CT-Based Radiomics Models for Differentiation of Benign and Malignant Thyroid Nodules: A Multicenter Development and Validation Study.

BACKGROUND. CT is increasingly detecting thyroid nodules. Prior studies indicated a potential role of CT-based radiomics models in characterizing thyroid nodules, although these studies lacked external validation. OBJECTIVE. The purpose of this study was to develop and validate a CT-based radiomics model for the differentiation of benign and malignant thyroid nodules. METHODS. This retrospective study included 378 patients (mean age, 46.3 ± 13.9 [SD] years; 86 men, 292 women) with 408 resected thyroid nodules (145 benign, 263 malignant) from two centers (center 1: 293 nodules, January 2018 to December 2022; center 2: 115 nodules, January 2020 to December 2022) who underwent preoperative multiphase neck CT (noncontrast, arterial, and venous phases). Nodules from center 1 were divided into training (n = 206) and internal validation (n = 87) sets; all nodules from center 2 formed an external validation set. Radiologists assessed nodules for morphologic CT features. Nodules were manually segmented on all phases, and radiomic features were extracted. Conventional (clinical and morphologic CT), noncontrast CT radiomics, arterial phase CT radiomics, venous phase CT radiomics, multiphase CT radiomics, and combined (clinical, morphologic CT, and multiphase CT radiomics) models were established using feature selection methods and evaluated by ROC curve analysis, calibration-curve analysis, and decision-curve analysis. RESULTS. The combined model included patient age, three morphologic features (cystic change, "edge interruption" sign, abnormal cervical lymph nodes), and 28 radiomic features (from all three phases). In the external validation set, the combined model had an AUC of 0.923, and, at an optimal threshold derived in the training set, sensitivity of 84.0%, specificity of 94.1%, and accuracy of 87.0%. In the external validation set, the AUC was significantly higher for the combined model than for the conventional model (0.827), noncontrast CT radiomics model (0.847), arterial phase CT radiomics model (0.826), venous phase CT radiomics model (0.773), and multiphase CT radiomics model (0.824) (all p < .05). In the external validation set, the calibration curves indicated the lowest (i.e., best) Brier score for the combined model; in the decision-curve analysis, the combined model had the highest net benefit for most of the range of threshold probabilities. CONCLUSION. A combined model incorporating clinical, morphologic CT, and multiphase CT radiomics features exhibited robust performance in differentiating benign and malignant thyroid nodules. CLINICAL IMPACT. The combined radiomics model may help guide further management for thyroid nodules detected on CT.

The aging of glymphatic system in human brain and its correlation with brain charts and neuropsychological functioning.

This study aimed to investigate the aging of the glymphatic system in healthy adults, and to determine whether this change is correlated with the brain charts and neuropsychological functioning. Two independent brain 3.0 T MRI datasets were analyzed: a public dataset and our hospital-own dataset from two hospitals. The function of the glymphatic system was quantified by diffusion analysis along the perivascular space (ALPS) index via an automatic method. Brain charts were calculated online. Correlations of the ALPS index with the brain charts, age, gender, and neuropsychological functioning, as well as differences in ALPS index across age groups, were assessed. A total of 161 healthy volunteers ranging in age from 20 to 87 years were included. ALPS index was negatively correlated with the age in both independent datasets. Compared with that of the young group, the ALPS index was significantly lower in the elderly group. No significant difference was found in the ALPS index between different genders. In addition, the ALPS index was not significantly correlated with the brain charts and neuropsychological functioning. In conclusion, the aging of glymphatic system exists in healthy adults, which is not correlated with the changes of brain charts and neuropsychological functioning.

Quantitative morphometric changes in vascular mild cognitive impairment patients: early diagnosis of dementia.

Vascular mild cognitive impairment (VMCI) is an early and reversible stage of dementia. Volume differences in regional gray matter may reveal the development and prognosis of VMCI. This study selected 2 of the most common types of VMCI, namely, periventricular white matter hyperintensities (PWMH, n = 14) and strategic single infarctions (SSI, n = 10), and used the voxel-based morphometry method to quantify their morphological characteristics. Meanwhile, age- and sex-matched healthy volunteers were included (n = 16). All the participants were neuropsychologically tested to characterize their cognitive function and underwent whole-brain magnetic resonance imaging scanning. Our results showed that the volumes of the bilateral temporal lobes and bilateral frontal gray matter were obviously diminished in the PWMH group. The atrophy volume difference was 4,086 voxels in the left temporal lobe, 4,154 voxels in the right temporal lobe, 1,718 voxels in the left frontal lobe, and 1,141 voxels in the right frontal lobe (P ≤ 0.001). Moreover, the characteristics of the gray matter atrophy associated with the PWMH were more similar to those associated with Alzheimer's disease than SSI, which further revealed the susceptibility for escalation from PWMH to dementia. In conclusion, PWMH patients and SSI patients have different morphological characteristics, which explain the different prognoses of VMCI.

