTS: Ninety-two eyes of 89 patients with CSC, 61 eyes of 59 patients with PNV, 63 eyes of 61 patients with PCV, and 25 healthy control eyes of 25 age- and gender-matched participants for each pachychoroid spectrum disease. METHODS: Clinical records of patients with pachychoroid spectrum diseases and healthy controls were reviewed. Multimodal images of each group were analyzed. Swept-source OCT was performed to obtain B-mode and en face images in patients with pachychoroid spectrum diseases and healthy controls. All patients underwent fluorescein angiography, indocyanine green angiography, and OCT. MAIN OUTCOME MEASURES: Vortex vein anastomosis at the watershed, determined using en face OCT, and central choroidal thickness (CCT), measured using B-mode OCT, were examined in patients and healthy controls. Patient ages also were taken into consideration. RESULTS: Patients with CSC were the youngest, followed by patients with PNV, and then those with PCV (P < 0.01, CSC vs. PNV and PNV vs. PCV), whereas CSC eyes showed the highest CCT values, followed by the PNV and then the PCV eyes (P < 0.01, CSC vs. PNV; P < 0.05, PNV vs. PCV). Central choroidal thickness was significantly greater in pachychoroid spectrum diseases than in healthy controls. No significant CCT differences were found among healthy controls. Anastomosis between superior and inferior vortex veins was observed in more than 90% of eyes with pachychoroid spectrum diseases, making this finding significantly more frequent than in healthy controls (P < 0.01, each pachychoroid spectrum disease vs. control). Polypoidal choroidal vasculopathy showed a significantly higher rate of anastomosis than CSC (P < 0.05). CONCLUSIONS: Anastomosis between superior and inferior vortex veins was found to be a common feature in pachychoroid spectrum diseases. Longstanding vortex vein congestion may lead to the development of pachychoroid spectrum diseases. Choroidal congestion may be compensated for by new drainage routes formed via vortex vein anastomosis.

Classification of Breast Masses on Ultrasound Shear Wave Elastography using Convolutional Neural Networks.

We aimed to use deep learning with convolutional neural networks (CNNs) to discriminate images of benign and malignant breast masses on ultrasound shear wave elastography (SWE). We retrospectively gathered 158 images of benign masses and 146 images of malignant masses as training data for SWE. A deep learning model was constructed using several CNN architectures (Xception, InceptionV3, InceptionResNetV2, DenseNet121, DenseNet169, and NASNetMobile) with 50, 100, and 200 epochs. We analyzed SWE images of 38 benign masses and 35 malignant masses as test data. Two radiologists interpreted these test data through a consensus reading using a 5-point visual color assessment (SWEc) and the mean elasticity value (in kPa) (SWEe). Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated. The best CNN model (which was DenseNet169 with 100 epochs), SWEc, and SWEe had a sensitivity of 0.857, 0.829, and 0.914 and a specificity of 0.789, 0.737, and 0.763 respectively. The CNNs exhibited a mean AUC of 0.870 (range, 0.844-0.898), and SWEc and SWEe had an AUC of 0.821 and 0.855. The CNNs had an equal or better diagnostic performance compared with radiologist readings. DenseNet169 with 100 epochs, Xception with 50 epochs, and Xception with 100 epochs had a better diagnostic performance compared with SWEc (P = 0.018-0.037). Deep learning with CNNs exhibited equal or higher AUC compared with radiologists when discriminating benign from malignant breast masses on ultrasound SWE.

Detection and Diagnosis of Breast Cancer Using Artificial Intelligence Based assessment of Maximum Intensity Projection Dynamic Contrast-Enhanced Magnetic Resonance Images.

We aimed to evaluate an artificial intelligence (AI) system that can detect and diagnose lesions of maximum intensity projection (MIP) in dynamic contrast-enhanced (DCE) breast magnetic resonance imaging (MRI). We retrospectively gathered MIPs of DCE breast MRI for training and validation data from 30 and 7 normal individuals, 49 and 20 benign cases, and 135 and 45 malignant cases, respectively. Breast lesions were indicated with a bounding box and labeled as benign or malignant by a radiologist, while the AI system was trained to detect and calculate possibilities of malignancy using RetinaNet. The AI system was analyzed using test sets of 13 normal, 20 benign, and 52 malignant cases. Four human readers also scored these test data with and without the assistance of the AI system for the possibility of a malignancy in each breast. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were 0.926, 0.828, and 0.925 for the AI system; 0.847, 0.841, and 0.884 for human readers without AI; and 0.889, 0.823, and 0.899 for human readers with AI using a cutoff value of 2%, respectively. The AI system showed better diagnostic performance compared to the human readers (p = 0.002), and because of the increased performance of human readers with the assistance of the AI system, the AUC of human readers was significantly higher with than without the AI system (p = 0.039). Our AI system showed a high performance ability in detecting and diagnosing lesions in MIPs of DCE breast MRI and increased the diagnostic performance of human readers.

