Objectives
To evaluate the performance of a deep learning radiomic nomogram (DLRN) model at predicting tumor relapse in patients with soft tissue sarcomas (STS) who underwent surgical resection.
...Methods
In total, 282 patients who underwent MRI and resection for STS at three independent centers were retrospectively enrolled. In addition, 113 of the 282 patients received additional contrast-enhanced MRI scans. We separated the participants into a development cohort and an external test cohort. The development cohort consisted of patients from one center and the external test cohort consisted of patients from two other centers. Two MRI-based DLRNs for prediction of tumor relapse after resection of STS were established. We universally tested the DLRNs and compared them with other prediction models constructed by using widespread adopted predictors (i.e., staging systems and Ki67) instead of radiomics features.
Results
The DLRN1 model incorporated plain MRI-based radiomics signature into the clinical data, and the DLRN2 model integrated radiomics signature extracted from plain and contrast-enhanced MRI with the clinical predictors. Across both study sets, the two MRI-based DLRNs had relatively better prognostic capability (
C
index ≥ 0.721 and median AUC ≥ 0.746;
p
< 0.05 compared with most other models and predictors) and less opportunity for prediction error (integrated Brier score ≤ 0.159). The decision curve analysis indicates that the DLRNs have greater benefits than staging systems, Ki67, and other models. We selected appropriate cutoff values for the DLRNs to divide STS recurrence into three risk strata (low, medium, and high) and calculated those groups’ cumulative risk rates.
Conclusion
The DLRNs were shown to be a reliable and externally validated tool for predicting STS recurrence by comparing with other prediction models.
Key Points
•
The prediction of a high recurrence rate of STS before emergence of local recurrence can help to determine whether more active treatment should be implemented.
•
Two MRI-based DLRNs for prediction of tumor relapse were shown to be a reliable and externally validated tool for predicting STS recurrence.
•
We used the DLRNs to divide STS recurrence into three risk strata (low, medium, and high) to facilitate more targeted postoperative management in the clinic.
Abstract
Object
Varus-valgus lower alignment is a risk factor for patellofemoral osteoarthritis, but malalignment alone affect not only the tibiofemoral joint but also the patellofemoral joint. The ...aim of the present study was to analyse the contact area of patellofemoral joint in varus alignment and valgus alignment of healthy subjects using magnetic resonance imaging.
Methods
Twenty-six healthy subjects with valgus lower limb alignment (Group I, n = 26) and twenty-six volunteers with varus lower limb alignment (Group II, n = 26) was performed. An MRI scan was used to capture and measure the patellofemoral joint articular cartilage contact area at different degrees of knee flexion (20°, 40°,60°) in passive movement. All subjects were categorized on the basis of the global limb alignment and mechanical alignment of the femur and tibia. Varus alignment is hip–knee–ankle angle ≥ 3°; and valgus alignment is hip–knee–ankle angle ≥ − 3°. To obtain medial facet contact area and lateral facet contact area for each slice, the length of each respective line of contact was multiplied by the 5 mm slice thickness.
Results
The overall joint contact area increased from 168.0 ± 20.5 mm
2
at 20° knee flexion to 334.4 ± 30.5 mm
2
at 60° knee flexion in group (I) The overall joint contact area increased from 178.0 ± 18.9 mm
2
at 20° knee flexion to 328.9 ± 27.2 mm
2
at 60° knee flexion in group (II) There was a significant difference in lateral facet contact area between group I and group II at 40° of knee flexion. There was significantly different in medial facet contact area between group I and group II at 20° and 40° of knee flexion.
Conclusions
Throughout the knee movement, the contact area on the lateral facet of the patellofemoral joint was greater in the valgus group. In the early phase of knee flexion, the contact area of the medial patellofemoral joint was larger in the varus group. Lower alignment is an important factor in patellofemoral joint degeneration.
To develop a magnetic resonance imaging (MRI)-based radiomics signature for evaluating the risk of soft tissue sarcoma (STS) disease progression.
We retrospectively enrolled 335 patients with STS ...(training, validation, and The Cancer Imaging Archive sets, n = 168, n = 123, and n = 44, respectively) who underwent surgical resection. Regions of interest were manually delineated using two MRI sequences. Among 12 machine learning-predicted signatures, the best signature was selected, and its prediction score was inputted into Cox regression analysis to build the radiomics signature. A nomogram was created by combining the radiomics signature with a clinical model constructed using MRI and clinical features. Progression-free survival was analyzed in all patients. We assessed performance and clinical utility of the models with reference to the time-dependent receiver operating characteristic curve, area under the curve, concordance index, integrated Brier score, decision curve analysis.
For the combined features subset, the minimum redundancy maximum relevance-least absolute shrinkage and selection operator regression algorithm + decision tree classifier had the best prediction performance. The radiomics signature based on the optimal machine learning-predicted signature, and built using Cox regression analysis, had greater prognostic capability and lower error than the nomogram and clinical model (concordance index, 0.758 and 0.812; area under the curve, 0.724 and 0.757; integrated Brier score, 0.080 and 0.143, in the validation and The Cancer Imaging Archive sets, respectively). The optimal cutoff was - 0.03 and cumulative risk rates were calculated.