Early prediction of pathological complete response to neoadjuvant chemotherapy combining DCE-MRI and apparent diffusion coefficient values in breast Cancer.

INTRODUCTION: Improving the early prediction of neoadjuvant chemotherapy (NAC) efficacy in breast cancer can lead to an improved prediction of the final prognosis of patients, which would be useful for promoting individualized treatment. This study aimed to explore the value of the combination of dynamic contrast-enhanced (DCE)-MRI parameters and apparent diffusion coefficient (ADC) values in the early prediction of pathological complete response (pCR) to NAC for breast cancer. METHODS: A total of 119 (range, 28-69 years) patients with biopsy-proven breast cancer who received two cycles of NAC before breast surgery were retrospectively enrolled from our hospital database. Patients were divided into pCR and non pCR groups according to their pathological responses; a total of 24 patients achieved pCR, while 95 did not. The quantitative (Ktrans; Kep; Ve; IAUC) and semiquantitative parameters (W-in; W-out; TTP) of DCE-MRI that were significantly different between groups were combined with ADC values to explore their value in the early prediction of pCR to NAC for breast cancer. The independent T test was performed to compare the differences in DCE-MRI parameters and ADC values between the two groups. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC), sensitivity and specificity were calculated to evaluate the performance of the prediction. RESULTS: The Ktrans, Kep, IAUC, ADC, W-in and TTP values were significantly different between the pCR and non pCR groups after NAC. The AUC (0.845) and specificity (95.79%) of the combined Ktrans, Kep, IAUC and ADC values were both higher than those of the individual parameters. The combination of W-in, TTP and ADC values had the highest AUC value (0.886) in predicting pCR, with a sensitivity and specificity of 87.5% and 82.11%, respectively. CONCLUSIONS: The results suggested that the combination of ADC values and quantitative and semiquantitative DCE-MRI parameters, especially the combination of W-in, TTP, and ADC values, may improve the early prediction of pCR in breast cancer.

Readout-Segmented Echo-Planar Diffusion-Weighted MR Imaging Improves the Differentiation of Breast Cancer Receptor Statuses Compared With Conventional Diffusion-Weighted Imaging.

BACKGROUND: Readout-segmented echo-planar diffusion-weighted imaging (RS-EPI) can improve image quality and signal-to-noise ratio, the resulting apparent diffusion coefficient (ADC) value acts as a more sensitive biomarker to characterize tumors. However, data regarding the differentiation of breast cancer (BC) receptor statuses using RS-EPI are limited. PURPOSE: To determine whether RS-EPI improves the differentiation of receptor statuses compared with conventional single-shot (SS) EPI in breast MRI. STUDY TYPE: Retrospective. POPULATION: A total of 151 BC women with the mean age of 50.6 years. FIELD STRENGTH/SEQUENCE: A 3 T/ RS-EPI and SS-EPI. ASSESSMENT: The ADCs of the lesion and normal background tissue from the two sequences were collected by two radiologists with 15 years of experience working of breast MRI (M.H.Z. and X.F.C.), and a normalized ADC was calculated by dividing the mean ADC value of the lesion by the mean ADC value of the normal background tissue. STATISTICAL TESTS: Agreement between the ADC measurements from the two sequences was assessed using the Pearson correlation coefficient and Bland-Altman plots. One-way analysis of variance, Kruskal-Wallis test, and median difference were used to compare the ADC measurements for all lesions and different receptor statuses. A P value less than 0.05 indicated a significant result. RESULTS: The ADC measurements of all lesions and normal background tissues were significantly higher on RS-EPI than on SS-EPI (1.82 ± 0.33 vs. 1.55 ± 0.30 and 0.83 ± 0.11 vs. 0.79 ± 0.10). The normalized ADC was lower on RS-EPI than on SS-EPI (0.47 ± 0.11 vs. 0.53 ± 0.12, a median difference of -0.04 [95% CI: -0.256 to 0.111]). For both diffusion methods, only the ADC measurement of RS-EPI was higher for human epidermal growth factor receptor-2 (HER-2)-positive tumors than for HER-2-negative tumors (0.87 ± 0.10 vs. 0.81 ± 0.11), and this measurement was associated with HER-2 positive status (adjusted odds ratio [OR] = 654.4); however, similar results were not observed for the ADC measurement of SS-EPI (0.80 ± 0.10 vs. 0.78 ± 0.11 with P = 0.199 and adjusted OR = 0.21 with P = 0.464, respectively). DATA CONCLUSION: RS-EPI can improve the distinction between HER-2-positive and HER-2-negative breast cancer, complementing the clinical application of diffusion imaging. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Amide signal intensities may be reduced in the motor cortex and the corticospinal tract of ALS patients.

