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A sensitive and efficient imaging technique is required to assess the subtle abnormalities occurring in the normal-appearing white matter (NAWM) and normal-appearing grey matter (NAGM) in patients with relapsing-remitting multiple sclerosis (RRMS). In this study, a fast 3D macromolecular proton fraction (MPF) quantification based on spin-lock (fast MPF-SL) sequence was proposed for brain MPF mapping. Thirty-four participants, including 17 healthy controls and 17 RRMS patients were prospectively recruited. We conducted group comparison and correlation between conventional MPF-SL, fast MPF-SL, and DWI, and compared differences in quantified parameters within MS lesions and the regional NAWM, NAGM, and normal-appearing deep grey matter (NADGN). MPF of MS lesions was significantly reduced (7.17% ± 1.15%, P < 0.01) compared to all corresponding normal-appearing regions. MS patients also showed significantly reduced mean MPF values compared with controls in NAGM (4.87% ± 0.38% vs 5.21% ± 0.32%, P = 0.01), NAWM (9.49% ± 0.69% vs 10.32% ± 0.59%, P < 0.01) and NADGM (thalamus 5.59% ± 0.67% vs 6.00% ± 0.41%, P = 0.04; caudate 5.10% ± 0.55% vs 5.53% ± 0.58%, P = 0.03). MPF and ADC showed abnormalities in otherwise normal appearing close to lesion areas (P < 0.01). In conclusion, time-efficient MPF mapping of the whole brain can be acquired efficiently (< 3 min) using fast MPF-SL. It offers a promising alternative way to detect white matter abnormalities in MS.
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Encéfalo , Esclerosis Múltiple Recurrente-Remitente , Sustancia Blanca , Humanos , Femenino , Masculino , Adulto , Esclerosis Múltiple Recurrente-Remitente/diagnóstico por imagen , Esclerosis Múltiple Recurrente-Remitente/patología , Sustancia Blanca/diagnóstico por imagen , Sustancia Blanca/patología , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Persona de Mediana Edad , Protones , Sustancia Gris/diagnóstico por imagen , Sustancia Gris/patología , Imagenología Tridimensional/métodos , Imagen por Resonancia Magnética/métodos , Estudios de Casos y Controles , Mapeo Encefálico/métodos , Estudios ProspectivosRESUMEN
OBJECTIVES: To investigate the potential of T1rho, a new quantitative imaging sequence for cancer, for pre and early intra-treatment prediction of treatment response in nasopharyngeal carcinoma (NPC) and compare the results with those of diffusion-weighted imaging (DWI). MATERIALS AND METHODS: T1rho and DWI imaging of primary NPCs were performed pre- and early intra-treatment in 41 prospectively recruited patients. The mean preT1rho, preADC, intraT1rho, intraADC, and % changes in T1rho (ΔT1rho%) and ADC (ΔADC%) were compared between residual and non-residual groups based on biopsy in all patients after chemoradiotherapy (CRT) with (n = 29) or without (n = 12) induction chemotherapy (IC), and between responders and non-responders to IC in the subgroup who received IC, using Mann-Whitney U-test. A p-value of < 0.05 indicated statistical significance. RESULTS: Significant early intra-treatment changes in mean T1rho (p = 0.049) and mean ADC (p < 0.01) were detected (using paired t-test), most showing a decrease in T1rho (63.4%) and an increase in ADC (95.1%). Responders to IC (n = 17), compared to non-responders (n = 12), showed higher preT1rho (64.0 ms vs 66.5 ms) and a greater decrease in ΔT1rho% (- 7.5% vs 1.3%) (p < 0.05). The non-residual group after CRT (n = 35), compared to the residual group (n = 6), showed higher intraADC (0.96 vs 1.09 × 10-3 mm2/s) and greater increase in ΔADC% (11.7% vs 27.0%) (p = 0.02). CONCLUSION: Early intra-treatment changes are detectable on T1rho and show potential to predict tumour shrinkage after IC. T1rho may be complementary to DWI, which, unlike T1rho, did not predict response to IC but did predict non-residual disease after CRT. CLINICAL RELEVANCE STATEMENT: T1rho has the potential to complement DWI in the prediction of treatment response. Unlike DWI, it predicted shrinkage of the primary NPC after IC but not residual disease after CRT. KEY POINTS: Changes in T1rho were detected early during cancer treatment for NPC. Pre-treatment and early intra-treatment change in T1rho predicted response to IC, but not residual disease after CRT. T1rho can be used to complement DWI with DWI predicting residual disease after CRT.
