Background
Computer‐aided methods have been widely applied to diagnose lesions detected on breast MRI, but fully‐automatic diagnosis using deep learning is rarely reported.
Purpose
To evaluate the ...diagnostic accuracy of mass lesions using region of interest (ROI)‐based, radiomics and deep‐learning methods, by taking peritumor tissues into consideration.
Study Type
Retrospective.
Population
In all, 133 patients with histologically confirmed 91 malignant and 62 benign mass lesions for training (74 patients with 48 malignant and 26 benign lesions for testing).
Field Strength/Sequence
3T, using the volume imaging for breast assessment (VIBRANT) dynamic contrast‐enhanced (DCE) sequence.
Assessment
3D tumor segmentation was done automatically by using fuzzy‐C‐means algorithm with connected‐component labeling. A total of 99 texture and histogram parameters were calculated for each case, and 15 were selected using random forest to build a radiomics model. Deep learning was implemented using ResNet50, evaluated with 10‐fold crossvalidation. The tumor alone, smallest bounding box, and 1.2, 1.5, 2.0 times enlarged boxes were used as inputs.
Statistical Tests
The malignancy probability was calculated using each model, and the threshold of 0.5 was used to make a diagnosis.
Results
In the training dataset, the diagnostic accuracy was 76% using three ROI‐based parameters, 84% using the radiomics model, and 86% using ROI + radiomics model. In deep learning using the per‐slice basis, the area under the receiver operating characteristic (ROC) was comparable for tumor alone, smallest and 1.2 times box (AUC = 0.97‐0.99), which were significantly higher than 1.5 and 2.0 times box (AUC = 0.86 and 0.71, respectively). For per‐lesion diagnosis, the highest accuracy of 91% was achieved when using the smallest bounding box, and that decreased to 84% for tumor alone and 1.2 times box, and further to 73% for 1.5 times box and 69% for 2.0 times box. In the independent testing dataset, the per‐lesion diagnostic accuracy was also the highest when using the smallest bounding box, 89%.
Data Conclusion
Deep learning using ResNet50 achieved a high diagnostic accuracy. Using the smallest bounding box containing proximal peritumor tissue as input had higher accuracy compared to using tumor alone or larger boxes.
Level of Evidence: 3
Technical Efficacy: Stage 2
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Background
Prior studies indicated a link between urinary catheter use and urinary complications, highlighting the need for comprehensive, gender‐specific investigations. This study explored the ...association through a national retrospective cohort, emphasizing gender disparities and long‐term outcomes.
Methods
Our study utilized data from the entire population covered by Taiwan's National Health Insurance Research Database from 2000 to 2017. We included 148,304 patients who had undergone Foley catheter placement and their propensity‐scores matched controls in the study. We evaluated urinary complications, which encompassed urinary tract cancer, urolithiasis, urethral stricture, obstructive uropathy, reflux uropathy, fistula, diverticulum, caruncle, false passage, prolapsed urethral mucosa, urinary tract rupture, and urinary tract infection. These were assessed using the Fine and Gray sub‐distribution proportional hazards model to compare between the Foley and non‐Foley groups. Sensitivity analyses were conducted with different matching ratios.
Results
In the study, the non‐Foley group presented a marginally higher mean age (75.24 ± 10.47 years) than the Foley group (74.09 ± 10.47 years). The mean duration of Foley catheterization was 6.1 ± 4.19 years. Men with Foley catheterization exhibited the highest adjusted sub‐distribution hazard ratios for urinary tract cancer (6.57, 95% CI: 5.85–7.37), followed by women with Foley catheterization (4.48, 95% CI: 3.98–5.05), and men without catheterization (1.58, 95% CI: 1.39–1.8) in comparison with women without the procedure. Furthermore, men with Foley catheterization were found to be at the greatest risk for complications such as urolithiasis, urethral stricture, obstructive and reflux uropathy, fistula, diverticulum, caruncle, false passage, prolapsed urethral mucosa, and urinary tract rupture. Conversely, women with urinary catheterization were most susceptible to urinary tract infections.