OBJECTIVES: The aim of the study is to assess amide concentration changes in ALS patients compared with healthy controls by using quantitative amide proton transfer (APT) and multiparameter magnetic resonance imaging, and testing its correlation with clinical scores. METHODS: Sixteen ALS patients and sixteen healthy controls were recruited as part of the Canadian ALS Neuroimaging Consortium, and multimodal magnetic resonance imaging was performed at 3 T, including APT and diffusion imaging. Lorentz fitting was used to quantify the amide effect. Clinical disability was evaluated using the revised ALS functional rating scale (ALSFRS-R), and its correlation with image characteristics was assessed. The diagnostic performance of different imaging parameters was evaluated with receiver operating characteristic analysis. RESULTS: Our results showed that the amide peak was significantly different between the motor cortex and other gray matter territories within the brain of ALS patients (p < 0.001). Compared with controls, amide signal intensities in ALS were significantly reduced in the motor cortex (p < 0.001) and corticospinal tract (p = 0.046), while abnormalities were not detected using routine imaging methods. There was no significant correlation between amide and ALSFRS-R score. The diagnostic accuracy of the amide peak was superior to that of diffusion imaging. CONCLUSIONS: This study demonstrated changes of amide signal intensities in the motor cortex and corticospinal tract of ALS patients. KEY POINTS: • The neurodegenerative disease amyotrophic lateral sclerosis (ALS) has a lack of objective imaging indicators for diagnosis and assessment. • Analysis of amide proton transfer imaging revealed changes in the motor cortex and corticospinal tract of ALS patients that were not visible on standard magnetic resonance imaging. • The diagnostic accuracy of the amide peak was superior to that of diffusion imaging.

Atypical presentations of coronavirus disease 2019 (COVID-19) from onset to readmission.

BACKGROUND: To investigate the CT imaging and clinical features of three atypical presentations of coronavirus disease 2019 (COVID-19), namely (1) asymptomatic, (2) CT imaging-negative, and (3) re-detectable positive (RP), during all disease stages. METHODS: A consecutive cohort of 79 COVID-19 patients was retrospectively recruited from five independent institutions. For each presentation type, all patients were classified into atypical vs. typical groups (i.e., asymptomatic vs.symptomatic, CT imaging-negative vs. CT imaging-positive, and RP and non-RP,respectively). The chi-square test, Student's t test, and Kruskal-Wallis H test were performed to compare CT imaging and clinical features of atypical vs. typical patients for all three presentation categories. RESULTS: In our COVID-19 cohort, we found 12.7% asymptomatic patients, 13.9% CT imaging-negative patients, and 8.9% RP patients. The asymptomatic patients had fewer hospitalization days (P=0.043), lower total scores for bilateral lung involvement (P< 0.001), and fewer ground-glass opacities (GGOs) in the peripheral area (P< 0.001) than symptomatic patients. The CT imaging-negative patients were younger (P=0.002), had a higher lymphocyte count (P=0.038), had a higher lymphocyte rate (P=0.008), and had more asymptomatic infections (P=0.002) than the CT imaging-positive patients. The RP patients with moderate COVID-19 had lower total scores of for bilateral lung involvement (P=0.030) and a smaller portion of the left lung affected (P=0.024) than non-RP patients. Compared to their first hospitalization, RP patients had a shorter hospitalization period (P< 0.001) and fewer days from the onset of illness to last RNA negative conversion (P< 0.001) at readmission. CONCLUSIONS: Significant CT imaging and clinical feature differences were found between atypical and typical COVID-19 patients for all three atypical presentation categories investigated in this study, which may help provide complementary information for the effective management of COVID-19.

A diagnostic model for coronavirus disease 2019 (COVID-19) based on radiological semantic and clinical features: a multi-center study.

