Search

Abstract Background Postoperative progressive cerebral edema and hemorrhage (PPCEH) are major complications after meningioma resection, yet their preoperative predictive studies are limited. The aim is to develop and validate a multiparametric MRI machine learning model to predict PPCEH after meningioma resection. Methods This retrospective study included 148 patients with meningioma. A stratified three-fold cross-validation was used to split the dataset into training and validation sets. Radiomics features from the tumor enhancement (TE) and peritumoral brain edema (PTBE) regions were extracted from T1WI, T2WI, and ADC maps. Support vector machine constructed different radiomics models, and logistic regression explored clinical risk factors. Prediction models, integrating clinical and radiomics features, were evaluated using the area under the curve (AUC), visualized in a nomogram. Results The radiomics model based on TE and PTBE regions (training set mean AUC: 0.85 (95% CI: 0.78–0.93), validation set mean AUC: 0.77 (95%CI: 0.63–0.90)) outperformed the model with TE region solely (training set mean AUC: 0.83 (95% CI: 0.76–0.91), validation set mean AUC: 0.73 (95% CI: 0.58–0.87)). Furthermore, the combined model incorporating radiomics features, and clinical features of preoperative peritumoral edema and tumor boundary adhesion, had the best predictive performance, with AUC values of 0.87 (95% CI: 0.80–0.94) and 0.84 (95% CI: 0.72–0.95) for the training and validation set. Conclusions We developed a novel model based on clinical characteristics and multiparametric radiomics features derived from TE and PTBE regions, which can accurately and non-invasively predict PPCEH after meningioma resection. Additionally, our findings suggest the crucial role of PTBE radiomics features in understanding the potential mechanisms of PPCEH.

Abstract Background To evaluate the neurological alterations induced by Omicron infection, to compare brain changes in chronic insomnia with those in exacerbated chronic insomnia in Omicron patients, and to examine individuals without insomnia alongside those with new-onset insomnia. Methods In this study, a total of 135 participants were recruited between January 11 and May 4, 2023, including 26 patients with chronic insomnia without exacerbation, 24 patients with chronic insomnia with exacerbation, 40 patients with no sleep disorder, and 30 patients with new-onset insomnia after infection with Omicron (a total of 120 participants with different sleep statuses after infection), as well as 15 healthy controls who were never infected with Omicron. Neuropsychiatric data, clinical symptoms, and multimodal magnetic resonance imaging data were collected. The gray matter thickness and T1, T2, proton density, and perivascular space values were analyzed. Associations between changes in multimodal magnetic resonance imaging findings and neuropsychiatric data were evaluated with correlation analyses. Results Compared with healthy controls, gray matter thickness changes were similar in the patients who have and do not have a history of chronic insomnia groups after infection, including an increase in cortical thickness near the parietal lobe and a reduction in cortical thickness in the frontal, occipital, and medial brain regions. Analyses showed a reduced gray matter thickness in patients with chronic insomnia compared with those with an aggravation of chronic insomnia post-Omicron infection, and a reduction was found in the right medial orbitofrontal region (mean [SD], 2.38 [0.17] vs. 2.67 [0.29] mm; P

Abstract Background The presence of infarction in patients with unrecognized myocardial infarction (UMI) is a critical feature in predicting adverse cardiac events. This study aimed to compare the detection rate of UMI using conventional and deep learning reconstruction (DLR)-based late gadolinium enhancement (LGEO and LGEDL, respectively) and evaluate optimal quantification parameters to enhance diagnosis and management of suspected patients with UMI. Methods This prospective study included 98 patients (68 men; mean age: 55.8 ± 8.1 years) with suspected UMI treated at our hospital from April 2022 to August 2023. LGEO and LGEDL images were obtained using conventional and commercially available inline DLR algorithms. The myocardial signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and percentage of enhanced area (Parea) employing the signal threshold versus reference mean (STRM) approach, which correlates the signal intensity (SI) within areas of interest with the average SI of normal regions, were analyzed. Analysis was performed using the standard deviation (SD) threshold approach (2SD–5SD) and full width at half maximum (FWHM) method. The diagnostic efficacies based on LGEDL and LGEO images were calculated. Results The SNRDL and CNRDL were two times better than the SNRO and CNRO, respectively (P 0.05). The Parea−DL and Parea−O also differed except between the 2SD and 3SD and the 4SD/5SD and FWHM methods (P

