今泉 和良

The purpose of this study was to evaluate how the first oral administration of suvorexant affects PSG results in patients with severe obstructive sleep apnea (OSA). Single-center, prospective study conducted in a nonrandomized, uncontrolled, unblinded fashion. Undiagnosed 64 patients with suspected OSA underwent first-night PSG, and 30 patients with severe OSA (Apnea Hypopnea Index [AHI] ≥ 30 events/h) underwent second-night PSG testing after administration of 15 mg suvorexant. The change in AHI between the first and second nights was not significant, although the upper limit of the 95% confidence interval for the mean difference in AHI was high at 5.987.The mean duration of apnea on the second night was significantly prolonged compared to that on the first night, but there were no significant differences n 3% oxygen desaturation index, saturation of percutaneous oxygen<90% time. On the second night, total sleep time was significantly prolonged, mid-night awakenings decreased, REM sleep percentage increased, and REM latency was shorter. Because the environment for PSG testing is very different from the patient's home and many patients have difficulty sleeping, there are clinical cases in which PSG is performed with sleep medication. In this study, PSG after oral administration of 15 mg of suvorexant on the second night showed no significant difference or clear trend in AHI. However, the upper limit of the 95% confidence interval for the mean difference in AHI was greater than 5, suggesting that suvorexant may exacerbate AHI, even with the first administration.

BACKGROUND: The increasing prevalence of lung cancer in the elderly population necessitates a closer evaluation of diagnostic and therapeutic approaches. This study aimed to compare the safety and diagnostic efficacy of transbronchial lung cryobiopsy (TBLC) between patients ≥ 80 years and younger patients. METHODS: A retrospective review was conducted of 96 patients diagnosed with peripheral lung cancer who underwent TBLC between April 2021 and October 2023. The patients were categorized into two groups: the elderly group (age ≥ 80 years, n = 20) and younger group (age < 80 years; n = 76). Data regarding the biopsy yield, complications, and feasibility of molecular analyses were collected and analyzed. RESULTS: The diagnostic yield of TBLC was comparable between the elderly and younger groups (95% vs. 89.5%, p = 0.679). Biomarker testing, including programmed death-ligand 1 expression and genetic mutations, were feasible in all cases diagnosed with cancer using TBLC samples. No significant differences were observed in major complications such as pneumothorax or bleeding. CONCLUSIONS: TBLC was found to be a safe and effective diagnostic tool for peripheral lung cancer in elderly patients and provided adequate samples for molecular testing. Since the complication rates did not significantly differ between the two age groups, age alone should not be considered a contraindication for the procedure.

BACKGROUND: Immune checkpoint inhibitors (ICIs) play a central role in cancer immunotherapy. However, the occurrence of immune-related adverse events, especially ICI-induced interstitial lung disease (ICI-ILD), is life-threatening and affects the effectiveness of ICI treatment. This study aimed to explore potential drugs to mitigate ICI-ILD occurrence using data from the Japanese Adverse Drug Event Report (JADER) and the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS [JAPIC AERS]). RESEARCH DESIGN AND METHODS: We investigated concomitant drugs that reduce ILD associated with four ICIs - nivolumab, pembrolizumab, atezolizumab, and durvalumab - across the JADER and FAERS databases. Subsequently, the identified common concomitant drugs that reduce the occurrence of ICI-ILD were detected and analyzed. RESULTS: We found omega-3 fatty acids, loperamide, and amlodipine as common concomitant drugs that reduced ICI-ILD occurrence in both the JADER and FAERS databases. Omega-3 fatty acids reportedly have many effects in animal models of drug-induced ILD, including their association with ILD in humans and anti-inflammatory effects against ICI-ILD. However, loperamide and amlodipine reportedly have minimal effects against ILD, thereby necessitating further evaluation. CONCLUSION: Omega-3 fatty acids have emerged as potential agents for reducing ICI-ILD occurrence, as evidenced by findings from two different pharmacovigilance databases.