OBJECTIVES: Rapid and accurate diagnosis of coronavirus disease 2019 (COVID-19) is critical during the epidemic. We aim to identify differences in CT imaging and clinical manifestations between pneumonia patients with and without COVID-19, and to develop and validate a diagnostic model for COVID-19 based on radiological semantic and clinical features alone. METHODS: A consecutive cohort of 70 COVID-19 and 66 non-COVID-19 pneumonia patients were retrospectively recruited from five institutions. Patients were divided into primary (n = 98) and validation (n = 38) cohorts. The chi-square test, Student's t test, and Kruskal-Wallis H test were performed, comparing 1745 lesions and 67 features in the two groups. Three models were constructed using radiological semantic and clinical features through multivariate logistic regression. Diagnostic efficacies of developed models were quantified by receiver operating characteristic curve. Clinical usage was evaluated by decision curve analysis and nomogram. RESULTS: Eighteen radiological semantic features and seventeen clinical features were identified to be significantly different. Besides ground-glass opacities (p = 0.032) and consolidation (p = 0.001) in the lung periphery, the lesion size (1-3 cm) is also significant for the diagnosis of COVID-19 (p = 0.027). Lung score presents no significant difference (p = 0.417). Three diagnostic models achieved an area under the curve value as high as 0.986 (95% CI 0.966~1.000). The clinical and radiological semantic models provided a better diagnostic performance and more considerable net benefits. CONCLUSIONS: Based on CT imaging and clinical manifestations alone, the pneumonia patients with and without COVID-19 can be distinguished. A model composed of radiological semantic and clinical features has an excellent performance for the diagnosis of COVID-19. KEY POINTS: • Based on CT imaging and clinical manifestations alone, the pneumonia patients with and without COVID-19 can be distinguished. • A diagnostic model for COVID-19 was developed and validated using radiological semantic and clinical features, which had an area under the curve value of 0.986 (95% CI 0.966~1.000) and 0.936 (95% CI 0.866~1.000) in the primary and validation cohorts, respectively.

Brain metabolite changes in subcortical regions after exposure to cuprizone for 6 weeks: potential implications for schizophrenia.

Cuprizone is a copper chelating agent able to selectively damage the white matter in the mouse brain. Recent studies have reported behavioral abnormalities relevant to some of schizophrenia symptoms. While associating white matter damage to the behavioral abnormalities, these previous studies did not rule out the possible impairment in neuronal functions in cuprizone-exposed mice. The aim of this study was to examine brain metabolites of the cuprizone-exposed mice by proton magnetic resonance spectroscopy ((1)H-MRS). The examined brain regions were the caudoputamen, midbrain, and thalamus; these subcortical regions showed different susceptibilities to cuprizone in terms of demyelination and oligodendrocyte loss in previous studies. Young C57BL/6 mice were fed a standard rodent chow without or with cuprizone (0.2 %) for 6 weeks. At the end, open-field and Y-maze tests were performed to measure the emotional and cognitive behaviors of the animals, followed by (1)H-MRS procedure to evaluate the brain metabolites. Cuprizone-exposure increased anxiety levels and impaired spatial working memory. The same treatment increased T2 signal intensity in the cerebral cortex, hippocampus, and caudoputamen, but not in the thalamus. Cuprizone-exposure decreased the concentrations of NAA and NAA+NAAG in caudoputamen, but not in thalamus and midbrain. It decreased levels of Cr+PCr, GPC+PCh and myo-inositol in all the three brain regions. These results provided neurochemical evidence for the impairment in neuronal functions by cuprizone treatment.

Anterior cingulate cortex and cerebellar hemisphere neurometabolite changes in depression treatment: A 1H magnetic resonance spectroscopy study.

AIM: We utilized single-voxel 1H magnetic resonance spectroscopy to determine biochemical abnormalities related to major depressive disorder (MDD) in the bilateral dorsolateral prefrontal cortex, anterior cingulate cortex (ACC), and cerebellar hemisphere before and after antidepressant treatment. METHODS: Fifteen adult MDD patients and 15 age- and sex-matched healthy controls were involved. Magnetic resonance spectroscopy of the brain was conducted in all subjects at the beginning of the study and the depressed subjects were reassessed after 8 weeks of antidepressant treatment. RESULTS: At baseline, N-acetyl aspartate (NAA), total glutamine plus glutamate (Glx) and myo-inositol (MI) levels in the bilateral ACC were significantly lower in MDD patients than in controls (P < 0.05/3). MI in the bilateral cerebellar hemisphere were also decreased in patients compared with controls. After the treatment, the lower NAA, Glx and MI in ACC were normalized in MDD patients and the NAA and Glx increased compared to baseline values. The MI levels in the bilateral cerebellar hemisphere were also normalized in patients. MI and choline levels in the right cerebellar hemisphere were elevated compared to those at baseline. CONCLUSION: Our study suggests that metabolic abnormalities in the ACC and cerebellar hemisphere are implicated in MDD. Antidepressants may alter the local metabolic abnormalities in these areas.

Dual-phase contrast-enhanced multislice computed tomography scans play a key role in the diagnosis of abdominal wall desmoid-type fibromatoses.