Conclusions
The evidence confirms that urinary catheterization significantly increases urinary complications, particularly among men. Our study underscores the crucial need for healthcare providers to carefully evaluate the necessity of catheterization, aim to shorten its duration whenever feasible, and strictly adhere to established protocols to minimize complications.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Plants of the species
Gomphocarpus physocarpus
, commonly known as balloon plant or swan plant, exhibiting virus-like symptoms of mosaic, mottle and crinkling were observed and collected in the ...southwestern part of Taiwan in 2015. Electron microscopic examination showed the presence of virus-like flexuous-rod particles. Potyvirus pinwheel-shape and laminated inclusion bodies were observed in the preparations of ultrathin sections of diseased leaves. The complete genome sequence of the potyvirus of balloon plant was determined. It is 9998 nucleotides in length, excluding the 3′-terminal poly(A) tail. It contains two open reading frames encoding a polyprotein of 3196 amino acids and a PIPO protein of 89 amino acids. The polyprotein gene shares 52.8-68.4% nucleotide sequence identity and 40.2-75.8% amino acid sequence identity with other potyviruses tested. Molecular analysis indicates that the virus is most closely related to but distinct from keunjorong mosaic virus (KjMV). The virus causing mosaic, mottle and crinkling on
Gomphocarpus
plants (gomphocarpus mosaic virus, GoMV) likely belongs to a new species of the genus
Potyvirus
.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Objectives:
A subset of meningiomas may show progression/recurrence (P/R) after surgical resection. This study applied pre-operative MR radiomics based on support vector machine (SVM) to predict P/R ...in meningiomas.
Methods:
From January 2007 to January 2018, 128 patients with pathologically confirmed WHO grade I meningiomas were included. Only patients who had undergone pre-operative MRIs and post-operative follow-up MRIs for more than 1 year were studied. Pre-operative T2WI and contrast-enhanced T1WI were analyzed. On each set of images, 32 first-order features and 75 textural features were extracted. The SVM classifier was utilized to evaluate the significance of extracted features, and the most significant four features were selected to calculate SVM score for each patient.
Results:
Gross total resection (Simpson grades I–III) was performed in 93 (93/128, 72.7%) patients, and 19 (19/128, 14.8%) patients had P/R after surgery. Subtotal tumor resection, bone invasion, low apparent diffusion coefficient (ADC) value, and high SVM score were more frequently encountered in the P/R group (
p
< 0.05). In multivariate Cox hazards analysis, bone invasion, ADC value, and SVM score were high-risk factors for P/R (
p
< 0.05) with hazard ratios of 7.31, 4.67, and 8.13, respectively. Using the SVM score, an AUC of 0.80 with optimal cutoff value of 0.224 was obtained for predicting P/R. Patients with higher SVM scores were associated with shorter progression-free survival (
p
= 0.003).
Conclusions:
Our preliminary results showed that pre-operative MR radiomic features may have the potential to offer valuable information in treatment planning for meningiomas.
A subset of non-functioning pituitary macroadenomas (NFPAs) may exhibit early progression/recurrence (P/R) after surgical resection. The purpose of this study was to apply radiomics in predicting P/R ...in NFPAs.
Only patients who had undergone preoperative MRI and postoperative MRI follow-ups for more than 1 year were included in this study. From September 2010 to December 2017, 50 eligible patients diagnosed with pathologically confirmed NFPAs were identified. Preoperative coronal T2WI and contrast-enhanced (CE) T1WI imaging were analyzed by computer algorithms. For each imaging sequence, 32 first-order features and 75 texture features were extracted. Support vector machine (SVM) classifier was utilized to evaluate the importance of extracted parameters, and the most significant three parameters were used to build the prediction model. The SVM score was calculated based on the three selected features.