Cytology, a type of pathological examination, involves sampling cells from the human body and observing the morphology of the nucleus, cytoplasm, and cell arrangement. In developing classification AI technologies to support cytology, it is essential to collect and utilize a diverse range of images without bias. However, this is often challenging in practice because of the epidemiologic bias of cancer types and cellular characteristics. The main aim of this study was to develop a method to generate cytological diagnostic images from image findings using text-to-image technology in order to generate diverse images. In the proposed method, we collected Papanicolaou-stained specimens derived from the lung cells of 135 lung cancer patients, from which we extracted 472 patch images. Descriptions of the corresponding findings for these patch images were compiled to create a data set. This dataset was then utilized to finetune the Stable Diffusion (SD) v1 and v2 models. The cell images generated by this method closely resemble real images, and both cytotechnologists and cytopathologists provided positive subjective evaluations. Furthermore, SDv2 demonstrated shapes and contours of nuclei and cytoplasm that were more similar to real images compared to SDv1, showing superior performance in quantitative evaluation metrics. When the generated images were utilized in the classification tasks for cytological images, there was an improvement in classification performance. These results indicate that the proposed method may be effective for generating high-quality cytological images, which enables the image classification model to learn diverse features, thereby improving classification performance.

INTRODUCTION: Increasing numbers of cases of mild asymptomatic pulmonary alveolar proteinosis (PAP) are being reported with the recent increase in chest computed tomography (CT). Bronchoscopic diagnosis of mild PAP is challenging because of the patchy distribution of lesions, which makes it difficult to obtain sufficient biopsy samples. Additionally, the pathological findings of mild PAP, particularly those that differ from severe PAP, have not been fully elucidated. This study aimed to clarify the pathological findings of mild PAP and the usefulness of optical biopsy using probe-based confocal laser endomicroscopy (pCLE). METHODS: We performed bronchoscopic optical biopsy using pCLE and tissue biopsy in five consecutive patients with PAP (three with mild PAP and two with severe PAP). We compared the pCLE images of mild PAP with those of severe PAP by integrating clinical findings, tissue pathology, and chest computed tomography images. RESULTS: pCLE images of PAP showed giant cells with strong fluorescence, amorphous substances, and thin alveolar walls. Images of affected lesions in mild PAP were equivalent to those obtained in arbitrary lung lesions in severe cases. All three patients with mild PAP spontaneously improved or remained stable after ≥3 years of follow-up. Serum autoantibodies to granulocyte-macrophage colony-stimulating factor were detected in all five cases. CONCLUSION: Optical biopsy using pCLE can yield specific diagnostic findings, even in patients with mild PAP. pCLE images of affected areas in mild and severe PAP showed similar findings, indicating that the dysfunction level of pathogenic alveolar macrophages in affected areas is similar between both disease intensities.

Despite innovative advances in molecular targeted therapy, treatment strategies using immune checkpoint inhibitors (ICIs) for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) have not progressed significantly. Accumulating evidence suggests that ICI chemotherapy is inadequate in this population. Biomarkers of ICI therapy, such as programmed cell death ligand 1 (PD-L1) and tumor-infiltrating lymphocytes (TILs), are not biomarkers in patients with EGFR mutations, and the specificity of the tumor microenvironment has been suggested as the reason for this. Combination therapy with PD-L1 and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibitors is a concern because of its severe toxicity and limited efficacy. However, early-stage NSCLC may differ from advanced-stage NSCLC. In this review, we comprehensively review the current evidence and summarize the potential of ICI therapy in patients with EGFR mutations after acquiring resistance to treatment with EGFR-tyrosine kinase inhibitors (TKIs) with no T790M mutation or whose disease has progressed on osimertinib.