BACKGROUND: Abdominal wall desmoid-type fibromatoses (AWDF) are occasionally encountered in clinical work, but related CT reports are rare, and most cases were misdiagnosed as malignant tumors. OBJECTIVE: We aimed to determine the diagnostic value of multislice computed tomography (MSCT) in relation to the clinical diagnosis of AWDF. METHODS: The medical records of 14 patients whose pathology results provided initial confirmation of AWDF were reviewed, and data describing their clinical characteristics, tumors' MSCT characteristics, and the condition of the surrounding tissues were analyzed and summarized retrospectively. Intraobserver and interobserver reproducibilities were evaluated. RESULTS: AWDF tended to occur in women of childbearing age (24-32 years). They occurred more frequently during the first year following pregnancy. The mean disease duration was 5.64 ± 3.78 months. All isolated tumors were growing along the musculoaponeurotic layer, and their maximum diameters were between 32 and 76 mm. Tumors' capsules were incomplete, and although the tumors infiltrated the surrounding muscles, the surrounding fat tissue and vessels were not infiltrated. None of the patients' tumors showed cystic degeneration, calcification, necrosis, or peritumoral edema. The tumors had slightly lower densities on the pre-contrast enhancement scans and mild-to-moderate enhancement after contrast enhancement. All tumors contained ribbon-like structures, and approximately 65% of the tumors encircled vascular structures. CONCLUSION: Dual-phase contrast-enhanced MSCT scans were associated with a high level of diagnostic efficacy for AWDF. The abdominal wall masses grew along the musculoaponeurotic layer, which, together with the ribbon-like structures within the tumors, should prompt clinicians to consider the presence of AWDF.

Gemstone Spectral CT Virtual Noncontrast Images and Iodine Maps for the Characterization of Thyroid Lesions and Distinguishing Thyroid Papillary Carcinoma from Nodular Goiter.

Background: Gemstone spectral contrast-enhanced CT with virtual noncontrast (VNC) images and iodine maps can potentially reduce the number of required CT scans for thyroid lesions. However, data regarding the clinical utility of VNC images and iodine maps in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter are still limited. Purpose: To determine whether VNC images and iodine density could reliably aid in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter compared with true noncontrast (TNC) images. Methods: This retrospective study included patients with thyroid papillary carcinoma or nodular goiter who underwent TNC and contrast-enhanced gemstone spectral CT scans. The consistency of qualitative parameters, including intralesional calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis, between TNC and VNC images, was analyzed using the kappa statistic. TNC attenuation, VNC attenuation, absolute attenuation between TNC and VNC, and iodine density were compared between thyroid papillary carcinoma and nodular goiter by using Student's t-test. The diagnostic performance for distinguishing papillary carcinoma from nodular goiter was evaluated by using the area under the receiver operating characteristic curve (AUC) value, sensitivity, and specificity. Results: VNC and TNC imaging showed comparable performance in delineating calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis (all k > 0.75). Papillary carcinoma showed significantly lower absolute attenuation between VNC and TNC than nodular goiter (7.86 ± 6.74 vs. 13.43 ± 10.53, P=0.026), which was similarly observed for iodine density (31.45 ± 8.51 vs. 37.27 ± 10.34, P=0.016). The iodine density showed higher diagnostic performance (AUC = 0.727), accuracy (0.773 vs. 0.667), sensitivity (0.750 vs. 0.708), and specificity (0.786 vs. 0.643) than the absolute attenuation between TNC and VNC images (AUC = 0.683). Conclusions: VNC imaging, a promising substitute for TNC imaging, has comparable diagnostic efficacy for reliably characterizing thyroid lesions. Iodine density could be valuable for distinguishing thyroid papillary carcinoma from nodular goiter.

Bone marrow stromal cells-derived exosomes reduce neurological damage in traumatic brain injury through the miR-124-3p/p38 MAPK/GLT-1 axis.

