Magnetic Resonance Imaging Features of Normal Thyroid Parenchyma and Incidental Diffuse Thyroid Disease: A Single-Center Study.
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ABSTRACT:
SUBMITTER: Kang T
PROVIDER: S-EPMC6291476 | biostudies-other | 2018
REPOSITORIES: biostudies-other
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Project description:Meningiomas are the most common primary intracranial tumors and are associated with inactivation of the tumor suppressor NF2/Merlin, but one-third of meningiomas retain Merlin expression and typically have favorable clinical outcomes. Biochemical mechanisms underlying Merlin-intact meningioma growth are incompletely understood, and non-invasive biomarkers that predict meningioma outcomes and could be used to guide treatment de-escalation or imaging surveillance of Merlin-intact meningiomas are lacking. Here we integrate single-cell RNA sequencing, proximity-labeling proteomic mass spectrometry, mechanistic and functional approaches, and magnetic resonance imaging (MRI) across meningioma cells, xenografts, and human patients to define biochemical mechanisms and an imaging biomarker that distinguish Merlin-intact meningiomas with favorable clinical outcomes from meningiomas with unfavorable clinical outcomes. We find Merlin drives meningioma Wnt signaling and tumor growth through a feed-forward mechanism that requires Merlin dephosphorylation on serine 13 (S13) to attenuate inhibitory interactions with β-catenin and activate the Wnt pathway. Meningioma MRI analyses of xenografts and human patients show Merlin-intact meningiomas with S13 phosphorylation and favorable clinical outcomes are associated with high apparent diffusion coefficient (ADC) on diffusionweighted imaging. In sum, our results shed light on Merlin posttranslational modifications that regulate meningioma Wnt signaling and tumor growth in tumors without NF2/Merlin inactivation. To translate these findings to clinical practice, we establish a non-invasive imaging biomarker that could be used to guide treatment de-escalation or imaging surveillance for patients with favorable meningiomas.
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Project description:Background: Wrist pain is often nonspecific. Magnetic resonance imaging (MRI) is regularly obtained to evaluate wrist pain. Variations and pathophysiology identified on MRI may not account for patient's clinical symptoms. This study aims to quantify the prevalence of flexor carpi radialis (FCR) tendinopathy on MRI and the coexistence of trapeziometacarpal (TMC) or scaphotrapeziotrapezoid (STT) osteoarthritis. Methods: Using an institutional research database, we identified 3631 adult patients who obtained an MRI of the wrist during a 15-year period. Text search in the radiology reports identified 302 patients with possible FCR signal abnormalities. After reviewing the medical records, 98 patients were identified with FCR tendinopathy. Furthermore, medical records were used to identify pain located on the volar radial part of the wrist. In the absence of a documented examination consistent with FCR tendinopathy, we considered any signal change in the FCR incidental. Results: We identified 55 patients (55%) with incidental FCR tendinopathy. In a bivariate analysis, we found FCR signal changes on the MRI were associated with older age, white race, clinically suspected FCR tendinopathy, volar-radial sided wrist pain, and TMC and STT arthritis. Using multivariable logistic regression to account for confounding, older age and volar-radial sided wrist pain were independently associated with FCR signal changes on MRI. Conclusions: Signal changes in the FCR are infrequent and often incidental (asymptomatic) or associated with peritrapezial osteoarthritis.