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OBJECTIVES: Parotid gland tumors (PGTs) often occur as incidental findings on magnetic resonance images (MRI) that may be overlooked. This study aimed to construct and validate a deep learning model to automatically identify parotid glands (PGs) with a PGT from normal PGs, and in those with a PGT to segment the tumor. MATERIALS AND METHODS: The nnUNet combined with a PG-specific post-processing procedure was used to develop the deep learning model trained on T1-weighed images (T1WI) in 311 patients (180 PGs with tumors and 442 normal PGs) and fat-suppressed (FS)-T2WI in 257 patients (125 PGs with tumors and 389 normal PGs), for detecting and segmenting PGTs with five-fold cross-validation. Additional validation set separated by time, comprising T1WI in 34 and FS-T2WI in 41 patients, was used to validate the model performance. RESULTS AND CONCLUSION: To identify PGs with tumors from normal PGs, using combined T1WI and FS-T2WI, the deep learning model achieved an accuracy, sensitivity and specificity of 98.2% (497/506), 100% (119/119) and 97.7% (378/387), respectively, in the cross-validation set and 98.5% (67/68), 100% (20/20) and 97.9% (47/48), respectively, in the validation set. For patients with PGTs, automatic segmentation of PGTs on T1WI and FS-T2WI achieved mean dice coefficients of 86.1% and 84.2%, respectively, in the cross-validation set, and of 85.9% and 81.0%, respectively, in the validation set. The proposed deep learning model may assist the detection and segmentation of PGTs and, by acting as a second pair of eyes, ensure that incidentally detected PGTs on MRI are not missed.
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Aprendizaje Profundo , Imagen por Resonancia Magnética , Neoplasias de la Parótida , Humanos , Neoplasias de la Parótida/diagnóstico por imagen , Neoplasias de la Parótida/patología , Imagen por Resonancia Magnética/métodos , Femenino , Masculino , Persona de Mediana Edad , Adulto , Anciano , Glándula Parótida/diagnóstico por imagen , Glándula Parótida/patología , Adulto Joven , Adolescente , Procesamiento de Imagen Asistido por Computador/métodos , Anciano de 80 o más AñosRESUMEN
BACKGROUND: Although contrast-enhanced magnetic resonance imaging (MRI) detects early-stage nasopharyngeal carcinoma (NPC) not detected by endoscopic-guided biopsy (EGB), a short contrast-free screening MRI would be desirable for NPC screening programs. This study evaluated a screening MRI in a plasma Epstein-Barr virus (EBV)-DNA NPC screening program. METHODS: EBV-DNA-screen-positive patients underwent endoscopy, and endoscopy-positive patients underwent EGB. EGB was negative if the biopsy was negative or was not performed. Patients also underwent a screening MRI. Diagnostic performance was based on histologic confirmation of NPC in the initial study or during a follow-up period of at least 2 years. RESULTS: The study prospectively recruited 354 patients for MRI and endoscopy; 40/354 (11.3%) endoscopy-positive patients underwent EGB. Eighteen had NPC (5.1%), and 336 without NPC (94.9%) were followed up for a median of 44.8 months. MRI detected additional NPCs in 3/18 (16.7%) endoscopy-negative and 2/18 (11.1%) EGB-negative patients (stage I/II, n = 4; stage III, n = 1). None of the 24 EGB-negative patients who were MRI-negative had NPC. MRI missed NPC in 2/18 (11.1%), one of which was also endoscopy-negative. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of MRI, endoscopy, and EGB were 88.9%, 91.1%, 34.8%, 99.4%, and 91.0%; 77.8%, 92.3%, 35.0%, 98.7%, and 91.5%; and 66.7%, 92.3%, 31.6%, 98.1%, and 91.0%, respectively. CONCLUSION: A quick contrast-free screening MRI complements endoscopy in NPC screening programs. In EBV-screen-positive patients, MRI enables early detection of NPC that is endoscopically occult or negative on EGB and increases confidence that NPC has not been missed.
