Publications by authors named "YinHui Deng"

Objectives: Anti-HER2 targeted therapy significantly reduces risk of relapse in HER2 + breast cancer. New measures are needed for a precise risk stratification to guide (de-)escalation of anti-HER2 strategy.

Methods: A total of 726 HER2 + cases who received no/single/dual anti-HER2 targeted therapies were split into three respective cohorts.

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Background And Aims: The clinical management of small gastric submucosal tumors (SMTs) (<2 cm) faces a non-negligible challenge because of the lack of guideline consensus and effective diagnostic tools. This article develops an automatically optimized radiomics modeling system (AORMS) based on EUS images to diagnose and evaluate SMTs.

Methods: A total of 205 patients with EUS images of small gastric SMTs (<2 cm) were retrospectively enrolled in the development phase of AORMS for the diagnosis and the risk stratification of GI stromal tumor (GIST).

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Purpose: Diabetes is a well-recognized risk factor for cognitive frailty. This study aimed to investigate the influencing factors of cognitive frailty in elderly patients with diabetes and develop a nomogram for its assessment.

Methods: We collected the clinical data of diabetic patients aged 60 years or older and the patients were divided into training and validation cohorts at a ratio of 7:3.

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Objective: To explore the results of the Gamma Knife radiosurgery (GKRS) for World Health Organization (WHO) grade I intracranial meningiomas after surgical resection.

Methods: A total of 130 patients who were pathologically diagnosed as having WHO grade I meningiomas and who underwent post-operative GKRS were retrospectively reviewed in a single center.

Results: Of the 130 patients, 51 patients (39.

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Article Synopsis
  • Elastography ultrasound (EUS) is an important imaging method, but it faces challenges like subjective interpretation and hardware limitations that affect the miniaturization of equipment.
  • A new deep neural network has been developed to create virtual EUS (V-EUS) from traditional B-mode images, providing a cost-effective solution.
  • Analysis of 4580 breast tumor cases shows that V-EUS performs similarly to real EUS in identifying tumors, and it improves the diagnostic accuracy of portable ultrasound devices by approximately 5%.
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Raman spectroscopy is a spectroscopic technique typically used to determine vibrational modes of molecules and is commonly used in chemistry to provide a structural fingerprint by which molecules can be identified. With the help of deep learning, Raman spectroscopy can be analyzed more efficiently and thus provide more accurate molecular information. However, no general neural network is designed for one-dimensional Raman spectral data so far.

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Objective: The aims of this study were to investigate the long-term outcomes of primary versus postoperative Gamma Knife radiosurgery (GKRS) for benign meningiomas.

Methods: Three hundred and forty meningioma patients underwent GKRS were retrospectively reviewed. Patients in the postoperative GKRS group were matched to those in the primary GKRS group, in a 1:1 ratio.

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Surgeons face challenges in intraoperatively defining margin of brain tumors due to its infiltrative nature. Extracellular acidosis caused by metabolic reprogramming of cancer cells is a reliable marker for tumor infiltrative regions. Although the acidic margin-guided surgery shows promise in improving surgical prognosis, its clinical transition is delayed by having the exogenous probes approved by the drug supervision authority.

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Gastric cancer is the second most lethal type of malignant tumor in the world. Early diagnosis of gastric cancer can reduce the transformation to advanced cancer and improve the early treatment rate. As a cheap, real-time, non-invasive examination method, oral contrast-enhanced ultrasonography (OCUS) is a more acceptable way to diagnose gastric cancer than interventional diagnostic methods such as gastroscopy.

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Article Synopsis
  • The study focused on tumor regrowth after gamma knife radiosurgery (GKRS) in patients with nonfunctioning pituitary adenomas (NFPAs), analyzing data from 369 patients with a median age of 45.2 years and varying tumor sizes.* -
  • It reported a 6.5% rate of tumor regrowth after treatment, identifying risk factors such as parasellar invasion and low radiation doses (less than 12 Gy) that contributed to this regrowth, with average regrowth occurring around 86 months post-GKRS.* -
  • Repeat GKRS was performed on 12 patients, showing a 58.3% success rate in shrinking tumors, while overall tumor control rates after repeat GKRS were
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Article Synopsis
  • The study analyzed 751 patients with pituitary adenomas treated with gamma knife radiosurgery (GKRS) to understand the incidence and risk factors for pituitary hemorrhage.
  • Out of the total patients, 17% experienced pituitary hemorrhage, with 11.7% occurring before GKRS and 7.3% developing afterward, particularly in patients with nonfunctioning pituitary adenomas (NFPAs).
  • NFPAs and suprasellar extension increased the risk of hemorrhage, suggesting that GKRS may not be a guaranteed success for these patients, as complications could lead to treatment failure.
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Article Synopsis
  • The study aimed to evaluate the long-term effects of Gamma Knife radiosurgery (GKRS) on large or growing asymptomatic meningiomas in 59 patients, with a median age of 56 years and follow-up of around 67 months.
  • Results showed that 59.3% of tumors shrank, 39% remained stable, and only 1.7% progressed, indicating a high tumor control rate over time.
  • Complications included new neurological symptoms in 15.3% of patients and peritumoral edema (PTE) in 25.4%, with tumor size and maximum dose being significant risk factors for PTE.
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Non-invasive assessment of the risk of lymph node metastasis (LNM) in patients with papillary thyroid carcinoma (PTC) is of great value for the treatment option selection. The purpose of this paper is to develop a transfer learning radiomics (TLR) model for preoperative prediction of LNM in PTC patients in a multicenter, cross-machine, multi-operator scenario. Here we report the TLR model produces a stable LNM prediction.

