Radiologic texture is the variation in image intensities within an image and is an important part of radiomics. The objective of this article is to discuss some parameters that affect the performance ...of texture metrics and propose recommendations that can guide both the design and evaluation of future radiomics studies.
A variety of texture-extraction techniques are used to assess clinical imaging data. Currently, no consensus exists regarding workflow, including acquisition, extraction, or reporting of variable settings leading to poor reproducibility.
Objective
Thalamic volume is a candidate magnetic resonance imaging (MRI)‐based marker associated with neurodegeneration to hasten development of neuroprotective treatments. Our objective is to ...describe the longitudinal evolution of thalamic atrophy in MS and normal aging, and to estimate sample sizes for study design.
Methods
Six hundred one subjects (2,632 MRI scans) were analyzed. Five hundred twenty subjects with relapse‐onset MS (clinically isolated syndrome, n = 90; relapsing–remitting MS, n = 392; secondary progressive MS, n = 38) underwent annual standardized 3T MRI scans for an average of 4.1 years, including a 1mm3 3‐dimensional T1‐weighted sequence (3DT1; 2,485 MRI scans). Eighty‐one healthy controls (HC) were scanned longitudinally on the same scanner using the same protocol (147 MRI scans). 3DT1s were processed using FreeSurfer's longitudinal pipeline after lesion inpainting. Rates of normalized thalamic volume loss in MS and HC were compared in linear mixed effects models. Simulation‐based sample size calculations were performed incorporating the rate of atrophy in HC.
Results
Thalamic volume declined significantly faster in MS subjects compared to HC, with an estimated decline of −0.71% per year (95% confidence interval CI = −0.77% to −0.64%) in MS subjects and −0.28% per year (95% CI = −0.58% to 0.02%) in HC (p for difference = 0.007). The rate of decline was consistent throughout the MS disease duration and across MS clinical subtypes. Eighty or 100 subjects per arm (α = 0.1 or 0.05, respectively) would be needed to detect the maximal effect size with 80% power in a 24‐month study.
Interpretation
Thalamic atrophy occurs early and consistently throughout MS. Preliminary sample size calculations appear feasible, adding to its appeal as an MRI marker associated with neurodegeneration. Ann Neurol 2018;83:223–234
Since December 2019, the novel coronavirus disease 2019 (COVID-19) that emerged in Wuhan city has spread rapidly around the world. The risk for poor outcome dramatically increases once a patient ...progresses to the severe or critical stage. The present study aims to investigate the risk factors for disease progression in individuals with mild to moderate COVID-19.
We conducted a cohort study that included 1007 individuals with mild to moderate COVID-19 from three hospitals in Wuhan. Clinical characteristics and baseline laboratory findings were collected. Patients were followed up for 28 days for observation of disease progression. The end point was the progression to a more severe disease stage.
During a follow up of 28 days, 720 patients (71.50%) had recovered or were symptomatically stable, 222 patients (22.05%) had progressed to severe disease, 22 patients (2.18%) had progressed to the critically ill stage and 43 patients (4.27%) had died. Multivariate Cox proportional hazards models identified that increased age (hazard ratio (HR) 2.56, 95% CI 1.97–3.33), male sex (HR 1.79, 95% CI 1.41–2.28), presence of hypertension (HR 1.44, 95% CI 1.11–1.88), diabetes (HR 1.82, 95% CI 1.35–2.44), chronic obstructive pulmonary disease (HR 2.01, 95% CI 1.38–2.93) and coronary artery disease (HR 1.83, 95% CI 1.26–2.66) were risk factors for disease progression. History of smoking was protective against disease progression (HR 0.56, 95% CI 0.34–0.91). Elevated procalcitonin (HR 1.72, 95% CI 1.02–2.90), urea nitrogen (HR 1.72, 95% CI 1.21–2.43), α-hydroxybutyrate dehydrogenase (HR 3.02, 95% CI 1.26–7.21) and D-dimer (HR 2.01, 95% CI 1.12–3.58) at baseline were also associated with risk for disease progression.
This study identified a panel of risk factors for disease progression in individuals with mild to moderate COVID-19.
Oral squamous cell carcinoma (OSCC) is prevalent around the world and is associated with poor prognosis. OSCC is typically diagnosed from tissue biopsy sections by pathologists who rely on their ...empirical experience. Deep learning models may improve the accuracy and speed of image classification, thus reducing human error and workload. Here we developed a custom-made deep learning model to assist pathologists in detecting OSCC from histopathology images. We collected and analyzed a total of 2,025 images, among which 1,925 images were included in the training set and 100 images were included in the testing set. Our model was able to automatically evaluate these images and arrive at a diagnosis with a sensitivity of 0.98, specificity of 0.92, positive predictive value of 0.924, negative predictive value of 0.978, and F1 score of 0.951. Using a subset of 100 images, we examined whether our model could improve the diagnostic performance of junior and senior pathologists. We found that junior pathologists were able to delineate OSCC in these images 6.26 min faster when assisted by the model than when working alone. When the clinicians were assisted by the model, their average F1 score improved from 0.9221 to 0.9566 in the case of junior pathologists and from 0.9361 to 0.9463 in the case of senior pathologists. Our findings indicate that deep learning can improve the accuracy and speed of OSCC diagnosis from histopathology images.