Rationale and objectives: This study aimed to assess the feasibility and image quality of free-breathing 3D isotropic zero echo time (ZTE) whole-lung imaging and explore a clinically appropriate protocol for MR lung imaging. Materials and methods: The study was approved by the local ethics committee. A total of thirty healthy volunteers were enrolled in this study from October 2022 to May 2023. Free-breathing pulmonary 3D isotropic ZTE scans were implemented with various acquisition planes and the number of excitations (NEX). ZTE images were evaluated by two radiologists for the overall Image quality and visibility of intrapulmonary structures as well as the signal-to-noise ratio (SNR) of the lung parenchyma. ZTE images with different acquisition parameters were compared. For preliminary clinical visual assessment, three patients with interstitial lung disease underwent both ZTE imaging and computed tomography (CT). Results: The overall image quality of the lung in healthy subjects was good to excellent. The visibilities of pulmonary arteries and bronchus were up to the 7th and 5th generation, respectively. The display of lung fissures was poor. The overall image quality, the visibility of the pulmonary artery, and lung fissures in the axial acquisition were better than in the coronal acquisition (P = 0.011, 0.008, 0.010, respectively) but not statistically different from those in the sagittal acquisition (all P > 0.05). Conclusion: The free-breathing pulmonary ZTE is feasible and may serve as an alternative method in chest imaging. Either axial or sagittal ZTE image acquisition would be preferred in clinical practice.

Abstract Background The three-dimensional chemical exchange saturation transfer (3D CEST) technique is a novel and promising magnetic resonance sequence; however, its application in nasopharyngeal carcinoma (NPC) lacks sufficient evaluation. This study aimed to assess the feasibility of the 3D CEST technique in predicting the short-term treatment outcomes for chemoradiotherapy (CRT) in NPC patients. Methods Forty NPC patients and fourteen healthy volunteers were enrolled and underwent the pre-treatment 3D CEST magnetic resonance imaging and diffusion-weighted imaging (DWI). The reliability of 3D CEST was assessed in healthy volunteers by calculating the intra- and inter-observer correlation coefficient (ICC) for amide proton transfer weighted-signal intensity (APTw-SI) and magnetization transfer ratio (MTR) values. NPC patients were divided into residual and non-residual groups based on short-term treatment outcomes after CRT. Whole-tumor regions of interest (ROIs) were manually drawn to measure APTw-SI, MTR and apparent diffusion coefficient (ADC) values. Multivariate analysis and the receiver operating characteristic curve (ROC) were used to evaluate the prediction performance of clinical characteristics, APTw-SI, MTR, ADC values, and combined models in predicting short-term treatment outcomes in NPC patients. Results For the healthy volunteer group, all APTw-SI and MTR values exhibited good to excellent intra- and inter-observer agreements (0.736–0.910, 0.895–0.981, all P > 0.05). For NPC patients, MTR values showed a significant difference between the non-residual and residual groups (31.24 ± 5.21% vs. 34.74 ± 1.54%, P = 0.003) while no significant differences were observed for APTw-SI and ADC values (P > 0.05). Moreover, the diagnostic power of MTR value was superior to APTw-SI (AUC: 0.818 vs. 0.521, P = 0.017) and comparable to ADC values (AUC: 0.818 vs. 0.649, P > 0.05) in predicting short-term treatment outcomes for NPC patients. The prediction performance did not improve even when combining MTR values with APTw-SI and/or ADC values (P > 0.05). Conclusions The pre-treatment MTR value acquired through 3D CEST demonstrated superior predictive performance for short-term treatment outcomes compared to APTw-SI and ADC values in NPC patients after CRT.

Key points rFOV-syDWI provided better lesion clarity and image quality while shortening scan time. Scanned and synthetic ADCs have the same diagnostic value for cervical cancer. Scanned and synthetic ADCmean, minimum can distinguish cervical lesions from normal tissue