To assess the risk of STS progression, the radiomics signature may have better prognostic power than a nomogram/clinical model.
Enterobacter hormaechei is commonly considered a causative pathogen for nosocomial infections and it does not usually cause diseases in animals. However, researchers have recently dissociated the ...pathogenic Enterobacter hormaechei from foxes and piglets. Here, the Enterobacter hormaechei was first found to be associated with respiratory disease in unweaned calves in China.
A 2-month-old calf was severely sick and diagnosed with respiratory infection by a rural veterinarian, and it died 5 days after treatment with penicillin G. The lung sample was then run through histopathological analysis and pathogen isolation. The sequence analysis and biochemical tests results showed the isolated bacterium strain to be Enterobacter hormaechei, and drug sensitivity tests showed resistance to all β-lactam antimicrobials and sensitivity to quinolones. Thickened alveoli septum, inflammatory cell infiltration, and erythrocyte diapedesis around the pulmonary alveoli septum were visible in lung histopathological sections. One week later, at the same farm, another calf showed similar clinical signs, and the Enterobacter hormaechei strain was isolated from its nasal discharge; after a week of treatment with enrofloxacin, as suggested by the results of drug sensitivity tests, this calf fully recovered.
To the best of our knowledge, this is the first case report of calves with respiratory disease that was associated with E. hormaechei, and multi-drug resistance was observed in isolates.
'Candidatus Mycoplasma haemobos' is an emerging pathogen in the genus Mycoplasma. The Rhipicephalus (Boophilus) microplus tick has been suspected to be the vector of 'C. M. haemobos'. To determine ...the role of R. (B.) microplus in transmission of 'C. M. haemobos', we tested the competence of R. (B.) microplus larvae to acquire 'C. M. haemobos' from positive female ticks and to serve as a 'C. M. haemobos' vector in mice. Using PCR and sequencing, we also analyzed the epidemic strains of 'C. M. haemobos' among R. (B.) microplus ticks collected from goats and sheep in southern Henan Province, central China. Our results identified three epidemic strains of 'C. M. haemobos', and the positive female ticks naturally infected could pass 'C. M. haemobos' at egg and larval stages. Furthermore, 'C. M. haemobos' infected larvae could transmit the pathogens to mice during feeding, and the negative larvae could acquire 'C. M. haemobos' from infected mice. Our study shows that R. (B.) microplus ticks could serve as a vector and reservoir of 'C. M. haemobos'.
Purpose
The aim of this study is to compare the blood oxygen level–dependent (BOLD) fluctuation power in 96 frequency points ranging from 0 to 0.25 Hz between benign and malignant musculoskeletal ...(MSK) tumors
via
power spectrum analyses using functional magnetic resonance imaging (fMRI).
Materials and methods
BOLD-fMRI and T1-weighted imaging (T1WI) of 92 patients with benign or malignant MSK tumors were acquired by 1.5-T magnetic resonance scanner. For each patient, the tumor-related BOLD time series were extracted, and then, the power spectrum of BOLD time series was calculated and was then divided into 96 frequency points. A two-sample
t
-test was used to assess whether there was a significant difference in the powers (the “power” is the square of the BOLD fluctuation amplitude with arbitrary unit) of each frequency point between benign and malignant MSK tumors. The receiver operator characteristic (ROC) analysis was used to assess the diagnostic capability of distinguishing between benign and malignant MSK tumors.
Results
The result of the two-sample
t
-test showed that there was significant difference in the power between benign and malignant MSK tumor at frequency points of 58 (0.1508 Hz,
P
= 0.036), 59 (0.1534 Hz,
P
= 0.032), and 95 (0.247 Hz,
P
= 0.014), respectively. The ROC analysis of mean power of three frequency points showed that the area of under curve is 0.706 (
P =
0.009), and the cutoff value is 0.73130. If the power of the tumor greater than or equal to 0.73130 is considered the possibility of benign tumor, then the diagnostic sensitivity and specificity values are 83% and 59%, respectively. The
post hoc
analysis showed that the merged power of 0.1508 and 0.1534 Hz in benign MSK tumors was significantly higher than that in malignant ones (
P
= 0.014). The ROC analysis showed that, if the benign MSK tumor was diagnosed with the power greater than or equal to the cutoff value of 1.41241, then the sensitivity and specificity were 67% and 68%, respectively.
Conclusion
The mean power of three frequency points at 0.1508, 0.1534, and 0.247 Hz may potentially be a biomarker to differentiate benign from malignant MSK tumors. By combining the power of 0.1508 and 0.1534 Hz, we could better detect the difference between benign and malignant MSK tumors with higher specificity.