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Detección Precoz del Cáncer , Infecciones por Virus de Epstein-Barr , Herpesvirus Humano 4 , Imagen por Resonancia Magnética , Carcinoma Nasofaríngeo , Neoplasias Nasofaríngeas , Humanos , Neoplasias Nasofaríngeas/virología , Neoplasias Nasofaríngeas/diagnóstico por imagen , Neoplasias Nasofaríngeas/diagnóstico , Neoplasias Nasofaríngeas/patología , Masculino , Persona de Mediana Edad , Femenino , Imagen por Resonancia Magnética/métodos , Detección Precoz del Cáncer/métodos , Adulto , Herpesvirus Humano 4/aislamiento & purificación , Carcinoma Nasofaríngeo/virología , Carcinoma Nasofaríngeo/diagnóstico por imagen , Carcinoma Nasofaríngeo/diagnóstico , Carcinoma Nasofaríngeo/patología , Estudios Prospectivos , Anciano , Infecciones por Virus de Epstein-Barr/complicaciones , Infecciones por Virus de Epstein-Barr/diagnóstico , ADN Viral/sangre , Carcinoma/diagnóstico por imagen , Carcinoma/virología , Carcinoma/diagnóstico , Carcinoma/patología , Sensibilidad y Especificidad , Endoscopía/métodos , Estadificación de Neoplasias , Tamizaje Masivo/métodos , Medios de Contraste/administración & dosificaciónRESUMEN
BACKGROUND: Preoperative, noninvasive prediction of meningioma grade is important for therapeutic planning and decision making. In this study, we propose a dual-level augmentation strategy incorporating image-level augmentation (IA) and feature-level augmentation (FA) to tackle class imbalance and improve the predictive performance of radiomics for meningioma grading on Magnetic Resonance Imaging (MRI). METHODS: This study recruited 160 consecutive patients with pathologically proven meningioma (129 low-grade (WHO grade I) tumors; 31 high-grade (WHO grade II and III) tumors) with preoperative multisequence MRI imaging. A dual-level augmentation strategy combining IA and FA was applied and evaluated in 100 repetitions in 3-, 5-, and 10-fold cross-validation. RESULTS: The best area under the receiver operating characteristics curve of our method in 100 repetitions was ≥0.78 in all cross-validations. The corresponding cross-validation sensitivities (cross-validation specificity) were 0.72 (0.69), 0.76 (0.71), and 0.63 (0.82) in 3-, 5-, and 10-fold cross-validation, respectively. The proposed method achieved significantly better performance and distribution of results, outperforming single-level augmentation (IA or FA) or no augmentation in each cross-validation. CONCLUSIONS: The dual-level augmentation strategy using IA and FA significantly improves the performance of the radiomics model for meningioma grading on MRI, allowing better radiomics-based preoperative stratification and individualized treatment.