Objectives: This work aimed to investigate the feasibility and diagnostic value of synthetic MRI, including T1, T2 and PD values in determining the severity of cervical spondylotic myelopathy (CSM).Methods: All subjects (51 CSM patients and 9 healthy controls) underwent synthetic MRI scan on a 3.0T GE MR scanner. The cervical canal stenosis degree of subjects was graded 0—III based on the method of a MRI grading system. Regions of interest (ROIs) were manually drawn at the maximal compression level (MCL) by covering the whole spinal cord to generate T1MCL, T2MCL, and PDMCL values in grade I-III groups. Besides, anteroposterior (AP) and transverse (Trans) diameters of the spinal cord at MCL were measured in grade II and grade III groups, and relative values were calculated as follows: rAP = APMCL/APnormal, rTrans = TransMCL/Transnormal. rMIN = rAP/rTrans.Results: T1MCL value showed a decreasing trend with severity of grades (from grade 0 to grade II, p < 0.05), while it increased dramatically at grade III. T2MCL value showed no significant difference among grade groups (from grade 0 to grade II), while it increased dramatically at grade III compared to grade II (p < 0.05). PDMCL value showed no statistical difference among all grade groups. rMIN of grade III was significantly lower than that of grade II (p < 0.05). T2MCL value was negatively correlated with rMIN, whereas positively correlated with rTrans.Conclusion: Synthetic MRI can provide not only multiple contrast images but also quantitative mapping, which is showed promisingly to be a reliable and efficient method in the quantitative diagnosis of CSM.

Abstract Background It is yet unknown if the whole-brain resting-state network is altered in multiple system atrophy with symptoms of depression. This study aimed to investigate if and how depression symptoms in multiple system atrophy are associated with resting-state network dysfunction. Methods We assessed the resting-state functional network matric using Degree centrality (DC) coupling with a second ROI-wise functional connectivity (FC) algorithm in a multimodal imaging case-control study that enrolled 32 multiple system atrophy patients with depression symptoms (MSA-D), 30 multiple system atrophy patients without depression symptoms (MSA-ND), and 34 healthy controls (HC). Results Compared to HC, MSA-D showed more extensive DC hub dysfunction in the left precentral and right middle frontal cortex than MSA-ND. A direct comparison between MSA-D and MSA-ND detected increased DC in the right anterior cingulum cortex, but decreased DC in the left cerebellum lobule IV and lobule V, left middle pole temporal cortex, and right superior frontal cortex. Only right anterior cingulum cortex mean DC values showed a positive correlation with depression severity, and used ACC as seed, a second ROI-wise functional connectivity further revealed MSA-D patients showed decreased connectivity between the ACC and right thalamus and right middle temporal gyrus (MTG). Conclusions These findings revealed that dysfunction of rACC, right middle temporal lobe and right thalamus involved in depressed MSA. Our study might help to the understanding of the neuropathological mechanism of depression in MSA.

BackgroundChronic kidney disease (CKD) has a significant negative impact on bone health. Bone marrow is an essential component of bone, mainly composed of trabecular bone and fat. The IDEAL-IQ sequence of MRI allows indirect quantification of trabecular bone mass by R2* and direct quantification of bone marrow fat content by FF map, respectively.ObjectiveOur objective was to explore the association of CKD severity with bone marrow using IDEAL-IQ and whether mineral and bone metabolism markers alter this association.MethodWe recruited 68 CKD patients in this cross-sectional research (15 with CKD stages 3-4, 26 with stage 5, and 27 with stage 5d). All patients underwent lumbar spine IDEAL-IQ, BMD, and several bone metabolism markers (iPTH, 25-(OH)-VitD, calcium and phosphorus). Multiple linear regression analysis was used to examine the association of CKD severity with MRI measurements (R2* and FF).ResultsMore severe CKD was associated with a higher R2* value [CKD 5d versus 3-4: 30.077 s-1 (95% CI: 12.937, 47.217), P for trend < 0.001], and this association was attenuated when iPTH was introduced [CKD 5d versus 3-4: 19.660 s-1 (95% CI: 0.205, 39.114), P for trend = 0.042]. Furthermore, iPTH had an association with R2* value [iPTH (pg/mL): 0.033 s-1 (95% CI: 0.001, 0.064), P = 0.041]. Besides, FF was mainly affected by age and BMI, but not CKD.ConclusionsThe bone marrow R2* value measured by IDEAL-IQ sequence is associated with CKD severity and iPTH. The R2* of IDEAL-IQ has the potential to reflect lumbar bone changes in patients with CKD.

