Use of the SRU recommendations and three-tiered system can reduce the workup of ITN by one third compared with current practice without specific guidelines. One case of localized papillary carcinoma was missed when the SRU recommendations were used.
One in four thyroid biopsy encounters at our institution did not meet SRU recommendations for biopsy. The application of SRU recommendations reduces the number of benign nodules that undergo workup. Potentially missed malignancies in SRU-negative nodules are less aggressive by histologic type and stage compared with SRU-positive malignancies.
Automatic survival prognosis in glioblastoma (GBM) could result in improved treatment planning for the patient. The purpose of this research is to investigate the association of survival in GBM patients with tumor features in pre-operative magnetic resonance (MR) images assessed using a fully automatic computer algorithm. MR imaging data for 68 patients from two US institutions were used in this study. The images were obtained from the Cancer Imaging Archive. A fully automatic computer vision algorithm was applied to segment the images and extract eight imaging features from the MRI studies. The features included tumor side, proportion of enhancing tumor, proportion of necrosis, T1/FLAIR ratio, major axis length, minor axis length, tumor volume, and thickness of enhancing margin. We constructed a multivariate Cox proportional hazards regression model and used a likelihood ratio test to establish whether the imaging features are prognostic of survival. We also evaluated the individual prognostic value of each feature through multivariate analysis using the multivariate Cox model and univariate analysis using univariate Cox models for each feature. We found that the automatically extracted imaging features were predictive of survival (p = 0.031). Multivariate analysis of individual features showed that two individual features were predictive of survival: proportion of enhancing tumor (p = 0.013), and major axis length (p = 0.026). Univariate analysis indicated the same two features as significant (p = 0.021, and p = 0.017 respectively). We conclude that computer-extracted MR imaging features can be used for survival prognosis in GBM patients.
Based on thyroid cancers diagnosed during a decade, incidental malignancies missed by the 3-tiered system represent 1.2% of all thyroid malignancies. Three-tiered system-negative incidental cancers were all small papillary cancers. Given that few cancers would be missed and most are less aggressive, we propose that the 3-tiered system could be adopted in clinical practice to guide the workup of ITN identified on CT, MRI, and PET/CT.
Chelated hollow microcapsules are unstable under in vitro conditions because of their hygroscopic nature. Nongel inducing cations, such as Na+, stabilize the outer membrane of the alginate-polylysine-alginate microcapsules leading to more stable beads. We made different batches of empty capsules with a mean +/- SEM diameter of 607+/-11 microns, and found that within 1 week of incubating these capsules in normal saline at 37 degrees C, they increased to 718+/-10 microns (p < 0.05, n = 5). In initial experiments, we made different batches of capsules and divided them into two groups. One group was left untreated (control) whereas the other was treated with 6 mM Na2SO4 for 30 min, before incubation in saline at 37 degrees C. Control capsules increased in weight and size, before beginning to melt in less than 1 week. In contrast, treated capsules rapidly lost weight and remained intact during 1 month of follow-up. In perifusion experiments, we found no deleterious effect of sodium sulfate treatment on the function of islets enclosed in the capsules.
Imaging-detected ITCs are uncommon. Two percent (16 of 680) of malignancies would not undergo fine-needle aspiration biopsy or surgery if the SRU guidelines were used for work-up of incidental thyroid nodules. SRU criteria-negative tumors are lower in stage than SRU criteria-positive tumors.
The authors proposed and evaluated an algorithm that, given a set of MR volumes of a glioblastoma patient, is able to extract MR image features that correlate well with their reference standard. Future studies will evaluate how well the computer-extracted features predict survival.
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