Publications by authors named "Baohua Lv"

This study aimed to investigate the correlation between baseline MRI features and baseline carcinoembryonic antigen (CEA) expression status in rectal cancer patients. A training cohort of 168 rectal cancer patients from Center 1 and an external validation cohort of 75 rectal cancer patients from Center 2 were collected. A nomogram was constructed based on the training cohort and validated using the external validation cohort to predict high baseline CEA expression in rectal cancer patients.

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Background: Pneumonia and tuberculosis are prevalent pulmonary diseases globally, each demanding specific care measures. However, distinguishing between these two conditions imposes challenges due to the high skill requirements for doctors, the impact of imaging positions and respiratory intensity of patients, and the associated high healthcare costs, emphasizing the imperative need for intelligent and efficient diagnostic methods.

Method: This study aims to develop a highly accurate automatic diagnosis and classification method for various lung diseases (Normal, Pneumonia, and Tuberculosis).

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Background: Fat-suppressed (FS) T2-weighed turbo spin-echo (TSE) sequence was used to detect the signal of the thymus and the characteristics of the thymus location, measure the two-dimensional diameter at specific levels, and analyze the association with gestational weeks.

Methods: This study involved 51 fetal specimens. Post-mortem MRI scanning was implemented with a 3.

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Background: Infiltrating tumor border configuration (iTBC) is assessed by postoperative pathological examination, thus, is not helpful for preoperative treatment strategies. The study aimed to detect iTBC by magnetic resonance imaging (MRI) and evaluate its predictive value.

Materials And Methods: A total of 153 patients with rectal cancer were retrospectively analyzed.

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Objective: To explore the relationship of MRI morphology of primary rectal cancer with extramural vascular invasion (EMVI), metastasis and local recurrence.

Materials And Methods: This retrospective study included 153 patients with rectal cancer. Imaging factors and histopathological index including nodular projection (NP), cord sign (CS) at primary tumor margin, irregular nodules (IN) of mesorectum, MRI-detected peritoneal reflection invasion (PRI), range of rectal wall invasion (RRWI), patterns and length of tumor growth, maximal extramural depth (EMD), histologically confirmed local node involvement (hLN), MRI T stage, MRI N stage, MRI-detected extramural vascular invasion (mEMVI) and histologically confirmed extramural vascular invasion (hEMVI) were evaluated.

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Background: Although tumor deposits (TDs) are not the same as lymph nodes, the prognosis of patients with TDs is similar or worse than that of patients with metastatic lymph nodes. TDs are mostly assessed by the histology of samples after surgery, thus, not helpful for preoperative treatment strategies. The primary objective of this study was to detect TDs by MRI and evaluate its predictive value.

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Background: The prognosis of postoperative tumor deposits (TDs) is worse than positive lymph node metastases alone.

Objective: To detect TDs by using multiplanar high-resolution T2-weighted imaging (HRT2WI).

Material And Methods: This retrospective study enrolled 130 patients with locally advanced rectal cancer (LARC).

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Atomically thin two-dimensional (2D) van der Waals materials have exhibited many exotic layer-dependent physical properties including electronic structure, magnetic order, etc. Here, we report a striking even-odd layer dependent oscillation in the ferroelectric polarization of 2H-stacked few-layer α-InSe nanoflakes. As characterized by piezoresponse force microscopy (PFM), when the in-plane (IP) electric polarization of 2H-stacked α-InSe films is electrically aligned, the out-of-plane (OOP) polarization of the odd-layer (OL) samples is obviously larger than that of the even-layer (EL) ones.

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Synopsis of recent research by authors named "Baohua Lv"

  • - Baohua Lv's recent research primarily focuses on advancing diagnostic methods in medical imaging, particularly for lung diseases, rectal cancer, and fetal anatomy, utilizing innovative imaging techniques such as MRI and deep learning algorithms.
  • - Noteworthy findings include the development of the DSEception neural network architecture, which significantly improves the accuracy of pneumonia and tuberculosis diagnoses, as well as the identification of tumor deposits in rectal cancer through MRI, enhancing preoperative assessment strategies.
  • - Additionally, Lv's work has explored the morphological characteristics of rectal cancer and the biological significance of fetal thymus imaging, contributing valuable insights to both oncological and prenatal diagnostic fields.