Publications by authors named "Qing-Quan Lai"

Objective: To create an automated machine learning model using sacroiliac joint MRI imaging for early sacroiliac arthritis detection, aiming to enhance diagnostic accuracy.

Methods: We conducted a retrospective analysis involving 71 patients with early sacroiliac arthritis and 85 patients with normal sacroiliac joint MRI scans. Transverse T1WI and T2WI sequences were collected and subjected to radiomics analysis by two physicians.

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This study aims to validate a nomogram model that predicts invasive placenta in patients with placenta previa, utilizing MRI findings and clinical characteristics. A retrospective analysis was conducted on a training cohort of 269 patients from the Second Affiliated Hospital of Fujian Medical University and a validation cohort of 41 patients from Quanzhou Children's Hospital. Patients were classified into noninvasive and invasive placenta groups based on pathological reports and intraoperative findings.

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Background: Automated segmentation techniques for cardiac magnetic resonance imaging (MRI) are beneficial for evaluating cardiac functional parameters in clinical diagnosis. However, due to the characteristics of unclear image boundaries and anisotropic resolution anisotropy produced by cardiac magnetic resonance imaging technology, most of the existing methods still have the problems of intra-class uncertainty and inter-class uncertainty. However, due to the irregularity of the anatomical shape of the heart and the inhomogeneity of tissue density, the boundaries of its anatomical structures become uncertain and discontinuous.

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Background And Objective: In today's society, people's work pressure, coupled with irregular diet, lack of exercise and other bad lifestyle, resulting in frequent cardiovascular diseases. Medical imaging has made great progress in modern society, among which the role of MRI in cardiovascular field is self-evident. Based on this research background, how to process cardiac MRI quickly and accurately by computer has been extensively discussed.

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Background: The diagnostic results of magnetic resonance imaging (MRI) are essential references for arthroscopy as an invasive procedure. A deviation between medical imaging diagnosis and arthroscopy results may cause irreversible damage to patients and lead to excessive medical treatment. To improve the accurate diagnosis of meniscus injury, it is urgent to develop auxiliary diagnosis algorithms to improve the accuracy of radiological diagnosis.

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Background: In recent years, with the increase of late puerperium, cesarean section and induced abortion, the incidence of placenta accreta has been on the rise. It has become one of the common clinical diseases in obstetrics and gynecology. In clinical practice, accurate segmentation of placental tissue is the basis for identifying placental accreta and assessing the degree of accreta.

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Article Synopsis
  • The combined model shows impressive results with DSC, PPV, and sensitivity values of 0.94, 0.93, and 0.94, indicating strong performance in accurately segmenting breast tumors.
  • Our model outperforms other segmentation frameworks, demonstrating its effectiveness in detecting breast tumors.
  • The method is adaptable to different types of breast tumors and has the potential for clinical application, aiding in diagnosis and treatment planning for breast cancer patients.
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Article Synopsis
  • Breast cancer, a common type of cancer starting in breast tissue, is increasingly affecting younger individuals, highlighting the importance of advanced detection methods like MRI for tumor identification and treatment planning.
  • The proposed approach utilizes a combined Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for automated segmentation of breast tumors, achieving high performance metrics with scores of 0.93, 0.95, and 0.92 for DSC coefficient, PPV, and sensitivity, respectively.
  • The CNN-SVM network shows superior segmentation accuracy compared to other frameworks, suggesting its potential for improving breast tumor diagnostics, particularly for challenging cases like triple-negative breast cancer.
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Objective: To investigate the application value of dual-source computed tomography (DSCT) in preoperative assessment the rupture site of an thoracic aortic dissection (TAD).

Methods: A retrospective analysis of preoperative DSCT, multislice computed tomography (MSCT), and transthoracic echocardiography (TTE) results of 150 patients with suspected TAD in our hospital was conducted, and the intraoperative findings or interventional treatment results were used as the diagnostic gold standard.

Results: Of all 150 suspected TAD patients, 123 patients were confirmed to have TAD.

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Pulmonary artery sling (PAS) is a rare congenital vascular anomaly. Ninety percent of patients with PAS have respiratory distress and need surgical correction. Asymptomatic adult presentation of PAS is rare.

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Article Synopsis
  • A myxofibrosarcoma (MFS) is a rare and aggressive tumor, with this case focused on a 46-year-old male diagnosed with an MFS in the scalp after a 6-month unnoticed growth.
  • The tumor was initially small but grew significantly without causing pain or other symptoms, and imaging revealed extensive damage to surrounding tissues.
  • Treatment involved aggressive surgery followed by radiotherapy to reduce the risk of recurrence or metastasis.
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BACKGROUND The aim of this study was to assess the value of indirect MRI signs in the prenatal diagnosis of abnormally invasive placenta (AIP). MATERIAL AND METHODS This study involved the retrospective analysis of indirect signs of 109 patients with AIP and 59 patients without AIP. The numbers of cases of placenta increta, accreta, and percreta confirmed by surgical and pathological results were 54, 19, and 36, respectively.

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BACKGROUND This study aimed to investigate the role of dual-source computed tomography angiography (DSCTA) to evaluate the anatomy of the aortic arch vessels in patients with acute Type A aortic dissection (AD). MATERIAL AND METHODS A retrospective clinical study included 42 patients with acute Type A AD who underwent DSCTA and were treated in our hospital between January 2018 and December 2018. The findings were compared with a control group of 45 healthy individuals with hypertension and without aortic arch lesions.

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BACKGROUND The purpose of this study was to evaluate the utility of multi-detector computed tomography (MDCT) angiography and transthoracic echocardiography (TTE) in the diagnosis of congenital coarctation of the aorta (CoA) and accompanying malformations in infants. MATERIAL AND METHODS From January 2012 and December 2015, we enrolled 68 infants with clinically suspected CoA who underwent MDCT angiography and TTE in our hospital. Surgical correction was conducted to confirm the diagnostic accuracy of both examinations in all patients.

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The purpose of this study was to preoperatively evaluate the value of aortic arch lesions by multidetector computed tomography (MDCT) angiography in type A aortic dissection (AD).From January 2013 to December 2015, we enrolled 42 patients with type A AD who underwent MDCT angiography in our hospital. The institutional database of patients was retrospectively reviewed to identify MDCT angiography examinations for type A AD.

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Objective: To study the MRI features of 1,2-dichloroethane Chronic Toxic Encephalopathy of 10 cases.

Method: 10 cases were examined by MRI, slice thickness 8 mm, layer from 2 mm, axial and coronal line scan, T1WI, T2WI, FLAIR imaging.

Results: 10 cases show varying degrees of abnormal signal of white matters, low signal intensity on T1WI, high signal intensity on T2WI and FLAIR.

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