BACKGROUND: Bronchial thermoplasty (BT) is a recently developed non-pharmacological therapy for refractory bronchial asthma. Although increasing evidence has suggested that BT is effective for various phenotypes of severe asthma, its safety and efficacy in patients with severe irreversible impaired lung function are unclear. OBJECTIVES: To assess the efficacy and safety of BT in patients with refractory asthma, including patients with a severely impaired forced expiratory volume in 1 second (FEV1). DESIGN: This was a single-center, retrospective, observational cohort study. METHODS: We retrospectively reviewed the medical records of 15 patients with refractory asthma (Global Initiative for Asthma step 4 or 5), including patients with severely impaired airflow limitation (% predicted pre-bronchodilator FEV1 <60%), who had undergone BT between June 2016 and January 2022. We analyzed the efficacy (change in asthma symptoms, exacerbation rate, pulmonary function, asthma medication, and serum inflammatory chemokine/cytokines before and after BT) and complications in all patients. We compared these data between patients with severe obstructive lung dysfunction [group 1(G1)] and patients with FEV1 ⩾ 60% [group 2 (G2)]. RESULTS: Six patients were in G1 and nine were in G2. Clinical characteristics, T2 inflammation, and concurrent treatment were equivalent in both groups. BT significantly improved asthma-related symptoms (measured using the Asthma Control Test and Asthma Quality of Life Questionnaire scores) in both groups. FEV1 was significantly improved in G1 but not in G2. Four patients in G2, but none in G1, experienced asthma exacerbation requiring additional systemic corticosteroids (including two requiring prolonged hospitalization) after BT. Long-term responders (patients who reduced systemic or inhaled corticosteroid without newly adding biologics in a follow-up > 2 years) of BT were identified in G1 and G2 (n = 2, 33.3% and n = 4, 44.4%, respectively). CONCLUSION: BT in patients with refractory asthma and severe airflow limitation is equally safe and efficacious as that in patients with moderate airflow limitation.

Interstitial pneumonia of uncertain cause is referred to as idiopathic interstitial pneumonia (IIP). Among the various types of IIPs, the prognosis of cases of idiopathic pulmonary fibrosis (IPF) is extremely poor, and accurate differentiation between IPF and non-IPF pneumonia is critical. In this study, we consider deep learning (DL) methods owing to their excellent image classification capabilities. Although DL models require large quantities of training data, collecting a large number of pathological specimens is difficult for rare diseases. In this study, we propose an end-to-end scheme to automatically classify IIPs using a convolutional neural network (CNN) model. To compensate for the lack of data on rare diseases, we introduce a two-step training method to generate pathological images of IIPs using a generative adversarial network (GAN). Tissue specimens from 24 patients with IIPs were scanned using a whole slide scanner, and the resulting images were divided into patch images with a size of 224 × 224 pixels. A progressive growth GAN (PGGAN) model was trained using 23,142 IPF images and 7817 non-IPF images to generate 10,000 images for each of the two categories. The images generated by the PGGAN were used along with real images to train the CNN model. An evaluation of the images generated by the PGGAN showed that cells and their locations were well-expressed. We also obtained the best classification performance with a detection sensitivity of 97.2% and a specificity of 69.4% for IPF using DenseNet. The classification performance was also improved by using PGGAN-generated images. These results indicate that the proposed method may be considered effective for the diagnosis of IPF.

Abstract Artificial intelligence (AI) applications in medical imaging continue facing the difficulty in collecting and using large datasets. One method proposed for solving this problem is data augmentation using fictitious images generated by generative adversarial networks (GANs). However, applying a GAN as a data augmentation technique has not been explored, owing to the quality and diversity of the generated images. To promote such applications by generating diverse images, this study aims to generate free-form lesion images from tumor sketches using a pix2pix-based model, which is an image-to-image translation model derived from GAN. As pix2pix, which assumes one-to-one image generation, is unsuitable for data augmentation, we propose StylePix2pix, which is independently improved to allow one-to-many image generation. The proposed model introduces a mapping network and style blocks from StyleGAN. Image generation results based on 20 tumor sketches created by a physician demonstrated that the proposed method can reproduce tumors with complex shapes. Additionally, the one-to-many image generation of StylePix2pix suggests effectiveness in data-augmentation applications.