BACKGROUND: Mounting evidence indicates that stem cell-derived exosomal miRNAs have therapeutic effects on traumatic brain injury (TBI). This research is focused on exploring the molecular processes of miR-124-3p obtained from bone marrow stromal cells-derived exosomes (BMSCs-Exos) in attenuating posttraumatic glutamate-mediated excitotoxicity. METHODS: We created a TBI rat model and analyzed the expression profile of miRNA through miRNA microarray. The miR-124-3p and p38 MAPK levels were analyzed utilizing RT-qPCR and western blotting. Dual-luciferase reporter (DLR) assay showed the targeting relationship between miR-124-3p and p38 MAPK. We subsequently conducted a TUNEL assay and flow cytometry to evaluate the neuronal apoptotic rate in an in vitro glutamate-mediated excitotoxicity model treated with BMSCs-Exos enriched with miR-124-3p (BMSCs-ExosmiR-124-3p). Moreover, the levels of p38 MAPK and glutamate transporter-1 (GLT-1) were measured by western blotting. Furthermore, BMSCs-ExosmiR-124-3p were administered to the TBI rats, and their neuroprotective effects were observed using western blotting, immunohistochemistry, histological staining, magnetic resonance imaging (MRI), and Morris water maze (MWM). RESULTS: The results revealed that the brains of TBI rats exhibited lowered miR-124-3p and enhanced p38 MAPK levels. DLR assay demonstrated miR-124-3p's role in targeting p38 MAPK and negatively regulating its expression. In vitro and in vivo studies confirmed that BMSCs-ExosmiR-124-3p attenuated glutamate-mediated excitotoxicity by downregulating p38 MAPK and upregulating GLT-1 expressions via transferring exosomal miR-124-3p. Moreover, histopathological evaluation and MRI results showed that BMSCs-ExosmiR-124-3p remarkably alleviated neuronal cell death and minimized the lesion volumes post-TBI. MWM outcomes illustrated that BMSCs-ExosmiR-124-3p treatment could substantially improve neurological function post-TBI. Furthermore, the effects of treatment with p38 MAPK inhibitor SB203580 were similar to BMSCs-ExosmiR-124-3p. CONCLUSION: Overall, the outcomes of the current report highlighted that BMSCs-ExosmiR-124-3p can lead to the upregulation of GLT-1 in TBI rat models by inhibiting the p38 MAPK signaling pathway, hence alleviating glutamate-mediated excitotoxicity and attenuating neurological damage post-TBI.

Ultrasound features affecting the sample adequacy after fine-needle aspiration of thyroid nodules with different risk stratification.

BACKGROUND: The inadequacy samples caused by the internal characteristic structure of thyroid nodules are difficult to be solved. OBJECTIVE: To evaluate the ultrasound features affecting the sample adequacy after fine-needle aspiration (FNA) of thyroid nodules with different risk stratification. METHODS: 592 thyroid nodules that underwent ultrasound-guided FNA were included in this retrospective study. The sample obtained by FNA were classified as inadequacy and adequacy according to the cytopathological results. Ultrasound features (ie., size, position, cystic predominance, composition, echo, shape, margin, and superficial annular calcification status) of the nodules were recorded and compared between the inadequacy sample group and adequacy sample group. RESULTS: Multiple logistic regression shows that preponderant cystic proportion (OR, 0.384; P = 0.041), extremely hypoechogenicity and hypoechogenicity (OR, 6.349; P = 0.006) were the independent influencing factors of inadequate samples after FNA in benign expected nodules. In addition, nodule size ≤10 mm (OR, 1.960; P = 0.010) and superficially annular calcification (OR, 4.600; P < 0.001) were independent influencing factors for inadequate samples after FNA in malignant expected nodules. CONCLUSION: The ultrasound features of hypoechogenicity or high cystic proportion in benign expected nodules and that of small size or annular calcification in malignant expected nodules were the risk factors for inadequacy samples by US-guided FNA.

Combined fine-needle aspiration with core needle biopsy for assessing thyroid nodules: a more valuable diagnostic method?

PURPOSE: This study aimed to evaluate the diagnostic value of combined fine-needle aspiration (FNA) with core needle biopsy (CNB) in thyroid nodules. METHODS: FNA and CNB were performed simultaneously on 703 nodules. We compared the proportions of inconclusive results and the diagnostic performance for malignancy among FNA, CNB, and combined FNA/CNB for different nodule sizes. RESULTS: Combined FNA/CNB showed lower proportions of inconclusive results than CNB for all nodules (2.8% vs. 5.7%, P<0.001), nodules ≤1.0 cm (4.9% vs. 7.3%, P=0.063), nodules >1.0 cm (2.0% vs. 5.0 %, P<0.001), nodules ≤1.5 cm (3.8% vs. 7.9 %, P<0.001), and nodules >1.5 cm (2.1% vs. 3.9 %, P=0.016). The sensitivity of combined FNA/CNB in predicting malignancy was significantly higher than that of CNB (89.0% vs. 80.0%, P<0.001) and FNA (89.0% vs. 58.1%, P<0.001) for all nodules. Within American College of Radiology Thyroid and Imaging Reporting and Data System grades 4-5, in the subgroup of nodules ≤1.5 cm, combined FNA/ CNB showed the best sensitivity in predicting malignancy (91.4%), significantly higher than that of CNB (81.0%, P<0.001) and FNA (57.8%, P<0.001). However, in the subgroup of nodules >1.5 cm, the difference between combined FNA/CNB and CNB was not significant (84.2% vs. 78.9%, P=0.500). CONCLUSION: Regardless of nodule size, combined FNA/CNB tended to yield lower proportions of inconclusive results than CNB or FNA alone and exhibited higher performance in diagnosing malignancy. The combined FNA/CNB technique may be a more valuable diagnostic method for nodules ≤1.5 cm and nodules with a risk of malignancy than CNB and FNA alone.