Twenty-eight patients exhibited P/R (28/50, 56%) after surgery. The median follow-up time was 38 months, and the median time to P/R was 20 months. Visual disturbance, hypopituitarism, extrasellar extension, compression of the third ventricle, large tumor height and volume, failed optic chiasmatic decompression, and high SVM score were more frequently encountered in the P/R group (
< 0.05). In multivariate Cox hazards analysis, symptoms of sex hormones, hypopituitarism, and SVM score were high risk factors for P/R (
< 0.05) with hazard ratios of 10.71, 2.68, and 6.88. The three selected radiomics features were T1 surface-to-volume radio, T1 GLCM-informational measure of correlation, and T2 NGTDM-coarseness. The radiomics predictive model shows 25 true positive, 16 true negative, 6 false positive, and 3 false negative cases, with an accuracy of 82% and AUC of 0.78 in differentiating P/R from non-P/R NFPAs. For SVM score, optimal cut-off value of 0.537 and AUC of 0.87 were obtained for differentiation of P/R. Higher SVM scores were associated with shorter progression-free survival (
< 0.001).
Our preliminary results showed that objective and quantitative MR radiomic features can be extracted from NFPAs. Pending more studies and evidence to support the findings, radiomics analysis of preoperative MRI may have the potential to offer valuable information in treatment planning for NFPAs.
Andrographolide (Andro), the major constituent of
, is was known to reduces inflammatory reaction. In the current study, the ability of Andro to reduce pain sensation in a rat post-operative wound ...model was explored. The hind paws of 18 Sprague-Dawley rats (SD) bearing post-operative wounds received the following three treatments: Saline, Andro via direct injection into the paw (Andro-injected) and Tablet containing Andro + poly (lactic-co-glycolic acid) (PLGA) (Andro-tablet). Von Frey tests assessed mechanical allodynia at 1, 3, 5 h and 1-, 2-, 3-, 4-, and 5-days post-operation. Behavioral analyses were performed to measure reaction threshold and reaction frequencies. Immunoreactivity of p-ERK and GluR1 was examined in the dorsal horn of the spinal cord. Histopathological and immunostaining studies were conducted on paw epidermis to observe the gross morphology and angiogenesis. The threshold for inducing allodynia increased and the reaction frequency reduced in the Andro-injected group compared to the saline-group, at 3 h post-surgery and the effect lasted between 3-4 days. The threshold for inducing pain and reaction frequency for the Andro-tablet group did not differ from the saline-treated group. The levels of p-ERK and GluR1 in the dorsal horn were reduced after Andro treatment. No significant difference in wound healing index was observed between saline and Andro-injected groups, but CD-31 staining showed less angiogenesis in the Andro-injected group. Andro significantly reduced mechanical allodynia compared to saline treatment, both in shorter and longer time frames. Furthermore, Andro influenced the expression of p-ERK and GluR1 in the dorsal horn, and the angiogenesis process in the wound healing area.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Abstract
Objective
The incidence and prevalence of gout are increasing, but the management is poor. Considering the increased prevalence of gout in the diabetic population, this study evaluated the ...effects of pioglitazone, an insulin resistance inhibitor, on the incidence of gout in the diabetic population.
Methods
We used data from the National Health Insurance program in Taiwan. The pioglitazone cohort contained 30 100 patients and each patient was age and sex matched with three non-pioglitazone users who were randomly selected from the diabetic population. Cox proportional hazards regression analysis was conducted to estimate the effects of pioglitazone on the incidence of gout in the diabetic population.
Results
The incidence of gout was significantly lower in pioglitazone users than in non-pioglitazone users adjusted hazard ratio (aHR) 0.81 (95% CI 0.78, 0.85). The HR for the incidence of gout was lower in both male aHR 0.80 (95% CI 0.75, 0.85) and female aHR 0.83 (95% CI 0.78, 0.88) pioglitazone users than in non-pioglitazone users. An analysis of three age groups (<40, 40-59 and ⩾60 years) revealed that the HRs of both the 40-59 years aHR 0.78 (95% CI 0.73, 0.83) and the ⩾60 years aHR 0.85 (95% CI 0.80, 0.91) age groups were significantly lower among pioglitazone users than non-pioglitazone users.
Conclusion
Compared with the non-pioglitazone users, the incidence of gout in the diabetic population using pioglitazone was less.
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