BackgroundFreezing of gait (FOG) in multiple system atrophy (MSA) is characterized by a higher risk of falls and a reduced quality of life; however, the mechanisms underlying these effects have yet to be identified by neuroimaging. The aim of this study was to investigate the differences in functional network when compared between MSA patients with and without freezing.MethodsDegree centrality (DC) based on the resting-state functional magnetic resonance imaging was computed in 65 patients with MSA and 36 healthy controls. Brain regions with statistically different DC values between groups were selected as seed points for a second seed-based functional connectivity (FC) analysis. The relationships between brain activity (DC and FC alterations) and the severity of freezing symptoms were then investigated in the two groups of patients with MSA.ResultsCompared to MSA patients without FOG symptoms (MSA-nFOG), patients with MSA-FOG showed an increased DC in the left middle temporal gyrus but a reduced DC in the right superior pole temporal gyrus, left anterior cingulum cortex, left thalamus, and right middle frontal gyrus. Furthermore, in patients with MSA-FOG, the DC in the left thalamus was negatively correlated with FOG scores. Using the left thalamus as a seed, secondary seed-based functional connectivity analysis revealed that patients with MSA-FOG commonly showed the left thalamus-based FC abnormalities in regions related to cognition and emotion. In contrast to the patients with MSA-nFOG, patients with MSA-FOG showed an increased FC between the left thalamus and the left middle temporal gyrus (MTG), right inferior parietal lobule (IPL), bilateral cerebellum_8, and left precuneus.ConclusionFreezing of gait is associated with centrality of the impaired thalamus network. Abnormal FC between the thalamus and left MTG, right IPL, bilateral cerebellum_8, and left precuneus was involved in FOG. These results provide new insight into the pathophysiological mechanism of FOG in MSA.

ObjectiveThe aim of this study is to determine the potential of zero echo time (ZTE) MR lung imaging in the assessment of solid pulmonary nodules or masses and diagnostic consistency to CT in terms of morphologic characterization.MethodsOur Institutional Review Board approved this prospective study. Seventy-one patients with solid pulmonary nodules or masses larger than 1 cm in diameter confirmed by chest CT were enrolled and underwent further lung ZTE-MRI scans within 7 days. ZTE-MRI and CT images were compared in terms of image quality and imaging features. Unidimensional diameter and three-dimensional volume measurements on both modalities were manually measured and compared using the Wilcoxon signed-rank test, intraclass correlation coefficient (ICC), Pearson’s correlation analysis, and Bland–Altman analysis. Multivariable logistic regression analysis was used to identify the factors associated with significant inter-modality variation of volume.ResultsFifty-four of 71 (76.1%) patients were diagnosed with lung cancer. Subjective image quality was superior in CT compared with ZTE-MRI (p < 0.001). Inter-modality agreement for the imaging features was moderate for emphysema (kappa = 0.50), substantial for fibrosis (kappa = 0.76), and almost perfect (kappa = 0.88-1.00) for the remaining features. The size measurements including diameter and volume between ZTE-MRI and CT showed no significant difference (p = 0.36 for diameter and 0.60 for volume) and revealed perfect inter-observer (ICC = 0.975–0.980) and inter-modality (ICC = 0.942–0.992) agreements. Multivariable analysis showed that non-smooth margin [odds ratio (OR) = 6.008, p = 0.015] was an independent predictor for the significant inter-modality variation of volume.ConclusionZTE lung imaging is feasible as a part of chest MRI in the assessment and surveillance for solid pulmonary nodules or masses larger than 1 cm, presenting perfect agreement with CT in terms of morphologic characterization.

Background and PurposeFreezing of gait (FOG) is a common gait disturbance phenomenon in multiple system atrophy (MSA) patients. The current investigation assessed the incidence FOG in a cross-sectional clinical study, and clinical correlations associated with it.MethodsNinety-nine MSA patients from three hospitals in China were consecutively enrolled in the study. Eight patients were subsequently excluded from the analysis due to incomplete information. The prevalence of FOG symptoms in the MSA cohort was determined, and clinical manifestations in MSA patients with and without FOG were assessed.ResultsOf 91 MSA patients, 60 (65.93%) exhibited FOG. The incidence of FOG increased with disease duration and motor severity and was correlated with modified Hoehn and Yahr (H-Y) stages [odds ratio (OR), 0.54; 95% confidence interval (CI), 0.33–3.92], longer disease duration (OR, 0.54, 95% CI, 0.37–0.78), higher Unified Multiple System Atrophy Rating Scale (UMSARS) score (OR, 0.96, 95% CI, 0.93–0.99), MSA-cerebellum subtype (OR, 2.99, 95% CI, 1.22–7.33), levodopa-equivalent dose (LDED) (OR, 0.998, 95% CI, 0.997–1.00), and higher Scale for the Assessment and Rating of Ataxia (SARA) score (OR, 0.80, 95% CI, 0.72–0.89) (logistic regression). Motor dysfunction was significantly positively associated with lower quality of life scores (p < 0.01).ConclusionFOG is a common symptom in MSA patients and it is correlated with poor quality of life, disease progression and severity, levodopa-equivalent dose, and cerebellum impairment.

