Development of automated neural network prediction for echocardiographic left ventricular ejection fraction.

Introduction: The echocardiographic measurement of left ventricular ejection fraction (LVEF) is fundamental to the diagnosis and classification of patients with heart failure (HF). Methods: This paper aimed to quantify LVEF automatically and accurately with the proposed pipeline method based on deep neural networks and ensemble learning. Within the pipeline, an Atrous Convolutional Neural Network (ACNN) was first trained to segment the left ventricle (LV), before employing the area-length formulation based on the ellipsoid single-plane model to calculate LVEF values. This formulation required inputs of LV area, derived from segmentation using an improved Jeffrey's method, as well as LV length, derived from a novel ensemble learning model. To further improve the pipeline's accuracy, an automated peak detection algorithm was used to identify end-diastolic and end-systolic frames, avoiding issues with human error. Subsequently, single-beat LVEF values were averaged across all cardiac cycles to obtain the final LVEF. Results: This method was developed and internally validated in an open-source dataset containing 10,030 echocardiograms. The Pearson's correlation coefficient was 0.83 for LVEF prediction compared to expert human analysis (p < 0.001), with a subsequent area under the receiver operator curve (AUROC) of 0.98 (95% confidence interval 0.97 to 0.99) for categorisation of HF with reduced ejection (HFrEF; LVEF<40%). In an external dataset with 200 echocardiograms, this method achieved an AUC of 0.90 (95% confidence interval 0.88 to 0.91) for HFrEF assessment. Conclusion: The automated neural network-based calculation of LVEF is comparable to expert clinicians performing time-consuming, frame-by-frame manual evaluations of cardiac systolic function.

Detection of mesenchymal chondrosarcoma in pleural effusion with immunocytochemistry and determination of HEY1::NCOA2 fusion by next-generation sequencing on cell block.

Mesenchymal chondrosarcoma (MC) is a rare but extremely aggressive type of chondrosarcoma distinguished by the presence of both primitive mesenchymal cells and fully developed chondroid tissue. The identification of a biphasic morphology in pleural effusion, along with detection of the HEY1::NCOA2 fusion using next-generation sequencing, serve as vital indicators for an accurate diagnosis.

Case report metastatic SMARCB1 (INI1)-deficient gastric undifferentiated carcinoma in pleural effusion: A case report and literature review.

INI1-deficient gastric undifferentiated carcinoma is a rare tumour that may present as high-grade epithelioid morphology without apparent rhabdoid tumour cells. Syncytial tumour cells may be a crucial clue in such cases, especially in cytological specimens. Cell block and immunocytochemical staining can be valuable tools in achieving an accurate diagnosis.

Neoadjuvant chemoimmunotherapy achieved a pathologic complete response in stage IIIA lung adenocarcinoma harboring RET fusion: a case report.

Neoadjuvant chemoimmunotherapy has demonstrated significant benefit for resectable non-small-cell lung cancer (NSCLC) excluding known EGFR/ALK genetic alterations. Recent evidence has shown that neoadjuvant chemoimmunotherapy could be clinically valuable in resectable localized driver gene-mutant NSCLC, though the data still lack robust support, especially for rare oncogenic mutations. Here, we report a patient with stage IIIA lung adenocarcinoma with a RET fusion gene and high expression of PD-L1 who underwent neoadjuvant chemoimmunotherapy and successfully attained a pathologic complete response. The patient has survived for 12 months with no recurrence or metastases after surgery. Our case suggests that this treatment strategy may be an alternative therapeutic option for resectable RET fusion-positive NSCLC patients.

Solitary Fibrous Tumor of the Paranasal Sinuses with Intracranial Extension: A Rare Case Report and Review of the Literature.

Solitary fibrous tumors (SFTs) are rare mesenchymal neoplasms that were initially identified in the pleura. SFTs in the nasal or paranasal sinuses are especially rare. Most SFTs exhibit indolent behavior, with a low local recurrence rate. A 39-year-old man complained of bilateral nasal congestion, hyposmia, and occasional right eye tears six months prior to hospitalization. Based on MRI and CT imaging, a total gross surgical resection was achieved. Subsequently, postsurgical histopathological examinations were conducted. Under the microscope, pathological mitotic bodies were visible (<5 mitoses per 2 mm2). The immunohistochemical staining results revealed that tumor cells were positive for CD34, BCL-2, STAT-6, and Ki-67 (<5%) but negative for EMA, S-100, PR, GFAP, and SMA. Based on these findings, the patient was diagnosed with SFT.

TRIM34 modulates influenza virus-activated programmed cell death by targeting Z-DNA-binding protein 1 for K63-linked polyubiquitination.

Z-DNA-binding protein 1 (ZBP1) is an innate sensor of influenza A virus (IAV) that participates in IAV-induced programmed cell death. Nevertheless, little is known about the upstream signaling pathways regulating ZBP1. We found that a member of the tripartite motif (TRIM) family, TRIM34, interacted with ZBP1 to promote its K63-linked polyubiquitination. Using a series of genetic approaches, we provide in vitro and in vivo evidence indicating that IAV triggered cell death and inflammatory responses via dependent on TRIM34/ZBP1 interaction. TRIM34 and ZBP1 expression and interaction protected mice from death during IAV infection owing to reduced inflammatory responses and epithelial damage. Additionally, analysis of clinical samples revealed that TRIM34 associates with ZBP1 and mediates ZBP1 polyubiquitination in vivo. Higher levels of proinflammatory cytokines correlated with higher levels of ZBP1 in IAV-infected patients. Taken together, we conclude that TRIM34 serves as a critical regulator of IAV-induced programmed cell death by mediating the K63-linked polyubiquitination of ZBP1.