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Radiomics analysis can potentially characterize salivary gland tumors (SGTs) on magnetic resonance imaging (MRI). The procedures for radiomics analysis were various, and no consistent performances were reported. This review evaluated the methodologies and performances of studies using radiomics analysis to characterize SGTs on MRI. We systematically reviewed studies published until July 2023, which employed radiomics analysis to characterize SGTs on MRI. In total, 14 of 98 studies were eligible. Each study examined 23-334 benign and 8-56 malignant SGTs. Least absolute shrinkage and selection operator (LASSO) was the most common feature selection method (in eight studies). Eleven studies confirmed the stability of selected features using cross-validation or bootstrap. Nine classifiers were used to build models that achieved area under the curves (AUCs) of 0.74 to 1.00 for characterizing benign and malignant SGTs and 0.80 to 0.96 for characterizing pleomorphic adenomas and Warthin's tumors. Performances were validated using cross-validation, internal, and external datasets in four, six, and two studies, respectively. No single feature consistently appeared in the final models across the studies. No standardized procedure was used for radiomics analysis in characterizing SGTs on MRIs, and various models were proposed. The need for a standard procedure for radiomics analysis is emphasized.
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PURPOSE: T1rho imaging is a promising MRI technique for imaging of brain disease. This study aimed to assess the repeatability of quantitative T1rho imaging in the normal brain grey and white matter. METHODS: The study prospectively recruited 30 healthy volunteers without a history of neurological diseases or brain injury, and T1rho was performed and quantified from three imaging sessions. Repeat measures analysis of variance (ANOVA) and within-subject coefficients of variation (wCoV) was used to detect differences in T1rho values between the three scans. RESULTS: The results showed low wCoVs of less than 4.3% (range 0.92-4.27%) across all the brain structures. No significant differences were observed in T1rho measurement between the three scans (p > 0.05). The amygdala and hippocampus showed the highest T1rho values of 91.79 ± 2.55 msec and 91.07 ± 2.11 msec respectively, and the palladium and putamen had the lowest values of 67.60 ± 1.84 msec and 71.83 ± 1.85 msec respectively. CONCLUSION: T1rho shows high test-retest repeatability for whole brain imaging in serial imaging sessions, indicating it to be a reliable sequence for quantitative brain imaging.
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Encéfalo , Imagen por Resonancia Magnética , Humanos , Imagen por Resonancia Magnética/métodos , Encéfalo/diagnóstico por imagen , Reproducibilidad de los ResultadosRESUMEN
The lack of a consistent MRI radiomic signature, partly due to the multitude of initial feature analyses, limits the widespread clinical application of radiomics for the discrimination of salivary gland tumors (SGTs). This study aimed to identify the optimal radiomics feature category and MRI sequence for characterizing SGTs, which could serve as a step towards obtaining a consensus on a radiomics signature. Preliminary radiomics models were built to discriminate malignant SGTs (n = 34) from benign SGTs (n = 57) on T1-weighted (T1WI), fat-suppressed (FS)-T2WI and contrast-enhanced (CE)-T1WI images using six feature categories. The discrimination performances of these preliminary models were evaluated using 5-fold-cross-validation with 100 repetitions and the area under the receiver operating characteristic curve (AUC). The differences between models' performances were identified using one-way ANOVA. Results show that the best feature categories were logarithm for T1WI and CE-T1WI and exponential for FS-T2WI, with AUCs of 0.828, 0.754 and 0.819, respectively. These AUCs were higher than the AUCs obtained using all feature categories combined, which were 0.750, 0.707 and 0.774, respectively (p < 0.001). The highest AUC (0.846) was obtained using a combination of T1WI + logarithm and FS-T2WI + exponential features, which reduced the initial features by 94.0% (from 1015 × 3 to 91 × 2). CE-T1WI did not improve performance. Using one feature category rather than all feature categories combined reduced the number of initial features without compromising radiomic performance.