ObjectiveThis study aimed to construct a radiomics-based MRI sequence from high-resolution magnetic resonance imaging (HRMRI), combined with clinical high-risk factors for non-invasive differentiation of the plaque of symptomatic patients from asyptomatic patients.MethodsA total of 115 patients were retrospectively recruited. HRMRI was performed, and patients were diagnosed with symptomatic plaques (SPs) and asymptomatic plaques (ASPs). Patients were randomly divided into training and test groups in the ratio of 7:3. T2WI was used for segmentation and extraction of the texture features. Max-Relevance and Min-Redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) were employed for the optimized model. Radscore was applied to construct a diagnostic model considering the T2WI texture features and patient demography to assess the power in differentiating SPs and ASPs.ResultsSPs and ASPs were seen in 75 and 40 patients, respectively. Thirty texture features were selected by mRMR, and LASSO identified a radscore of 16 radiomics features as being related to plaque vulnerability. The radscore, consisting of eight texture features, showed a better diagnostic performance than clinical information, both in the training (area under the curve [AUC], 0.923 vs. 0.713) and test groups (AUC, 0.989 vs. 0.735). The combination model of texture and clinical information had the best performance in assessing lesion vulnerability in both the training (AUC, 0.926) and test groups (AUC, 0.898).ConclusionThis study demonstrated that HRMRI texture features provide incremental value for carotid atherosclerotic risk assessment.

Chronic kidney disease (CKD) has a significant negative impact on bone health. However, the mechanisms of cortical bone deterioration and cortical porosity enlargement caused by CKD have not been fully described. We therefore examined the association of CKD stages with cortical porosity index (PI), and explored potential mediators of this association. Double-echo ultrashort echo-time magnetic resonance imaging (UTE MRI) provides the possibility of quantifying cortical porosity in vivo. A total of 95 patients with CKD stages 2-5 underwent 3D double-echo UTE-Cones MRI (3.0T) of the midshaft tibia to obtain the PI. PI was defined as the ratio of the image signal intensity of a sufficiently long echo time (TE) to the shortest achievable TE. Parathyroid hormone (PTH), β-CrossLaps (β-CTX), total procollagen type I amino-terminal propeptide (T-P1NP), osteocalcin (OC), 25-hydroxyvitamin D (25OHD), and lumbar bone mineral density (BMD) were measured within one week of the MRI. Partial correlation analysis was performed to address associations between PI, eGFR and potential mediators (PTH, β-CTX, T-P1NP, OC, 25OHD, BMD, and T-score). Multiple linear regression models were used to assess the association between CKD stages and PI value. Then, a separate exploratory mediation analysis was carried out to explore the impact of CKD stages and mediators on the PI value. The increasing CKD stages were associated with a higher PI value (Ptrend < 0.001). The association of CKD stages and PI mediated 34.4% and 30.8% of the total effect by increased PTH and β-CTX, respectively. Our study provides a new idea to monitor bone health in patients with CKD, and reveals the internal mechanism of bone deterioration caused by CKD to some extent.