The value of quantitative plaque analysis based on coronary computed tomography angiography in predicting the percutaneous coronary intervention outcome of chronic total occlusion lesions.

Background: Due to the uncertainty of the success of percutaneous coronary intervention (PCI) and the complexity of selecting suitable treatment cases, the interventional outcome of coronary chronic total occlusion (CTO) remains challenging. The purpose of this study was to evaluate the role of quantitative plaque analysis based on coronary computed tomography angiography (CCTA) in predicting the CTO-PCI outcome. Methods: We retrospectively included 78 patients with CTO (80 lesions) confirmed by invasive coronary angiography from July 2016 to December 2018. All patients underwent PCI treatment according to standard practice. A total of 47 lesions in 47 patients were successfully treated with PCI. PCI failed in the remaining 33 lesions in 31 patients. The following conventional CCTA morphologic parameters were evaluated and compared between the PCI-success and PCI-failure groups: stump morphology; occlusion length, tortuous course; CTO lesion calcium; bridging collateral vessel; retrograde collateral vessel; the appearance of the occluded distal segment; and quantitative CTO plaque characteristics, including total plaque volume, calcified plaque (CP) volume, noncalcified plaque (NCP) volume, low-density noncalcified plaque (LDNCP) volume, and plaque length. Univariate and multivariate logistic regression analyses were performed to determine independent parameters predictive of CTO-PCI outcomes. The predictive performances were assessed using receiver operating characteristic curve analysis. Results: The blunt stump was the only independent CCTA morphologic parameter to predict the outcome of CTO-PCI [odds ratio (OR): 10.807; P<0.001]. NCP volume (OR: 1.018; P<0.001), CP volume (OR: 1.026; P=0.049), and plaque length (OR: 1.058; P=0.037) were independent quantitative CTO plaque characteristics predictive of CTO-PCI outcomes. The plaque-based model combining NCP volume with CP volume and plaque length had a higher area under the curve (AUC =0.96) than did the morphology-based model that included blunt stump (AUC 0.68) in predicting the outcomes of CTO-PCI (P<0.001). Conclusions: The CCTA-based plaque characteristics, including NCP volume, CP volume, and plaque length, outperformed morphologic parameters in predicting the CTO-PCI outcomes.

Increased glymphatic system activity in patients with mild traumatic brain injury.

Purpose: This study aims to investigate the glymphatic system activity changes in patients with mild traumatic brain injury (mTBI), particularly in MRI-negative patients, using analysis along the perivascular space (ALPS) technology. Methods: A total of 161 mTBI patients (age: 15-92 years old) and 28 healthy controls (age: 15-84 years old) were included in this retrospective study. The mTBI patients were divided into MRI-negative and MRI-positive groups. ALPS index was calculated automatically using whole-brain T1-MPRAGE imaging and diffusion tensor imaging. The Student's t and chi-squared tests were performed to compare the ALPS index, age, gender, course of disease, and Glasgow Coma Scale (GCS) score between groups. Correlations among ALPS index, age, course of disease and GCS score were computed using Spearman's correlation analysis. Results: Increased activity of the glymphatic system was suggested in mTBI patients based on ALPS index analysis, including the MRI-negative patients. There was a significant negative correlation between the ALPS index and age. In addition, a weak positive correlation between the ALPS index and course of disease was also observed. On the contrary, there was no significant correlation between the ALPS index and sex nor between the ALPS index and GCS score. Conclusion: Our study demonstrated that the activity level of the glymphatic system was enhanced in mTBI patients, even when their brain MRI scans were negative. These findings may provide novel insights for understanding the pathophysiology of mild TBI.

Development and validation of a point-based scoring system for predicting axillary lymph node metastasis and disease outcome in breast cancer using clinicopathological and multiparametric MRI features.