When people with stroke recover gait speed, they report improved function and reduced disability. However, the minimal amount of change in gait speed that is clinically meaningful and associated with ...an important difference in function for people poststroke has not been determined.
The purpose of this study was to determine the minimal clinically important difference (MCID) for comfortable gait speed (CGS) associated with an improvement in the modified Rankin Scale (mRS) score for people between 20 to 60 days poststroke.
This was a prospective, longitudinal, cohort study.
The participants in this study were 283 people with first-time stroke prospectively enrolled in the ongoing Locomotor Experience Applied Post Stroke (LEAPS) multi-site randomized clinical trial. Comfortable gait speed was measured and mRS scores were obtained at 20 and 60 days poststroke. Improvement of >or=1 on the mRS was used to detect meaningful change in disability level.
Mean (SD) CGS was 0.18 (0.16) m/s at 20 days and 0.39 (0.22) m/s at 60 days poststroke. Among all participants, 47.3% experienced an improvement in disability level >or=1. The MCID was estimated as an improvement in CGS of 0.16 m/s anchored to the mRS.
Because the mRS is not a gait-specific measure of disability, the estimated MCID for CGS was only 73.9% sensitive and 57.0% specific for detecting improvement in mRS scores.
We estimate that the MCID for gait speed among patients with subacute stroke and severe gait speed impairments is 0.16 m/s. Patients with subacute stroke who increase gait speed >or=0.16 m/s are more likely to experience a meaningful improvement in disability level than those who do not. Clinicians can use this reference value to develop goals and interpret progress in patients with subacute stroke.
The purpose of this study was to assess the accuracy of a panel of texture features extracted from clinical CT in differentiating benign from malignant solid enhancing lipid-poor renal masses.
In a ...retrospective case-control study of 174 patients with predominantly solid nonmacroscopic fat-containing enhancing renal masses, 129 cases of malignant renal cell carcinoma were found, including clear cell, papillary, and chromophobe subtypes. Benign renal masses-oncocytoma and lipid-poor angiomyolipoma-were found in 45 patients. Whole-lesion ROIs were manually segmented and coregistered from the standard-of-care multiphase contrast-enhanced CT (CECT) scans of these patients. Pathologic diagnosis of all tumors was obtained after surgical resection. CECT images of the renal masses were used as inputs to a CECT texture analysis panel comprising 31 texture metrics derived with six texture methods. Stepwise logistic regression analysis was used to select the best predictor among all candidate predictors from each of the texture methods, and their performance was quantified by AUC.
Among the texture predictors aiding renal mass subtyping were entropy, entropy of fast-Fourier transform magnitude, mean, uniformity, information measure of correlation 2, and sum of averages. These metrics had AUC values ranging from good (0.80) to excellent (0.98) across the various subtype comparisons. The overall CECT-based tumor texture model had an AUC of 0.87 (p < 0.05) for differentiating benign from malignant renal masses.
The CT texture statistical model studied was accurate for differentiating benign from malignant solid enhancing lipid-poor renal masses.
Contribution of normal aging to brain atrophy in MS Azevedo, Christina J; Cen, Steven Y; Jaberzadeh, Amir ...
Neurology : neuroimmunology & neuroinflammation,
2019-November, Letnik:
6, Številka:
6
Journal Article
Recenzirano
Odprti dostop
OBJECTIVETo identify the top brain regions affected by MS-specific atrophy (i.e., atrophy in excess of normal aging) and to test whether normal aging and MS-specific atrophy increase or decrease in ...these regions with age.
METHODSSix hundred fifty subjects (2,790 MRI time points) were analyzed520 subjects with relapse-onset MS from a 5-year prospective cohort with annual standardized 1-mm 3D T1-weighted images (3DT1s; 2,483 MRIs) and 130 healthy controls with longitudinal 3DT1s (307 MRIs). Rates of change in all FreeSurfer regions (v5.3) and Structural Image Evaluation Using Normalization of Atrophy (SIENA) were estimated with mixed-effects models. All FreeSurfer regions were ranked by the MS-specific atrophy slope/standard error ratio (βMS × time/SEβMS × time). In the top regions, age was added as an effect modifier to test whether MS-specific atrophy varied by age.
RESULTSThe top-ranked regions were all gray matter structures. For SIENA, normal aging increased from 0.01%/y at age 30 years to −0.31%/y at age 60 years (−0.11% ± 0.032%/decade, p < 0.01), whereas MS-specific atrophy decreased from −0.38%/y at age 30 years to −0.12%/y at age 60 years (0.09% ± 0.035%/decade, p = 0.01). Similarly, in the thalamus, normal aging increased from −0.15%/y at age 30 years to −0.62%/y at age 60 years (−0.16% ± 0.079%/decade, p < 0.05), and MS-specific atrophy decreased from −0.59%/y at age 30 years to −0.05%/y at age 60 years (0.18% ± 0.08%/decade, p < 0.05). In the putamen and caudate, normal aging and MS-specific atrophy did not vary by age.