Objectives: To compare the efficacy of parameters from multiple diffusion magnetic resonance imaging (dMRI) for prediction of isocitrate dehydrogenase 1 (IDH1) genotype and assessment of cell proliferation in gliomas.Methods: Ninety-one patients with glioma underwent diffusion weighted imaging (DWI), multi-b-value DWI, and diffusion kurtosis imaging (DKI)/neurite orientation dispersion and density imaging (NODDI) on 3.0T MRI. Each parameter was compared between IDH1-mutant and IDH1 wild-type groups by Mann–Whitney U test in lower-grade gliomas (LrGGs) and glioblastomas (GBMs), respectively. Further, performance of each parameter was compared for glioma grading under the same IDH1 genotype. Spearman correlation coefficient between Ki-67 labeling index (LI) and each parameter was calculated.Results: The diagnostic performance was better achieved with apparent diffusion coefficient (ADC), slow ADC (D), fast ADC (D∗), perfusion fraction (f), distributed diffusion coefficient (DDC), heterogeneity index (α), mean diffusivity (MD), mean kurtosis (MK), and intracellular volume fraction (ICVF) for distinguishing IDH1 genotypes in LrGGs, with statistically insignificant AUC values from 0.750 to 0.817. In GBMs, no difference between the two groups was found. For IDH1-mutant group, all parameters, except for fractional anisotropy (FA) and D∗, significantly discriminated LrGGs from GBMs (P < 0.05). However, for IDH1 wild-type group, only ADC statistically discriminated the two (P = 0.048). In addition, MK has maximal correlation coefficient (r = 0.567, P < 0.001) with Ki-67 LI.Conclusion: dMRI-derived parameters are promising biomarkers for predicting IDH1 genotype in LrGGs, and MK has shown great potential in assessing glioma cell proliferation.

This study aimed to evaluate the difference in wall shear stress (WSS) (axial, circumferential, and 3D) between high-risk and low-risk plaques in patients with moderate carotid artery stenosis and to identify which time points and directions play the dominant roles in determining the risk associated with plaques. Forty carotid arteries in 30 patients were examined in this study. All patients underwent high-resolution vessel wall (HRVW) imaging, diffusion-weighted imaging (DWI), and 4D flow MRI; HRVW imaging and DWI were used to separate low- and high-risk plaque. Twenty-four high-risk plaques and 16 low-risk plaques were enrolled. An independent-sample t-test was used to compare WSS between low- and high-risk plaques in the whole cardiac cycle and at 20 different time points in the cardiac cycle. The study found that patients with high-risk plaques had higher WSS than those with low-risk plaques throughout the entire cardiac cycle (p < 0.05), but the changes varied at the 20 different time points. The number of non-significant differences (p > 0.05) was less in diastole than in systole across different time points. The axial WSS values were higher than the circumferential WSS values; the difference in axial WSS values between high- and low-risk plaques was more significant than the difference in circumferential WSS, whereas 3D WSS values best reflected the difference between high-risk and low-risk plaques because they showed significant differences at every time point. In conclusion, increased WSS, especially during the diastolic period and in the axial direction, may be a signal of a high-risk plaque and may cause cerebrovascular events in patients with moderate carotid artery stenosis. Additionally, WSS can provide hemodynamic information and help clinicians make more appropriate decisions for patients with plaques.

Objective: This study aims to evaluate the feasibility of visualizing nasal cartilage using deep-learning-based reconstruction (DLR) fast spin-echo (FSE) imaging in comparison to three-dimensional fast spoiled gradient-echo (3D FSPGR) images. Materials and Methods: This retrospective study included 190 set images of 38 participants, including axial T1- and T2-weighted FSE images using DLR (T1WIDL and T2WIDL, belong to FSEDL) and without using DLR (T1WIO and T2WIO, belong to FSEO) and 3D FSPGR images. Subjective evaluation (overall image quality, noise, contrast, artifacts, and identification of anatomical structures) was independently conducted by two radiologists. Objective evaluation including signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) was conducted using manual region-of-interest (ROI)-based analysis. Coefficient of variation (CV) and Bland–Altman plots were used to demonstrate the intra-rater repeatability of measurements for cartilage thickness on five different images. Results: Both qualitative and quantitative results confirmed superior FSEDL to 3D FSPGR images (both p < 0.05), improving the diagnosis confidence of the observers. Lower lateral cartilage (LLC), upper lateral cartilage (ULC), and septal cartilage (SP) were relatively well delineated on the T2WIDL, while 3D FSPGR showed poorly on the septal cartilage. For the repeatability of cartilage thickness measurements, T2WIDL showed the highest intra-observer (%CV = 8.7% for SP, 9.5% for ULC, and 9.7% for LLC) agreements. In addition, the acquisition time for T1WIDL and T2WIDL was respectively reduced by 14.2% to 29% compared to 3D FSPGR (both p < 0.05). Conclusions: Two-dimensional equivalent-thin-slice T1- and T2-weighted images using DLR showed better image quality and shorter scan time than 3D FSPGR and conventional construction images in nasal cartilages. The anatomical details were preserved without losing clinical performance on diagnosis and prognosis, especially for pre-rhinoplasty planning.