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PURPOSE: Nodal size is an important imaging criterion for differentiating benign from malignant nodes in the head and neck cancer staging. This study evaluated the size of normal nodes in less well-documented nodal groups in the upper head and neck on magnetic resonance imaging (MRI). METHODS: Analysis was performed on 289 upper head and neck MRIs of patients without head and neck cancer. The short axial diameters (SAD) of the largest node in the parotid, submandibular, occipital, facial, retroauricular and Level IIb of the upper internal jugular nodal groups were documented and compared to the commonly used threshold of ≥ 10 mm for diagnosis of a malignant node. RESULTS: Normal nodes in the parotid, occipital, retroauricular and Level IIb groups were small with a mean SAD ranging from 3.8 to 4.4 mm, nodes in the submandibular group were larger with a mean SAD of 5.5 mm and facial nodes were not identified. A size ≥ 10 mm was found in 0.8% of submandibular nodes. Less than 10% of the other nodal group had a SAD of ≥ 6 mm and none of them had a SAD ≥ 8 mm. CONCLUSION: To identify malignant neck nodes in these groups there is scope to reduce the size threshold of ≥ 10 mm to improve sensitivity without substantial loss of specificity.
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Neoplasias de Cabeza y Cuello , Humanos , Neoplasias de Cabeza y Cuello/diagnóstico por imagen , Imagen por Resonancia MagnéticaRESUMEN
KEY POINTS: ⢠Conventional and advanced MR techniques may aid in the diagnosis of motor neuron disease.⢠Iron-sensitive MR imaging of the primary motor cortex may reveal changes to help differentiate hereditary spastic paraplegia (HSP) from UMM predominant amyotrophic lateral sclerosis (UMN-ALS) and primary lateral sclerosis (PLS).⢠Additional research in this area is necessary.
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Esclerosis Amiotrófica Lateral , Corteza Motora , Enfermedad de la Neurona Motora , Paraplejía Espástica Hereditaria , Humanos , Paraplejía Espástica Hereditaria/diagnóstico por imagen , Corteza Motora/diagnóstico por imagen , Hierro , Enfermedad de la Neurona Motora/diagnóstico por imagen , Esclerosis Amiotrófica Lateral/diagnóstico , Imagen por Resonancia Magnética/métodosRESUMEN
STUDY DESIGN: Cross-sectional observational study. OBJECTIVE: The aim was to compare the prevalence and severity of radiographic lumbar spine degeneration between elderly Hong Kong Chinese and elderly Italian Caucasian women. SUMMARY OF BACKGROUND DATA: Rates of symptomatic low back pain and osteoporotic vertebral fracture have been shown to be lower in Asian and Chinese populations compared with Caucasians, but ethnic differences in spinal degeneration are less established. METHODS: Lumbar spine lateral radiographs of 566 age-matched (mean: 73.6 yr; range: 65-87 yr) female subjects from two population-based epidemiological studies from Hong Kong (n=283) and Rome, Italy (n=283) were reviewed. Grading of degeneration categories: disk height loss (none, <30%, 30%-60%, >60%), osteophyte formation (not present, minimal, small, large), endplate sclerosis (none, mild, moderate, severe), and antero/retrolisthesis (none, <25%, 25%-50%, >50%) was performed for vertebral levels from L1/2 to L5/S1 (five levels). Each category was assigned a score (0, 1, 2, 3) at individual vertebral level according to severity. The total degeneration score was obtained by adding scores for all categories across the vertebral levels. RESULTS: Italian subjects [total score (mean±SD): 7.0±5.5] had a higher severity of overall degenerative changes compared with Hong Kong subjects (5.7±4.4), P <0.01. Italian subjects had higher scores for individual findings of disk height loss (Italian, 3.6±2.8 vs. Hong Kong 2.5±2.1, P <0.01); antero/retrolisthesis (Italian 0.3±0.7 vs. Hong Kong 0.2±0.4, P =0.01); and endplate sclerosis (Italian 1.0±1.2 vs. Hong Kong 0.6±1.0, P <0.01). At each individual level from L1/2 to L5/S1, total degeneration scores were higher in Italian than Hong Kong subjects ( P <0.01-0.04). CONCLUSION: Degenerative changes in the lumbar spine are less prevalent and less severe in elderly Hong Kong Chinese women than in age-matched Italian Caucasian women. The observed differences may reflect a foundational background influence of genetic predisposition that requires further studies.