Syphilis can cause a wide range of systemic manifestations, such as papular rash, malaise, weight loss, muscle aches, generalized lymphadenopathy, and meningitis. However, pulmonary involvement in patients with secondary syphilis is thought to be relatively rare. Moreover, bone involvement in patients with secondary syphilis is also considered rare, and only a few cases of involvement of lung and bone in such patients have been reported. In this paper, we report a case of secondary syphilis with pulmonary involvement in the form of multiple nodules with low attenuation areas, lymphadenopathy and multiple bone lesions detected on computed tomography and 18F fluorodeoxyglucose-positron emission tomography/computed tomography.

Induced pluripotent stem (iPS) cells are widely used as a research tool in regenerative medicine and embryology. In studies related to lens regeneration in the eye, iPS cells have been reported to differentiate into lens epithelial cells (LECs); however, to the best of our knowledge, no study to date has described their formation of three-dimensional cell aggregates. Notably, in vivo studies in newts have revealed that iris cells in the eye can dedifferentiate into LECs and regenerate a new lens. Thus, as basic research on lens regeneration, the present study investigated the differentiation of human iris tissue-derived cells and human iris tissue-derived iPS cells into LECs and their formation of three-dimensional cell aggregates using a combination of two-dimensional culture, static suspension culture and rotational suspension culture. The results revealed that three-dimensional cell aggregates were formed and differentiated into LECs expressing αA-crystallin, a specific marker protein for LECs, suggesting that the cell-cell interaction facilitated by cell aggregation may have a critical role in enabling highly efficient differentiation of LECs. However, the present study was unable to achieve transparency in the cell aggregates; therefore, we aim to continue to investigate the degradation of organelles and other materials necessary to make the interior of the formed cell aggregates transparent. Furthermore, we aim to expand on our current work to study the regeneration of the lens and ciliary body as a whole in vitro, with the aim of being able to restore focusing function after cataract surgery.

OBJECTIVE: It is essential to accurately diagnose and classify histological subtypes into adenocarcinoma (ADC), squamous cell carcinoma (SCC), and small cell lung carcinoma (SCLC) for the appropriate treatment of lung cancer patients. However, improving the accuracy and stability of diagnosis is challenging, especially for non-small cell carcinomas. The purpose of this study was to compare multiple deep convolutional neural network (DCNN) technique with subsequent additional classifiers in terms of accuracy and characteristics in each histology. METHODS: Lung cancer cytological images were classified into ADC, SCC, and SCLC with four fine-tuned DCNN models consisting of AlexNet, GoogLeNet (Inception V3), VGG16 and ResNet50 pretrained by natural images in ImageNet database. For more precise classification, the figures of 3 histological probabilities were further applied to subsequent machine learning classifiers using Naïve Bayes (NB), Support vector machine (SVM), Random forest (RF), and Neural network (NN). RESULTS: The classification accuracies of the AlexNet, GoogLeNet, VGG16 and ResNet50 were 74.0%, 66.8%, 76.8% and 74.0%, respectively. Well differentiated typical morphologies were tended to be correctly judged by all four architectures. However, poorly differentiated non-small cell carcinomas lacking typical structures were inclined to be misrecognized in some DCNNs. Regarding the histological types, ADC were best judged by AlexNet and SCC by VGG16. Subsequent machine learning classifiers of NB, SVV, RF, and NN improved overall accuracies to 75.1%, 77.5%, 78.2%, and 78.9%, respectively. CONCLUSION: Fine-tuning DCNNs in combination with additional classifiers improved classification of cytological diagnosis of lung cancer, although classification bias could be indicated among DCNN architectures.

