Introduction: The purpose of this study is to evaluate the validity of a free-access software package (ITK-SNAP) in segmenting and measuring the volume of upper airway spaces secondary to rapid maxillary expansion (RME).
Materials And Methods: Sixteen participants who required RME were recruited for this study. Preoperative (T1) and 6-month postoperative (T2) cone-beam computed tomographic scans of all participants were analyzed. OnDemand3D software packages was used for superimposition and orientation of the images, while ITK-SNAP software was used to measure the volume of airway spaces. At week one (W1), all volumetric measurements were carried out by one examiner and repeated after 1 week (W2). Paired -test, the interclass correlation coefficient, and Dahlberg coefficients of reliability were used to assess the reproducibility.
Results: Student's -test showed no significant difference between the W1 and W2 set of measurements ( > 0.05). Coefficients of reliability were above 95% and intraclass correlation coefficient ranged from 0.99 to 1.000, which altogether confirmed the satisfactory reproducibility of the measurements.
Conclusions: ITK-SNAP software package is a reliable and cost-effective method to segment and measure upper airway changes subsequent to RME.
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http://dx.doi.org/10.4103/jos.JOS_93_17 | DOI Listing |
Magn Reson Imaging
December 2024
Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China. Electronic address:
Purpose: To evaluate cerebrospinal fluid (CSF) flow dynamics and volume changes of pulsatile tinnitus (PT) patients induced by sigmoid sinus wall dehiscence (SSWD) with intracranial hypertension.
Methods: Thirty-five SSWD-PT patients coexisted with intracranial hypertension and 35, age-, gender-, and handedness-matched healthy volunteers were prospectively enrolled and performed MRI. Clinical data were collected.
J Vasc Surg Venous Lymphat Disord
December 2024
Department of Radiology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China. Electronic address:
Objective: According to International Lymphology Society guidelines, the severity of lymphedema is determined by the difference in volume between the affected limb and the healthy side divided by the volume of the healthy side. However, this method of measuring volume is time consuming, laborious, and has certain errors in clinical applications. Therefore, this study aims to explore whether machine learning radiomics features based on noncontrast magnetic resonance imaging (MRI) can predict the severity of primary lower limb lymphedema.
View Article and Find Full Text PDFMetab Brain Dis
December 2024
Department of Neurology, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, 201613, Shanghai, China.
We used spontaneously hypertensive rats (SHR) as a hypertensive cerebral small vessel disease (CSVD) model to quantify blood-brain barrier (BBB) disruption by 11.7TMR T1mapping and to investigate white matter lesions and microangiopathy in CSVD. Male SHR were used as a hypertensive CSVD animal model and normotensive Wistar-Kyoto rats (WKY) were used as a control model.
View Article and Find Full Text PDFTechnol Cancer Res Treat
December 2024
Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Introduction: Since the response of patients with rectal cancer (RC) to neoadjuvant therapy is highly variable, there is an urgent need to develop accurate methods to predict the post-treatment T (pT) stage. The purpose of this study was to evaluate the utility of multi-parametric MRI radiomics models and identify the most accurate machine learning (ML) algorithms for predicting pT stage of RC.
Method: This retrospective study analyzed pretreatment clinical features of 171 RC patients who underwent 3 T MRI prior to neoadjuvant therapy and subsequent total mesorectal excision.
Cureus
November 2024
Neurosurgery, Russian People's Friendship University, Moscow, RUS.
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