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Fracturas Osteoporóticas , Enfermedades de la Columna Vertebral , Femenino , Humanos , Anciano , Prevalencia , Estudios Transversales , Hong Kong/epidemiología , Esclerosis , Vértebras Lumbares/diagnóstico por imagen , Fracturas Osteoporóticas/epidemiologíaRESUMEN
PURPOSES: To systematically review and perform meta-analysis to evaluate the prognostic value of cervical nodal necrosis (CNN) on the staging computed tomography/magnetic resonance imaging (MRI) of nasopharyngeal carcinoma (NPC) in era of intensity-modulated radiotherapy. METHODS: Literature search through PubMed, EMBASE, and Cochrane Library was conducted. The hazard ratios (HRs) with 95% confidence intervals (CIs) of CNN for distant metastasis-free survival (DMFS), disease free survival (DFS) and overall survival (OS) were extracted from the eligible studies and meta-analysis was performed to evaluate the pooled HRs with 95%CI. RESULTS: Nine studies, which investigated the prognostic values of 6 CNN patterns on MRI were included. Six/9 studies were eligible for meta-analysis, which investigated the CNN presence/absence in any nodal group among 4359 patients. The pooled unadjusted HRs showed that the CNN presence predicted poor DMFS (HR =1.89, 95%CI =1.72-2.08), DFS (HR =1.57, 95%CI =1.08-2.26), and OS (HR =1.87, 95%CI =1.69-2.06). The pooled adjusted HRs also showed the consistent results for DMFS (HR =1.34, 95%CI =1.17-1.54), DFS (HR =1.30, 95%CI =1.08-1.56), and OS (HR =1.61, 95%CI =1.27-2.04). Results shown in the other studies analysing different CNN patterns indicated the high grade of CNN predicted poor outcome, but meta-analysis was unable to perform because of the heterogeneity of the analysed CNN patterns. CONCLUSION: The CNN observed on the staging MRI is a negative factor for NPC outcome, suggesting that the inclusion of CNN is important in the future survival analysis. However, whether and how should CNN be included in the staging system warrant further evaluation.
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Neoplasias Nasofaríngeas , Radioterapia de Intensidad Modulada , Humanos , Imagen por Resonancia Magnética , Carcinoma Nasofaríngeo/diagnóstico por imagen , Carcinoma Nasofaríngeo/radioterapia , Neoplasias Nasofaríngeas/diagnóstico por imagen , Neoplasias Nasofaríngeas/radioterapia , Necrosis/patología , Estadificación de Neoplasias , Pronóstico , Estudios RetrospectivosRESUMEN
Blunt cerebrovascular injury (BCVI) is an often underrecognized injury occurring in the carotid or vertebral arteries, associated with a risk of ischemic stroke and potential for poor neurological outcome or death. Computed tomographic angiography (CTA) is the most common modality for initial screening and diagnosis. Vessel wall intimal injuries, intraluminal thrombus, dissection, intramural hematoma, pseudoaneurysm, vessel transection, and arteriovenous fistula, are potential findings to be considered in approach to imaging. Identification of high-risk trauma patients based on clinical and radiological risk factors can determine patients at risk of BCVI for targeted screening.