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Project description:ImportanceIncidental findings (IFs) are unexpected abnormalities discovered during imaging and can range from normal anatomic variants to findings requiring urgent medical intervention. In the case of brain magnetic resonance imaging (MRI), reliable data about the prevalence and significance of IFs in the general population are limited, making it difficult to anticipate, communicate, and manage these findings.ObjectivesTo determine the overall prevalence of IFs in brain MRI in the nonclinical pediatric population as well as the rates of specific findings and findings for which clinical referral is recommended.Design, setting, and participantsThis cohort study was based on the April 2019 release of baseline data from 11 810 children aged 9 to 10 years who were enrolled and completed baseline neuroimaging in the Adolescent Brain Cognitive Development (ABCD) study, the largest US population-based longitudinal observational study of brain development and child health, between September 1, 2016, and November 15, 2018. Participants were enrolled at 21 sites across the US designed to mirror the demographic characteristics of the US population. Baseline structural MRIs were centrally reviewed for IFs by board-certified neuroradiologists and findings were described and categorized (category 1, no abnormal findings; 2, no referral recommended; 3; consider referral; and 4, consider immediate referral). Children were enrolled through a broad school-based recruitment process in which all children of eligible age at selected schools were invited to participate. Exclusion criteria were severe sensory, intellectual, medical, or neurologic disorders that would preclude or interfere with study participation. During the enrollment process, demographic data were monitored to ensure that the study met targets for sex, socioeconomic, ethnic, and racial diversity. Data were analyzed from March 15, 2018, to November 20, 2020.Main outcomes and measuresPercentage of children with IFs in each category and prevalence of specific IFs.ResultsA total of 11 679 children (52.1% boys, mean [SD] age, 9.9 [0.62] years) had interpretable baseline structural MRI results. Of these, 2464 participants (21.1%) had IFs, including 2013 children (17.2%) assigned to category 2, 431 (3.7%) assigned to category 3, and 20 (0.2%) assigned to category 4. Overall rates of IFs did not differ significantly between singleton and twin gestations or between monozygotic and dizygotic twins, but heritability analysis showed heritability for the presence or absence of IFs (h2 = 0.260; 95% CI, 0.135-0.387).Conclusions and relevanceIncidental findings in brain MRI and findings with potential clinical significance are both common in the general pediatric population. By assessing IFs and concurrent developmental and health measures and following these findings over the longitudinal study course, the ABCD study has the potential to determine the significance of many common IFs.
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Project description:Background and purposeRadiomics offers great potential in improving diagnosis and treatment for patients with glioblastoma multiforme. However, in order to implement radiomics in clinical routine, the features used for prognostic modelling need to be stable. This comprises significant challenge in multi-center studies. The aim of this study was to evaluate the impact of different image normalization methods on MRI features robustness in multi-center study.MethodsRadiomics stability was checked on magnetic resonance images of eleven patients. The images were acquired in two different hospitals using contrast-enhanced T1 sequences. The images were normalized using one of five investigated approaches including grey-level discretization, histogram matching and z-score. Then, radiomic features were extracted and features stability was evaluated using intra-class correlation coefficients. In the second part of the study, improvement in the prognostic performance of features was tested on 60 patients derived from publicly available dataset.ResultsDepending on the normalization scheme, the percentage of stable features varied from 3.4% to 8%. The histogram matching based on the tumor region showed the highest amount of the stable features (113/1404); while normalization using fixed bin size resulted in 48 stable features. The histogram matching also led to better prognostic value (median c-index increase of 0.065) comparing to non-normalized images.ConclusionsMRI normalization plays an important role in radiomics. Appropriate normalization helps to select robust features, which can be used for prognostic modelling in multicenter studies. In our study, histogram matching based on tumor region improved both stability of radiomic features and their prognostic value.