A Tensor-Based Catheter and Wire Detection and Tracking Framework and Its Clinical Applications.

OBJECTIVE: Catheters and wires are used extensively in cardiac catheterization procedures. Detecting their positions in fluoroscopic X-ray images is important for several clinical applications such as motion compensation and co-registration between 2D and 3D imaging modalities. Detecting the complete length of a catheter or wire object as well as electrode positions on the catheter or wire is a challenging task. METHOD: In this paper, an automatic detection framework for catheters and wires is developed. It is based on path reconstruction from image tensors, which are eigen direction vectors generated from a multiscale vessel enhancement filter. A catheter or a wire object is detected as the smooth path along those eigen direction vectors. Furthermore, a real-time tracking method based on a template generated from the detection method was developed. RESULTS: The proposed framework was tested on a total of 7,754 X-ray images. Detection errors for catheters and guidewires are 0.56 ± 0.28 mm and 0.68 ± 0.33 mm, respectively. The proposed framework was also tested and validated in two clinical applications. For motion compensation using catheter tracking, the 2D target registration errors (TRE) of 1.8 mm ± 0.9 mm was achieved. For co-registration between 2D X-ray images and 3D models from MRI images, a TRE of 2.3 ± 0.9 mm was achieved. CONCLUSION: A novel and fully automatic detection framework and its clinical applications are developed. SIGNIFICANCE: The proposed framework can be applied to improve the accuracy of image-guidance systems for cardiac catheterization procedures.

Targeting the KIF4A/AR Axis to Reverse Endocrine Therapy Resistance in Castration-resistant Prostate Cancer.

PURPOSE: Emerging evidence indicates that castration-resistant prostate cancer (CRPC) is often driven by constitutively active androgen receptor (AR) or its V7 splice variant (AR-V7) and commonly becomes resistant to endocrine therapy. The aim of this work is to evaluate the function of a kinesin protein, KIF4A, in regulating AR/AR-V7 in prostate cancer endocrine therapy resistance. EXPERIMENTAL DESIGN: We examined KIF4A expression in clinical prostate cancer specimens by IHC. Regulated pathways were investigated by qRT-PCR, immunoblot analysis, immunoprecipitation, and luciferase reporter and chromatin immunoprecipitation (ChIP) assays. A series of functional analyses were conducted in cell lines and xenograft models. RESULTS: Examination of the KIF4A protein and mRNA levels in patients with prostate cancer showed that increased expression of KIF4A was positively correlated with androgen receptor (AR) levels. Patients with lower tumor KIF4A expression had improved overall survival and disease-free survival. Mechanistically, KIF4A and AR form an auto-regulatory positive feedback loop in prostate cancer: KIF4A binds AR and AR-V7 and prevents CHIP-mediated AR and AR-V7 degradation; AR binds the promoter region of KIF4A and activates its transcription. KIF4A promotes castration-sensitive and castration-resistant prostate cancer cell growth through AR- and AR-V7-dependent signaling. Furthermore, KIF4A expression is upregulated in enzalutamide-resistant prostate cancer cells, and KIF4A knockdown effectively reverses enzalutamide resistance and enhances the sensitivity of CRPC cells to endocrine therapy. CONCLUSIONS: These findings indicate that KIF4A plays an important role in the progression of CRPC and serves as a crucial determinant of the resistance of CRPC to endocrine therapy.

Core-Shell NaHoF4@TiO2 NPs: A Labeling Method to Trace Engineered Nanomaterials of Ubiquitous Elements in the Environment.

Understanding the fate and behavior of nanoparticles (NPs) in the natural environment is important to assess their potential risk. Single particle inductively coupled plasma mass spectrometry (spICP-MS) allows for the detection of NPs at extremely low concentrations, but the high natural background of the constituents of many of the most widely utilized nanoscale materials makes accurate quantification of engineered particles challenging. Chemical doping, with a less naturally abundant element, is one approach to address this; however, certain materials with high natural abundance, such as TiO2 NPs, are notoriously difficult to label and differentiate from natural NPs. Using the low abundance rare earth element Ho as a marker, Ho-bearing core -TiO2 shell (NaHoF4@TiO2) NPs were designed to enable the quantification of engineered TiO2 NPs in real environmental samples. The NaHoF4@TiO2 NPs were synthesized on a large scale (gram), at relatively low temperatures, using a sacrificial Al(OH)3 template that confines the hydrolysis of TiF4 within the space surrounding the NaHoF4 NPs. The resulting NPs consist of a 60 nm NaHoF4 core and a 5 nm anatase TiO2 shell, as determined by TEM, STEM-EDX mapping, and spICP-MS. The NPs exhibit excellent detectability by spICP-MS at extremely low concentrations (down to 1 × 10-3 ng/L) even in complex natural environments with high Ti background.