Secondary fungal infections are a critical problem that accompany immunosuppressive therapy for severe coronavirus disease 2019 (COVID-19). We report a fatal case of COVID-19 with disseminated mucormycosis diagnosed during autopsy. A 58-year-old man with diabetes was hospitalized for severe COVID-19 and treated with remdesivir, systemic steroids and tocilizumab. Following treatment, he was provided extracorporeal membrane oxygenation support. However, he died of multiple organ failure accompanied by pulmonary and kidney infarction, as revealed by computed tomography. Autopsy revealed that the infarction was caused by thromboangiitis due to mucormycosis in the brain, lungs, heart, liver and kidneys. Therefore, the diagnosis of disseminated mucormycosis was established. Disseminated mucormycosis is a rare complication of COVID-19. Although its early diagnosis is difficult, the disease progresses rapidly. Hence, we propose that immunosuppressive treatment for COVID-19 should be administered with caution considering the risk of developing severe opportunistic infections, such as mucormycosis.

OBJECTIVE: The prevalence of obstructive sleep apnea (OSA) in Japan is 9% among males and 3% among females. Up to 2.5 million patients are estimated to suffer from the disease, but limited number of facilities are capable of carrying out polysomnography (PSG), leaving more than 80% of these individuals are undiagnosed. In recent years, the development of new portable sleep monitoring (PMs) devices has been remarkable. We evaluate the correlation between the results of the LS-140 PMs device (Fukuda Denshi Tech Co. Ltd.), released in 2017, and those of PSG. METHODS: We obtained contemporaneous data from the same patients by equipping 58 patients with PMs (LS-140) devices while they underwent PSG. Our primary outcome was Case 2 of the intraclass correlation coefficient (ICC), i.e., the ICC (2.1). And we used a Bland-Altman analysis to compare the apnea-hypopnea index (AHI) given by PSG and the respiratory event index (REI) given by LS-140 and examined the sensitivity and specificity of the REI relative to the AHI in the diagnosis of OSA. We also carried out the same comparison but in terms of the presence or absence of periodic limb movements (PLMs). RESULTS: The ICC (2.1) between The REI and the AHI was 0.944, a rather high value (p<0.0001). The mean difference between AHI and REI values was -3.6 (p<0.0001), indicating a negative fixed bias. Sensitivity may decrease in groups with PLMs. CONCLUSION: The REI and the AHI are highly correlated, giving LS-140 sufficient diagnostic sensitivity and specificity to screen for OSA.

<title>Abstract</title>In cytological examination, suspicious cells are evaluated regarding malignancy and cancer type. To assist this, we previously proposed an automated method based on supervised learning that classifies cells in lung cytological images as benign or malignant. However, it is often difficult to label all cells. In this study, we developed a weakly supervised method for the classification of benign and malignant lung cells in cytological images using attention-based deep multiple instance learning (AD MIL). Images of lung cytological specimens were divided into small patch images and stored in bags. Each bag was then labeled as benign or malignant, and classification was conducted using AD MIL. The distribution of attention weights was also calculated as a color map to confirm the presence of malignant cells in the image. AD MIL using the AlexNet-like convolutional neural network model showed the best classification performance, with an accuracy of 0.916, which was better than that of supervised learning. In addition, an attention map of the entire image based on the attention weight allowed AD MIL to focus on most malignant cells. Our weakly supervised method automatically classifies cytological images with acceptable accuracy based on supervised learning without complex annotations.

We herein report a case of acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) triggered by COVID-19. An 87-year-old woman tested positive for COVID-19 on a polymerase chain reaction test, and computed tomography revealed ground-glass opacity (GGO) superimposed on a background pattern consistent with usual interstitial pneumonia. Considering these data, we diagnosed her with AE-IPF. She experienced worsening of dyspnea and expansion of the GGO. Therefore, we introduced high-dose steroids (methylprednisolone 250 mg/day for 3 days). After the treatment, the pulmonary infiltrates improved. She was discharged from our hospital without severe disability. High-dose steroids can be a viable treatment option for AE-IPF triggered by COVID-19.