One-year outcomes of half-fluence photodynamic therapy combined with intravitreal injection of aflibercept for pachychoroid neovasculopathy without polypoidal lesions.

PURPOSE: To evaluate the 1-year efficacy of half-fluence photodynamic therapy (HFPDT) combined with intravitreal aflibercept injection on treatment-naïve pachychoroid neovasculopathy (PNV) without polypoidal lesions. STUDY DESIGN: Retrospective, interventional case series PATIENTS AND METHODS: We retrospectively studied 21 eyes with treatment-naïve PNV and assessed the best-corrected visual acuity (BCVA), central macular thickness (CMT), central choroidal thickness (CCT), pachyvessel vertical diameter, and choroidal neovascularization thickness (CNVT) at the fovea over a 12-month period. RESULTS: The median BCVA was 0.15 at baseline, 0.00 (P < .05) at 3 months, 0.05 at 6 months, and -0.08 (P < .05) at 12 months. The BCVA was significantly improved at 3 months and 12 months as compared with the baseline BCVA. The median CMT was 230 µm at baseline, 140 µm (P < .01) at 3 months, 150 µm (P < .01) at 6 months, and 150 µm (P < .01) at 12 months. The median CCT was 386 µm at baseline, 347 µm (P < .01) at 3 months, 331 µm (P < .01) at 6 months, and 352 µm (P < .01) at 12 months. The median pachyvessel vertical diameter was 309 µm at baseline, 246 µm (P < .01) at 3 months, 232 µm (P < .01) at 6 months, and 242 µm (P < .01) at 12 months. The median CNVT was 28 µm at baseline, 17 µm (P < .01) at 3 months, 19 µm (P < .05) at 6 months, and 21 µm (P < .05) at 12 months. The CMT, CCT, pachyvessel vertical diameter, and CNVT were significantly decreased at 3, 6, and 12 months as compared with those at baseline. Whilst 17 eyes (81.0%) showed no signs of CNV recurrence during the 12-month period, 4 eyes (19.0%) required additional combination therapy. CONCLUSIONS: HFPDT combined with intravitreal aflibercept injection may effectively improve BCVA and ameliorate exudative changes in eyes with PNV without polypoidal lesions for up to 1 year.

Breast Ultrasound Image Synthesis using Deep Convolutional Generative Adversarial Networks.

Deep convolutional generative adversarial networks (DCGANs) are newly developed tools for generating synthesized images. To determine the clinical utility of synthesized images, we generated breast ultrasound images and assessed their quality and clinical value. After retrospectively collecting 528 images of 144 benign masses and 529 images of 216 malignant masses in the breasts, synthesized images were generated using a DCGAN with 50, 100, 200, 500, and 1000 epochs. The synthesized (n = 20) and original (n = 40) images were evaluated by two radiologists, who scored them for overall quality, definition of anatomic structures, and visualization of the masses on a five-point scale. They also scored the possibility of images being original. Although there was no significant difference between the images synthesized with 1000 and 500 epochs, the latter were evaluated as being of higher quality than all other images. Moreover, 2.5%, 0%, 12.5%, 37.5%, and 22.5% of the images synthesized with 50, 100, 200, 500, and 1000 epochs, respectively, and 14% of the original images were indistinguishable from one another. Interobserver agreement was very good (|r| = 0.708-0.825, p < 0.001). Therefore, DCGAN can generate high-quality and realistic synthesized breast ultrasound images that are indistinguishable from the original images.

Simultaneous comparison between strain and shear wave elastography of breast masses for the differentiation of benign and malignant lesions by qualitative and quantitative assessments.

PURPOSE: To compare the addition of diagnostic strain elastography (SE) and shear wave elastography (SWE) values to the conventional B-mode ultrasonography in differentiating between benign and malignant breast masses by qualitative and quantitative assessments. MATERIALS AND METHODS: B-mode ultrasound, SE, and SWE were simultaneously performed using one ultrasound system in 148 breast masses; 88 of them were malignant. The breast imaging reporting and data system category in the B-mode, Tsukuba score (SETsu), Fat-Lesion-Ratio (SEFLR) in SE, and five-point color assessment (SWEcol) and elasticity values (SWEela) in SWE were assessed. The results were compared using the area under the receiver-operating characteristic curve (AUC). RESULT: The AUC for B-mode and each elastography were similar (B-mode, 0.889; SETsu, 0.885; SEFLR, 0.875; SWEcol, 0.881; SWEela, 0.885; P > 0.05). The combined sets between B-mode and either of the elastography technique showed good diagnostic performance (B-mode + SETsu, 0.903; B-mode + SEFLR, 0.909; B-mode + SWEcol, 0.919; B-mode + SWEela, 0.914). B-mode + SWEcol and B-mode + SWEela showed a higher AUC than B-mode alone (P = 0.026 and 0.029), and B-mode + SETsu and B-mode + SEFLR showed comparable AUC to B-mode alone (P = 0.196 and 0.085). There was no significant difference between qualitative and quantitative assessments for the combined sets of B-mode and elastography (P > 0.05). CONCLUSION: The addition of both SE and SWE to B-mode ultrasound improved the diagnostic performance with increased AUC, and especially SWE was more useful than SE, and no significant difference was found between qualitative and quantitative assessments.

Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network.

PURPOSE: We aimed to use deep learning with convolutional neural network (CNN) to discriminate between benign and malignant breast mass images from ultrasound. MATERIALS AND METHODS: We retrospectively gathered 480 images of 96 benign masses and 467 images of 144 malignant masses for training data. Deep learning model was constructed using CNN architecture GoogLeNet and analyzed test data: 48 benign masses, 72 malignant masses. Three radiologists interpreted these test data. Sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were calculated. RESULTS: The CNN model and radiologists had a sensitivity of 0.958 and 0.583-0.917, specificity of 0.925 and 0.604-0.771, and accuracy of 0.925 and 0.658-0.792, respectively. The CNN model had equal or better diagnostic performance compared to radiologists (AUC = 0.913 and 0.728-0.845, p = 0.01-0.14). CONCLUSION: Deep learning with CNN shows high diagnostic performance to discriminate between benign and malignant breast masses on ultrasound.

An Atypical Case of Non-asthmatic Eosinophilic Granulomatosis with Polyangiitis Finally Diagnosed by Tissue Biopsy.

A 78-year-old woman with fever of unknown origin that had persisted for 3 months, systemic edema, and cervical lymphadenopathy was admitted to our hospital. Skin purpura and jaw claudication were subsequently observed. Histopathological examinations of the lymph nodes, skin, and temporal artery revealed findings characteristic of eosinophilic granulomatosis with polyangiitis (EGPA). However, she had no past medical history of asthma with modest eosinophilia. Although EGPA is a systemic vasculitis characterized by asthma and eosinophilia, various limited forms have been described. This was therefore considered to be an atypical form of non-asthmatic EGPA complicating with temporal arteritis (TA) diagnosed by tissue biopsy.

The feasibility of using 18F-FDG-PET/CT in patients with mucinous breast carcinoma.

PURPOSE: This study investigated the correlation between fluorine-18-fluorodeoxyglucose (F-FDG)-PET/computed tomography (CT) and clinicopathological factors in patients with mucinous breast carcinoma and assessed the feasibility of using F-FDG-PET/CT in evaluating tumors. PATIENTS AND METHODS: We retrospectively examined 42 consecutive patients with pathologically proven mucinous breast carcinoma who preoperatively underwent F-FDG-PET/CT. In addition, we compared F-FDG uptake with clinicopathological characteristics. RESULTS: F-FDG uptake was observed in 39 (92.9%) lesions. The maximum standardized uptake value (SUVmax) (mean±SD) of all mucinous carcinoma, pure type, and mixed type was 2.3±1.3 (range: 1.0-5.1), 1.9±0.9 (range: 1.0-3.5), and 3.2±1.3 (range: 1.4-5.1), respectively. The mixed type had a significantly higher F-FDG uptake than the pure type (P=0.006). In addition, the sensitivity, specificity, accuracy, and area under the curve for distinguishing the pure type from the mixed type were 61.5, 89.7, 81.0, and 0.76, respectively (cutoff value: SUVmax>3.0). Furthermore, SUVmax correlated significantly with the high nuclear grade (P=0.010) and the presence of axillary lymph node metastasis (P=0.017). CONCLUSION: F-FDG uptake efficiently distinguishes the pure type from the mixed type and may play a potential role in predicting the aggressiveness of mucinous breast carcinoma.

Osteogenic Lineage Commitment of Adipose-Derived Stem Cells Is Predetermined by Three-Dimensional Cell Accumulation on Micropatterned Surface.

Lineage commitment of stem cells is mainly regulated by their microenvironments, which comprise soluble growth factors, extracellular matrix, mechanical forces, and cell density. Although numerous studies have investigated stem cell response to these factors in two-dimensional (2D) culture, little is known about that in 3D culture. Here, we studied effects of 3D cell accumulation levels on the differentiation behavior of mesenchymal stem cells (MSCs) by using a micropatterned surface. After induction of 3D-cultured MSCs on the surface, their osteogenic differentiation was significantly promoted, while adipogenic differentiation was not. This differentiation behavior of densely packed MSCs in 3D culture is unlike that in 2D culture. Moreover, to determine the contributing factor of this commitment, the relationship between 3D cell accumulation levels and their differentiation potential was studied before differentiation induction. A series of MSCs with varied 3D accumulation levels were constructed on the micropatterned surface, where the accumulated MSCs were not in hypoxic environment. Interestingly, with increasing 3D accumulation levels, MSCs enhanced their osteogenic potential but repressed adipogenic potential in the gene expression level. These results suggest that preconditioned 3D microenvironments with high cell accumulation levels promote osteogenic differentiation of MSCs and their accumulation levels help in regulating MSC differentiation.