CONCLUSIONSFor SIENA and thalamic atrophy, the contribution of normal aging increases with age, but does not change in the putamen and caudate. This may have substantial implications to understand the biology of brain atrophy in MS.
Objective To evaluate the association between weekend admission to hospital and 11 hospital acquired conditions recently considered by the Centers for Medicare and Medicaid as “never events” for ...which resulting healthcare costs are not reimbursed.Design National analysis.Setting US Nationwide Inpatient Sample discharge database.Participants 351 million patients discharged from US hospitals, 2002-10.Main outcome measures Univariate rates and multivariable likelihood of hospital acquired conditions among patients admitted on weekdays versus weekends, as well as the impacts of these events on prolonged length of stay and total inpatient charges.Results From 2002 to 2010, 351 170 803 patients were admitted to hospital, with 19% admitted on a weekend. Hospital acquired conditions occurred at an overall frequency of 4.1% (5.7% among weekend admissions versus 3.7% among weekday admissions). Adjusting for patient and hospital cofactors the probability of having one or more hospital acquired conditions was more than 20% higher in weekend admissions compared with weekday admissions (odds ratio 1.25, 95% confidence interval 1.24 to 1.26, P<0.01). Hospital acquired conditions have a negative impact on both hospital charges and length of stay. At least one hospital acquired condition was associated with an 83% (1.83, 1.77 to 1.90, P<0.01) likelihood of increased charges and 38% likelihood of prolonged length of stay (1.38, 1.36 to 1.41, P<0.01).Conclusion Weekend admission to hospital is associated with an increased likelihood of hospital acquired condition, cost, and length of stay. Future protocols and staffing regulations must be tailored to the requirements of this high risk subgroup.
Integrating liquid biopsies of circulating tumor cells (CTCs) and cell-free DNA (cfDNA) with other minimally invasive measures may yield more comprehensive disease profiles. We evaluated the ...feasibility of concurrent cellular and molecular analysis of CTCs and cfDNA combined with radiomic analysis of CT scans from patients with metastatic castration-resistant PC (mCRPC). CTCs from 22 patients were enumerated, stained for PC-relevant markers, and clustered based on morphometric and immunofluorescent features using machine learning. DNA from single CTCs, matched cfDNA, and buffy coats was sequenced using a targeted amplicon cancer hotspot panel. Radiomic analysis was performed on bone metastases identified on CT scans from the same patients. CTCs were detected in 77% of patients and clustered reproducibly. cfDNA sequencing had high sensitivity (98.8%) for germline variants compared to WBC. Shared and unique somatic variants in PC-related genes were detected in cfDNA in 45% of patients (MAF > 0.1%) and in CTCs in 92% of patients (MAF > 10%). Radiomic analysis identified a signature that strongly correlated with CTC count and plasma cfDNA level. Integration of cellular, molecular, and radiomic data in a multi-parametric approach is feasible, yielding complementary profiles that may enable more comprehensive non-invasive disease modeling and prediction.
CSM is a common neurologic disease that results in progressive disability and eventual paralysis without appropriate treatment. Imaging plays a significant role in the evaluation of CSM and has ...evolved with recent technical advances. We sought to systematically explore the relationship between clinical disease severity and DTI in CSM, and to investigate the potential use of DTI in surgical decision-making models.
MR imaging studies and clinical assessments were prospectively collected on 30 patients with CSM. Spearman correlations were used to investigate associations between clinical disease severity and FA at the time of diagnosis. Clinical assessment was performed using mJOA, Nurick, Short Form-36, and NDI scores. Fifteen patients with CSM subsequently underwent decompressive surgery; Spearman correlation and logistic regression were applied to this cohort to study the relationship between baseline DTI measurements and postoperative outcome. Conventional imaging (spinal cord T2 signal intensity and degree of stenosis) was evaluated for comparison with DTI.
At diagnosis, FA demonstrated a strong correlation with baseline mJOA (r = 0.62, P < .01) and Nurick (r = -0.46, P = .01) scores. After surgery, recovery of function demonstrated by improvement in NDI score was associated with higher FA values on preoperative DTI (r = -0.61, P = .04). Severely affected patients with CSM with disproportionately high FA tended to achieve greater mJOA scores after surgery compared with subjects with lower FA (P = .08). T2 signal intensity was associated with functional status at baseline but did not predict postoperative outcome; degree of stenosis lacked any significant correlation with clinical parameters.
DTI may be a useful diagnostic tool for assessing disease severity in CSM. The predictive value of DTI regarding postoperative outcome may improve surgical decision-making and facilitate health care outcomes research.
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