BACKGROUND: Axillary lymph node (ALN) metastasis is used to select treatment strategies and define the prognosis in breast cancer (BC) patients and is typically assessed using an invasive procedure. Noninvasive, simple, and reliable tools to accurately predict ALN status are desirable. We aimed to develop and validate a point-based scoring system (PSS) for stratifying the ALN metastasis risk of BC based on clinicopathological and quantitative MRI features and to explore its prognostic significance. METHODS: A total of 219 BC patients were evaluated. The clinicopathological and quantitative MRI features of the tumors were collected. A multivariate logistic regression analysis was used to create the PSS. The performance of the models was evaluated using receiver operating characteristic curves, and the area under the curve (AUC) of the models was calculated. Kaplan-Meier curves were used to analyze the survival outcomes. RESULTS: Clinical features, including the American Joint Committee on Cancer (AJCC) stage, T stage, human epidermal growth factor receptor-2, estrogen receptor, and quantitative MRI features, including maximum tumor diameter, Kep, Ve, and TTP, were identified as risk factors for ALN metastasis and were assigned scores for the PSS. The PSS achieved an AUC of 0.799 in the primary cohort and 0.713 in the validation cohort. The recurrence-free survival (RFS) and overall survival (OS) of the high-risk (> 19.5 points) groups were significantly shorter than those of the low-risk (≤ 19.5 points) groups in the PSS. CONCLUSION: PSS could predict the ALN metastasis risk of BC. A PSS greater than 19.5 was demonstrated to be a predictor of short RFS and OS.

Development of a CT image analysis-based scoring system to differentiate gastric schwannomas from gastrointestinal stromal tumors.

Purpose: To develop a point-based scoring system (PSS) based on contrast-enhanced computed tomography (CT) qualitative and quantitative features to differentiate gastric schwannomas (GSs) from gastrointestinal stromal tumors (GISTs). Methods: This retrospective study included 51 consecutive GS patients and 147 GIST patients. Clinical and CT features of the tumors were collected and compared. Univariate and multivariate logistic regression analyses using the stepwise forward method were used to determine the risk factors for GSs and create a PSS. Area under the receiver operating characteristic curve (AUC) analysis was performed to evaluate the diagnostic efficiency of PSS. Results: The CT attenuation value of tumors in venous phase images, tumor-to-spleen ratio in venous phase images, tumor location, growth pattern, and tumor surface ulceration were identified as predictors for GSs and were assigned scores based on the PSS. Within the PSS, GS prediction probability ranged from 0.60% to 100% and increased as the total risk scores increased. The AUC of PSS in differentiating GSs from GISTs was 0.915 (95% CI: 0.874-0.957) with a total cutoff score of 3.0, accuracy of 0.848, sensitivity of 0.843, and specificity of 0.850. Conclusions: The PSS of both qualitative and quantitative CT features can provide an easy tool for radiologists to successfully differentiate GS from GIST prior to surgery.

Quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging to predict lymphovascular invasion and survival outcome in breast cancer.

BACKGROUND: Lymphovascular invasion (LVI) predicts a poor outcome of breast cancer (BC), but LVI can only be postoperatively diagnosed by histopathology. We aimed to determine whether quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can preoperatively predict LVI and clinical outcome of BC patients. METHODS: A total of 189 consecutive BC patients who underwent multiparametric MRI scans were retrospectively evaluated. Quantitative (Ktrans, Ve, Kep) and semiquantitative DCE-MRI parameters (W- in, W- out, TTP), and clinicopathological features were compared between LVI-positive and LVI-negative groups. All variables were calculated by using univariate logistic regression analysis to determine the predictors for LVI. Multivariate logistic regression was used to build a combined-predicted model for LVI-positive status. Receiver operating characteristic (ROC) curves evaluated the diagnostic efficiency of the model and Kaplan-Meier curves showed the relationships with the clinical outcomes. Multivariate analyses with a Cox proportional hazard model were used to analyze the hazard ratio (HR) for recurrence-free survival (RFS) and overall survival (OS). RESULTS: LVI-positive patients had a higher Kep value than LVI-negative patients (0.92 ± 0.30 vs. 0.81 ± 0.23, P = 0.012). N2 stage [odds ratio (OR) = 3.75, P = 0.018], N3 stage (OR = 4.28, P = 0.044), and Kep value (OR = 5.52, P = 0.016) were associated with LVI positivity. The combined-predicted LVI model that incorporated the N stage and Kep yielded an accuracy of 0.735 and a specificity of 0.801. The median RFS was significantly different between the LVI-positive and LVI-negative groups (31.5 vs. 34.0 months, P = 0.010) and between the combined-predicted LVI-positive and LVI-negative groups (31.8 vs. 32.0 months, P = 0.007). The median OS was not significantly different between the LVI-positive and LVI-negative groups (41.5 vs. 44.0 months, P = 0.270) and between the combined-predicted LVI-positive and LVI-negative groups (42.8 vs. 43.5 months, P = 0.970). LVI status (HR = 2.40), N2 (HR = 3.35), and the combined-predicted LVI model (HR = 1.61) were independently associated with disease recurrence. CONCLUSION: The quantitative parameter of Kep could predict LVI. LVI status, N stage, and the combined-predicted LVI model were predictors of a poor RFS but not OS.