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Project description:Background: Multiparametric magnetic resonance imaging (mpMRI) has emerged as a non-invasive modality to diagnose and monitor prostate cancer. Quantitative metrics on the regions of abnormality have shown to be useful descriptors to discriminate clinically significant cancers. In this study, we evaluate the reproducibility of quantitative imaging features using repeated mpMRI on the same patients. Methods: We retrospectively obtained the deidentified records of patients, who underwent two mpMRI scans within 2 weeks of the first baseline scan. The patient records were obtained as deidentified data (including imaging), obtained through the TCIA (The Cancer Imaging Archive) repository and analyzed in our institution with an institutional review board-approved Health Insurance Portability and Accountability Act-compliant retrospective study protocol. Indicated biopsied regions were used as a marker for our study radiologists to delineate the regions of interest. We extracted 307 quantitative features in each mpMRI modality [T2-weighted MR sequence image (T2w) and apparent diffusion coefficient (ADC) with b values of 0 and 1,400 mm/s2] across the two sequential scans. Concordance correlation coefficients (CCCs) were computed on the features extracted from sequential scans. Redundant features were removed by computing the coefficient of determination (R 2) among them and replaced with a feature that had the highest dynamic range within intercorrelated groups. Results: We have assessed the reproducibility of quantitative imaging features among sequential scans and found that habitat region characterization improves repeatability in ADC maps. There were 19 T2w features and two ADC features in radiologist drawn regions (native raw image), compared to 18 T2w and 15 ADC features in habitat regions (sphere), which were reproducible (CCC ?0.65) and non-redundant (R 2 ? 0.99). We also found that z-transformation of the images prior to feature extraction reduced the number of reproducible features with no detrimental effect. Conclusion: We have shown that there are quantitative imaging features that are reproducible across sequential prostate mpMRI acquisition at a preset level of filters. We also found that a habitat approach improves feature repeatability in ADC. A validated set of reproducible image features in mpMRI will allow us to develop clinically useful disease risk stratification, enabling the possibility of using imaging as a surrogate to invasive biopsies.
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Project description:PURPOSE:We aimed to evaluate which morphologic features on magnetic resonance imaging (MRI) could predict the progression of pancreatic cystic lesions (PCLs) that are suitable for follow-up. METHODS:A total of 2176 MRI findings of PCLs were retrospectively reviewed between January 2009 and December 2016. The study population was composed of 223 patients. Clinical data and morphologic features of PCLs were recorded. We divided the individuals into two sub-groups according to the final features on MRI. Univariable and multivariable regression analyses were performed to identify independent risk factors for progression of PCLs. RESULTS:A total of 84 PCLs (37.7%) progressed during follow-up, while 139 PCLs (62.3%) were stable. Age (odds ratio [OR], 1.042; P = 0.017), number of lesions (OR, 0.491; P = 0.048), communication to pancreatic duct (PD) (OR, 2.425; P = 0.007) and presence of septa (OR, 6.105; P < 0.001) were significant independent factors for progression of PCLs. Among 84 lesions that progressed, 23 lesions (27.4%) increased to ? 30 mm in diameter or showed worrisome imaging features at the end of follow-up that needed clinical intervention. The initial size and communication to PD were independent factors for progression of PCLs necessitating clinical intervention (P < 0.001 and P = 0.011, respectively). CONCLUSION:Age, number of the lesions, communication to PD and presence of septa were independent risk factors for the progression of PCLs, and the initial size and communication to PD could potentially predict PCLs needing clinical interventions.
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Project description:ObjectiveWe describe the prevalence and range of incidental intracranial abnormalities identified through MRI of the brain in a large group of children screened for a clinical trial.MethodsWe included 953 children between 5 and 14 years of age who were screened with MRI of the brain for the Silent Infarct Transfusion Trial. All had sickle cell anemia or sickle beta-null thalassemia. MRI scans were interpreted by 3 neuroradiologists. MRI scans reported to have any abnormality were reviewed by 2 study neuroradiologists. Incidental findings were classified into 4 categories, that is, no, routine, urgent, or immediate referral recommended. Cerebral infarctions and vascular lesions were not considered incidental and were excluded.ResultsWe identified 63 children (6.6% [95% confidence interval: 5.1%-8.4%]) with 68 incidental intracranial MRI findings. Findings were classified as urgent in 6 cases (0.6%), routine in 25 cases (2.6%), and no referral required in 32 cases (3.4%). No children required immediate referral. Two children with urgent findings underwent surgery in the subsequent 6 months.ConclusionIn this large cohort of children, incidental intracranial findings were identified for 6.6%, with potentially serious or urgent findings for 0.6%.
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