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Traumatismos Cerebrovasculares , Heridas no Penetrantes , Angiografía , Traumatismos Cerebrovasculares/complicaciones , Traumatismos Cerebrovasculares/diagnóstico por imagen , Humanos , Tomografía Computarizada por Rayos X/métodos , Arteria Vertebral/diagnóstico por imagen , Arteria Vertebral/lesiones , Heridas no Penetrantes/complicaciones , Heridas no Penetrantes/diagnóstico por imagenRESUMEN
Triaging and prioritising patients for RT-PCR test had been essential in the management of COVID-19 in resource-scarce countries. In this study, we applied machine learning (ML) to the task of detection of SARS-CoV-2 infection using basic laboratory markers. We performed the statistical analysis and trained an ML model on a retrospective cohort of 5148 patients from 24 hospitals in Hong Kong to classify COVID-19 and other aetiology of pneumonia. We validated the model on three temporal validation sets from different waves of infection in Hong Kong. For predicting SARS-CoV-2 infection, the ML model achieved high AUCs and specificity but low sensitivity in all three validation sets (AUC: 89.9-95.8%; Sensitivity: 55.5-77.8%; Specificity: 91.5-98.3%). When used in adjunction with radiologist interpretations of chest radiographs, the sensitivity was over 90% while keeping moderate specificity. Our study showed that machine learning model based on readily available laboratory markers could achieve high accuracy in predicting SARS-CoV-2 infection.
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Prueba de COVID-19 , COVID-19 , Aprendizaje Automático , Modelos Biológicos , SARS-CoV-2/metabolismo , Adolescente , Adulto , Biomarcadores/sangre , COVID-19/sangre , COVID-19/diagnóstico por imagen , Femenino , Humanos , Masculino , Persona de Mediana Edad , Valor Predictivo de las Pruebas , Estudios Retrospectivos , Tórax/diagnóstico por imagenRESUMEN
Data privacy mechanisms are essential for rapidly scaling medical training databases to capture the heterogeneity of patient data distributions toward robust and generalizable machine learning systems. In the current COVID-19 pandemic, a major focus of artificial intelligence (AI) is interpreting chest CT, which can be readily used in the assessment and management of the disease. This paper demonstrates the feasibility of a federated learning method for detecting COVID-19 related CT abnormalities with external validation on patients from a multinational study. We recruited 132 patients from seven multinational different centers, with three internal hospitals from Hong Kong for training and testing, and four external, independent datasets from Mainland China and Germany, for validating model generalizability. We also conducted case studies on longitudinal scans for automated estimation of lesion burden for hospitalized COVID-19 patients. We explore the federated learning algorithms to develop a privacy-preserving AI model for COVID-19 medical image diagnosis with good generalization capability on unseen multinational datasets. Federated learning could provide an effective mechanism during pandemics to rapidly develop clinically useful AI across institutions and countries overcoming the burden of central aggregation of large amounts of sensitive data.
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PURPOSE: T1rho imaging is a new quantitative MRI sequence for head and neck cancer and the repeatability for this region is unknown. This study aimed to evaluate the repeatability of quantitative T1rho imaging in the head and neck. MATERIALS AND METHODS: T1rho imaging of the head and neck was prospectively performed in 15 healthy participants on three occasions. Scan 1 and 2 were performed with a time interval of 30â¯minutes (intra-session) and scan 3 was performed 14 days later (inter-session). T1rho values for normal tissues (parotid glands, palatine tonsils, pterygoid muscles, and tongue) were obtained on each scan. Intra-class coefficients (ICCs), within-subject coefficient of variances (wCoVs), and repeatability coefficient (RCs) of the intra-session scan (scan 1 vs 2) and inter-session scan (scan 1 vs 3) for the normal tissues were calculated. RESULTS: The ICCs of T1rho values for normal tissues were almost perfect (0.83-0.97) for intra-session scans and were substantial (0.71-0.80) for inter-session scans. The wCoVs showed a small range (2.46%-3.30%) for intra-session scans, and slightly greater range (3.27%-6.51%) for inter-session scan. The greatest and lowest wCoVs of T1rho were found in the parotid gland and muscles, respectively. The T1rho RCs varied for all tissues between intra- and inter- sessions, and the greatest RC of 10.07â¯msec was observed for parotid gland on inter-session scan. CONCLUSION: T1rho imaging is a repeatable quantitative MRI sequence in the head and neck but variances of T1rho values among tissues should be take into account during analysis.