Bovine pestiviruses include
(BVDV-1),
(BVDV-2), and
, which was originally called
. We conducted an epidemiological investigation for pestiviruses circulating in backyard cattle farms in central ...China. RT-PCR assays and sequences analysis were conducted on 54 nasal swabs, 26 serum samples, and three lung samples from cattle with respiratory infections and identified 29 pestivirus strains, including 24
and five
strains. Phylogenetic analysis based on partial 5'-UTR and Npro sequences showed that the genotypes of 24
strains included
1b (six isolates),
1m (six isolates),
1q (two isolates),
1u (one isolates), and
1o (nine isolates, a putative new sub-genotype). In addition, a single
agenotype included all five
strains. This study revealed extensive genetic variations within bovine pestivirus isolates derived from cattle in backyard farms in Central China, and this epidemiological information improves our understanding of the epidemics of bovine Pestiviruses, as well as will be useful in designing and evaluating diagnostic methods and developing more effective vaccines.
Background
Preoperative prediction of soft tissue sarcoma (STS) grade is important for treatment decisions. Therefore, formulation an STS grade model is strongly needed.
Purpose
To develop and test ...an magnetic resonance imaging (MRI)‐based radiomics nomogram for predicting the grade of STS (low‐grade vs. high grade).
Study Type
Retrospective
Population
One hundred and eighty patients with STS confirmed by pathologic results at two independent institutions were enrolled (training set, N = 109; external validation set, N = 71).
Field Strength/Sequence
Unenhanced T1‐weighted (T1WI) and fat‐suppressed T2‐weighted images (FS‐T2WI) were acquired at 1.5 T and 3.0 T.
Assessment
Clinical‐MRI characteristics included age, gender, tumor‐node‐metastasis (TNM) stage, American Joint Committee on Cancer (AJCC) stage, progression‐free survival (PFS), and MRI morphological features (ie, margin). Radiomics feature extraction were performed on T1WI and FS‐T2WI images by minimum redundancy maximum relevance (MRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm. The selected features constructed three radiomics signatures models (RS‐T1， RS‐FST2, and RS‐Combined). Univariate and multivariate logistic regression analysis were applied for screening significant risk factors. Radiomics nomogram was constructed by incorporating the radiomics signature and risk factors.
Statistical Tests
Clinical‐MRI characteristics were performed by a univariate analysis. Model performances (discrimination, calibration, and clinical usefulness) were validated in the external validation set. The RS‐T1 model, RS‐FST2 model, and RS‐Combined model had an area under curves (AUCs) of 0.645, 0.641, and 0.829, respectively, in the external validation set. The radiomics nomogram, incorporating significant risk factors and the RS‐Combined model had AUCs of 0.916 (95%CI, 0.866–0.966, training set) and 0.879 (95%CI, 0.791–0.967, external validation set), and demonstrated good calibration and good clinical utility.
Data Conclusion
The proposed noninvasive MRI‐based radiomics models showed good performance in differentiating low‐grade from high‐grade STSs.
Level of Evidence
3
Technical Efficacy Stage
2
Mengulin sandstone reservoir in Huabei oilfield is low- temperature heavy oil reservoir. Recently, it is at later stage of waterflooding development. The producing degree of water flooding is poor, ...and it is difficult to keep yield stable. To improve oilfield development effect, according to the characteristics of reservoir geology, microbial enhanced oil recovery to improve oil displacement efficiency is researched. 2 microbial strains suitable for the reservoir conditions were screened indoor. The growth characteristics of strains, compatibility and function mechanism with crude oil were studied. Results show that the screened strains have very strong ability to utilize petroleum hydrocarbon to grow and metabolize, can achieve the purpose of reducing oil viscosity, and can also produce biological molecules with high surface activity to reduce the oil-water interfacial tension. 9 oil wells had been chosen to carry on the pilot test of microbial stimulation, of which 7 wells became effective with better experiment results. The measures effective rate is 77.8%, the increased oil is 1,093.5 tons and the valid is up to 190 days.
•A new dynamic supplier selection and inventory model for a serial supply chain is proposed.•Suppliers use a price break and discount scheme that considers order frequency and lead time.•The ...manufacturer achieves minimal purchasing cost by taking advantage of economies of scale.•A second model is proposed where the length of the time period is considered as a variable.•It is shown that the length of the time period affects inventory planning decisions.
A new supplier price break and discount scheme taking into account order frequency and lead time is introduced and incorporated into an integrated inventory planning model for a serial supply chain that minimizes the overall incurred cost including procurement, inventory holding, production, and transportation. A mixed-integer linear programming (MILP) formulation is presented addressing this multi-period, multi-supplier, and multi-stage problem with predetermined time-varying demand for the case of a single product. Then, the length of the time period is considered as a variable. A new MILP formulation is derived when each period of the model is split into multiple sub-periods, and under certain conditions, it is proved that the optimal solution and objective value of the original model form a feasible solution and an upper bound for the derived model. In a numerical example, three scenarios of the derived model are solved where the number of sub-period is set to 2, 3, and 4. The results further show the decrease of the optimal objective value as the length of the time period is shortened. Sufficient evidence demonstrates that the length of the time period has a significant influence on supplier selection, lot sizing allocation, and inventory planning decisions. This poses the necessity of the selection of appropriate length of a time period, considering the trade-off between model complexity and cost savings.
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