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BACKGROUND The aim of this study was to review outcomes of gamma knife radiosurgery (GKRS) for prolactinoma and report our experience with it. MATERIAL AND METHODS We reviewed the patient database in our center and identified 24 patients with prolactinoma who underwent GKRS from 1993 to 2016.  Complete endocrine, clinical, and radiological data were available on these individuals before and after GKRS.

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The aim of this retrospective study was to analyze the long-term outcomes and factors associated with treatment failure of Gamma Knife radiosurgery (GKRS) for postsurgical residual or recurrent nonfunctioning pituitary adenomas (NFPAs). A total of 148 cases of postsurgical residual or recurrent NFPA patients were enrolled in the study. There were 111 cases with residual tumor and 37 cases with recurrent tumor.

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Purpose: The evaluation of fetal lung maturity is critical for clinical practice since the lung immaturity is an important cause of neonatal morbidity and mortality. For the evaluation of the development of fetal lung maturation degree, our study established a deep model from ultrasound images of four-cardiac-chamber view plane.

Methods: A two-stage transfer learning approach is proposed for the purpose of the study.

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Objective: The aim of this study was to evaluate the long-term outcomes of initial Gamma Knife radiosurgery (GKRS) for patients with nonfunctioning pituitary adenomas (NFPAs).

Design And Methods: This was a single-center retrospective study. Eighty-one patients with NFPAs undergoing initial GKRS were enrolled.

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Ultrasound imaging plays an important role in breast cancer screening for which early and accurate lesion detection is crucial for clinical practice. Many researches were performed on supporting the breast lesion detection based on ultrasound data. In the paper, a novel hierarchical model is proposed to automatically detect breast lesion from ultrasound 3D data.

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Backscatter and attenuation parameters are not easily measured in clinical applications due to tissue inhomogeneity in the region of interest (ROI). A least squares method(LSM) that fits the echo signal power spectra from a ROI to a 3-parameter tissue model was used to get attenuation coefficient imaging in fatty liver. Since fat's attenuation value is higher than normal liver parenchyma, a reasonable threshold was chosen to evaluate the fatty proportion in fatty liver.

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Ultrasound lesion segmentation is an important and challenging task. Comparing with other methods, region-based level set has many advantages, but still requires considerable improvement to deal with the characteristic of lesions in the ultrasound modality such as shadowing, speckle and heterogeneity. In the clinical workflow, the physician would usually denote long and short axes of a lesion for measurement purpose yielding four markers in an image.

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The nuchal translucency (NT) thickness is an important parameter in the diagnosis of fetuses. The previous computerized methods often require manual operations to select the NT region, which leads to the time-consuming problem and the detection variability. In the paper, a hierarchical model is proposed for the automated detection of the NT region.

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The structure of an early fetal heart provides vital information for the diagnosis of fetus defects. However, early fetal hearts are difficult to detect due to their relatively small size and the low signal-to-noise ratio of ultrasound images. In this paper, a novel method is proposed for automatic detection of early fetal cardiac structure from ultrasound images.

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Objective: Polycystic ovary syndrome (PCOS) is a complex endocrine disorder that seriously affects women's health. The disorder is characterized by the formation of many follicles in the ovary. Currently the predominant diagnosis is to manually count the number of follicles, which may lead to inter-observer and intra-observer variability and low efficiency.

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Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder which seriously impacts women's health. The disorder is characterized by the formation of many follicular cysts in the ovary. Nowadays the diagnosis performed by doctors is to manually count the number of follicular cysts, which may lead to problems of the variability, reproducibility and low efficiency.

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