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Cabeza , Imagen por Resonancia Magnética , Cabeza/diagnóstico por imagen , Humanos , Cuello/diagnóstico por imagen , Glándula Parótida/diagnóstico por imagen , Reproducibilidad de los ResultadosRESUMEN
PURPOSE: Anatomical imaging criteria for the diagnosis of malignant head and neck nodes may not always be reliable. This study aimed to evaluate the diagnostic value of conventional diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) DWI in discriminating benign and malignant metastatic retropharyngeal nodes (RPNs). METHODS: IVIM DWI using 14 b-values was performed on RPNs of 30 patients with newly diagnosed metastatic nasopharyngeal carcinoma (NPC) and 30 patients with elevated plasma Epstein-Barr virus (EBV)-DNA without NPC who were part of an EBV-based NPC screening program. Histogram measurements of the two groups were compared for pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion volume fraction (f) and apparent diffusion coefficient (ADC) using the Mann-Whitney U test. Area under the curves (AUCs) of significant measurements were calculated from receiver-operating characteristics analysis and compared using the DeLong test. RESULTS: Compared with metastatic RPNs, benign RPNs had lower ADCmean (0.73 vs 0.82 × 10-3 mm2/s) and Dmean (0.60 vs 0.71 × 10-3 mm2/s) and a higher D*mean (35.21 vs 28.66 × 10-3 mm2/s) (all p < 0.05). There was no difference in the f measurements between the two groups (p = 0.204 to 0.301). Dmean achieved the highest AUC of 0.800, but this was not statistically better than the AUCs of the other parameters (p = 0.148 to 0.991). CONCLUSION: Benign RPNs in patients with EBV-DNA showed greater restriction of diffusion compared with malignant metastatic RPNs from NPC. IVIM did not show a significant advantage over conventional DWI in discriminating benign and malignant nodes.
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Imagen de Difusión por Resonancia Magnética/métodos , Metástasis Linfática/diagnóstico por imagen , Carcinoma Nasofaríngeo/diagnóstico por imagen , Adulto , Anciano , Teorema de Bayes , Medios de Contraste , Diagnóstico Diferencial , Femenino , Humanos , Interpretación de Imagen Asistida por Computador , Masculino , Meglumina , Persona de Mediana Edad , Carcinoma Nasofaríngeo/patología , Carcinoma Nasofaríngeo/virología , Compuestos Organometálicos , Estudios Retrospectivos , Sensibilidad y EspecificidadRESUMEN
PURPOSE: To evaluate whether pre-treatment intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) can predict treatment outcome after 2 years in patients with nasopharyngeal carcinoma (NPC). METHOD: One hundred and sixty-one patients with newly diagnosed NPC underwent pre-treatment IVIM-DWI. Univariate Cox regression analysis was performed to evaluate the correlation of the mean values of the pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction and apparent diffusion coefficient with local relapse-free survival (LRFS), regional relapse-free survival (RRFS), distant metastases-free survival (DMFS) and disease-free survival (DFS). Significant diffusion parameters, together with staging, age, gender and treatment as confounding factors, were added into a multivariate model. The area under the curves (AUCs) of significant parameters for disease relapse were compared using the Delong test. RESULTS: Disease relapse occurred in 30 % of the patients at a median follow-up time of 52.1 months. The multivariate analysis showed that high D and T-staging were correlated with poor LRFS (pâ¯=â¯0.042 and 0.020, respectively) and poor DFS (pâ¯=â¯0.023 and 0.001, respectively); low D* and high T-staging with poor RRFS (pâ¯=â¯0.020 and 0.033, respectively); and high N-staging with poor DMFS (pâ¯=â¯0.006). D with the optimal threshold of ≥0.68â¯×â¯10-3â¯mm2/s and T-staging showed similar AUCs (AUCâ¯=â¯0.614 and 0.651, respectively; pâ¯=â¯0.493) for predicting disease relapse. CONCLUSION: High D and low D* were predictors of poor locoregional outcome but none of the diffusion parameters predicted DMFS in NPC.