HSP47 in lung fibroblasts is a predictor of survival in fibrotic nonspecific interstitial pneumonia.

BACKGROUND: The histopathologic pattern is currently the most important prognostic marker for idiopathic interstitial pneumonia (IIP). However, more highly sensitive markers are now required. Heat shock protein (HSP) 47, a collagen-specific molecular chaperone, is involved in the processing and/or secretion of procollagens, and it has been demonstrated that HSP47 expression is significantly higher in the lung specimens of idiopathic UIP than in UIP associated with collagen vascular diseases (CVD). However, its expression in nonspecific interstitial pneumonia (NSIP), the other common pathological pattern of IIP, has not been well investigated. Therefore, the association between lung fibroblast HSP47 expression and prognosis in fibrotic NSIP was evaluated. METHODS: Surgical lung biopsy specimens of 63 patients [idiopathic fibrotic NSIP=19, fibrotic NSIP associated with CVD=9, idiopathic UIP=26, and UIP associated with CVD=9] were reviewed, and a score for lung fibroblast HSP47 expression was assigned. These patients\u27 clinical features and survival were also analyzed. RESULTS: There was no significant difference in HSP47 expression between idiopathic fibrotic NSIP and fibrotic NSIP associated with CVD. The idiopathic fibrotic NSIP patients with higher HSP47 expression levels in their lung specimens had a poorer prognosis than patients with lower HSP47 expression levels. CONCLUSIONS: The present results suggest that lung fibroblast HSP47 expression may be a useful new prognostic marker for idiopathic fibrotic nonspecific interstitial pneumonia

Reproduction of the Marine Debris Distribution in the Seto Inland Sea Immediately after the July 2018 Heavy Rains in Western Japan Using Multidate Landsat-8 Data

Understanding the spatiotemporal environment of the ocean after a heavy rain disaster is critical for satellite remote sensing research and disaster prevention. We attempted to reproduce changes in marine debris distributions using multidate data of Landsat-8 spectral reflectance acquired immediately after a heavy rain disaster in western Japan in July 2018. Data from cleaning ships were used for screening the marine debris area. As most of the target marine debris consisted of plant fragments, a method based on the corrected floating algae index (cFAI) was applied to Landsat-8 data. Data from cleaning ships clarify that most of the marine debris accumulated in the waters in the northern part of Aki Nada, a part of the Seto Inland Sea. The spectral characteristics of the corresponding marine debris spectral reflectance obtained from the Landsat-8 data were explained by the FAI with band 5 (central wavelength: 865 nm) as the maximum value. Unlike traditional FAI, cFAI eliminated the effect of background water turbidity. The Otsu method was effective for the automatic threshold determination for cFAI. Although Landsat-8 data have limited spatial resolution and observation frequency, these data were useful for understanding marine debris distribution after a heavy rain disaster

Laser Imaging Facilitates Early Detection of Synchronous Adenocarcinomas in Patients with Barrett’s Esophagus

Barrett’s adenocarcinoma may occur in multiple sites, and recurrence and metachronous lesions are the major problems with endoscopic resection. Therefore, early detection of such lesions is ideal to achieve complete resection and obtain improved survival rates with minimally invasive treatment. Laser imaging systems allow multiple modalities of endoscopic imaging by using white light laser, flexible spectral imaging color enhancement (FICE), blue laser imaging (BLI), and linked color imaging even at a distant view. However, the usefulness of these modalities has not been sufficiently reported regarding Barrett’s adenocarcinoma. Here, we report on a patient with three synchronous lesions followed by one metachronous lesion in a long segment with changes of Barrett’s esophagus, all diagnosed with this new laser endoscopic imaging system and enhanced by using FICE and/or BLI with high contrast compared with the surrounding mucosa. Laser endoscopic imaging may facilitate the detection of malignancies in patients with early Barrett’s adenocarcinoma

Automatic Segmentation of Pancreatic Tumors Using Deep Learning on a Video Image of Contrast-Enhanced Endoscopic Ultrasound

Background: Contrast-enhanced endoscopic ultrasound (CE-EUS) is useful for the differentiation of pancreatic tumors. Using deep learning for the segmentation and classification of pancreatic tumors might further improve the diagnostic capability of CE-EUS. Aims: The aim of this study was to evaluate the capability of deep learning for the automatic segmentation of pancreatic tumors on CE-EUS video images and possible factors affecting the automatic segmentation. Methods: This retrospective study included 100 patients who underwent CE-EUS for pancreatic tumors. The CE-EUS video images were converted from the originals to 90-s segments with six frames per second. Manual segmentation of pancreatic tumors from B-mode images was performed as ground truth. Automatic segmentation was performed using U-Net with 100 epochs and was evaluated with 4-fold cross-validation. The degree of respiratory movement (RM) and tumor boundary (TB) were divided into 3-degree intervals in each patient and evaluated as possible factors affecting the segmentation. The concordance rate was calculated using the intersection over union (IoU). Results: The median IoU of all cases was 0.77. The median IoUs in TB-1 (clear around), TB-2, and TB-3 (unclear more than half) were 0.80, 0.76, and 0.69, respectively. The IoU for TB-1 was significantly higher than that of TB-3 (p < 0.01). However, there was no significant difference between the degrees of RM. Conclusions: Automatic segmentation of pancreatic tumors using U-Net on CE-EUS video images showed a decent concordance rate. The concordance rate was lowered by an unclear TB but was not affected by RM

Impact of linked color imaging and blue laser imaging on the diagnosis of esophageal squamous cell carcinoma in iodine unstained areas

Abstract The pink color sign in iodine unstained areas is useful to differentiate esophageal squamous cell carcinoma (ESCC) from other lesions. However, some ESCCs have obscure color findings which affect the ability of endoscopists to differentiate these lesions and determine the resection line. Using white light imaging (WLI), linked color imaging (LCI) and blue laser imaging (BLI), 40 early ESCCs were retrospectively evaluated using images before and after iodine staining. Visibility scores for ESCC by expert and non‐expert endoscopists were compared using these three modalities and color differences measured for malignant lesions and surrounding mucosa. BLI had the highest score and color difference without iodine staining. Each determination with iodine was much higher than without iodine regardless of the modality. With iodine, ESCC mainly appeared pink, purple and green using WLI, LCI and BLI, respectively and visibility scores determined by non‐experts and experts were significantly higher for LCI (both p < 0.001) and BLI (p = 0.018 and p < 0.001) than for WLI. The score with LCI was significantly higher than with BLI among non‐experts (p = 0.035). With iodine, the color difference using LCI was twice that with WLI and one with BLI was significantly larger than with WLI (p < 0.001). These greater tendencies were found regardless of location, depth of cancer or intensity of pink color using WLI. In conclusion, areas of ESCC unstained by iodine were easily recognized using LCI and BLI. Visibility of these lesions is excellent even by non‐expert endoscopists, suggesting that this method is useful to diagnose ESCC and determine the resection line