Citations

Purpose To evaluate the feasibility of using three‐dimensional (3D) MR elastography (MRE) to determine the stiffness of the pancreas in healthy volunteers. Materials and Methods Twenty healthy volunteers underwent 1.5 Tesla MRE exams using an accelerated echo planar imaging (EPI) pulse sequence with low‐frequency vibrations (40 and 60 Hz). Stiffness was calculated with a 3D direct inversion algorithm. The mean shear stiffness in five pancreatic subregions (uncinate, head, neck, body, and tail) and the corresponding liver stiffness were calculated. The intrasubject coefficient of variation (CV) was calculated as a measure of the reproducibility for each volunteer. Results The mean shear stiffness (average of values obtained in different pancreatic subregions) was (1.15 ± 0.17) kPa at 40 Hz, and (2.09 ± 0.33) kPa at 60 Hz. The corresponding liver stiffness was higher than the pancreas stiffness at 40 Hz ([1.60 ± 0.21] kPa, mean pancreas‐to‐liver stiffness ratio: 0.72), but similar at 60Hz ([2.12 ± 0.23) kPa, mean ratio: 0.95). The mean intrasubject CV for each pancreatic subregion was lower at 40 Hz than 60 Hz ( P < 0.05 for all subregions, range: 11.9–15.7% at 40 Hz and 16.5–19.6% at 60 Hz). Conclusion The 3D pancreatic MRE can provide promising and reproducible stiffness measurements throughout the pancreas, with more consistent data acquired at 40 Hz. J. Magn. Reson. Imaging 2015;41:369–375. © 2013 Wiley Periodicals, Inc .

Abstract Motivation: Modern techniques have produced many sequence annotation databases and protein structure portals, but these Web resources are rarely integrated in ways that permit straightforward exploration of protein functional residues and their co-localization. Results: We have created the AMASS database, which maps 1D sequence annotation databases to 3D protein structures with an intuitive visualization interface. Our platform also provides an analysis service that screens mass spectrometry sequence data for post-translational modifications that reside in functionally relevant locations within protein structures. The system is built on the premise that functional residues such as active sites, cancer mutations and post-translational modifications within proteins may co-localize and share common functions. Availability and implementation: AMASS database is implemented with Biopython and Apache as a freely available Web server at amass-db.org. Contact: clinton.mielke@gmail.com

Key Points Alternatively polarized macrophages are abundant constituents of the tumor microenvironment in T-cell lymphoproliferative disorders. GATA-3 expression identifies a subset of PTCL, NOS with a distinct cytokine profile and inferior survival.

Reducing the incidence and mortality rates for clear cell renal cell carcinoma (ccRCC) remains a significant clinical challenge with poor 5‐year survival rates. A unique tissue cohort was assembled of matched ccRCC and distal nontumor tissues (n = 20) associated with moderate risk of disease progression, half of these from individuals who progressed to metastatic disease and the other half who remained disease free. These tissues were used for MALDI imaging MS profiling of proteins in the 2–20 kDa range, resulting in a panel of 108 proteins that had potential disease‐specific expression patterns. Protein lysates from the same tissues were analyzed by MS/MS, resulting in identification of 56 proteins of less than 20 kDa molecular weight. The same tissues were also used for global lipid profiling analysis by MALDI‐FT‐ICR MS. From the cumulative protein and lipid expression profile data, a refined panel of 26 proteins and 39 lipid species was identified that could either distinguish tumor from nontumor tissues, or tissues from recurrent disease progressors from nonrecurrent disease individuals. This approach has the potential to not only improve prognostic assessment and enhance postoperative surveillance, but also to inform on the underlying biology of ccRCC progression.

Depression symptoms contribute to significant morbidity and health care utilization. The aim of this study was to determine the impact of symptom improvement (to remission) on outpatient clinical visits by depressed primary care patients. This study was a retrospective chart review analysis of 1733 primary care patients enrolled into collaborative care management (CCM) or usual care (UC) with 6-month follow-up data. Baseline data (including demographic information, clinical diagnosis, and depression severity) and 6-month follow-up data (Patient Health Questionnaire scores and the number of outpatient visits utilized) were included in the data set. To control for individual patient complexity and pattern of usage, the number of outpatient visits for 6 months prior to enrollment also was measured as was the presence of medical comorbidities. Multiple logistic regression analysis demonstrated that clinical remission at 6 months was an independent predictor of outpatient visit outlier status (>8 visits) (odds ratio [OR] 0.609, confidence interval (CI) 0.460–0.805, P <0.01) when controlling for all other independent variables including enrollment into CCM or UC. The OR of those patients not in remission at 6 months having outpatient visit outlier status was the inverse of this at 1.643 (CI 1.243–2.173). The most predictive variable for determining increased outpatient visit counts after diagnosis of depression was increased outpatient visits prior to diagnosis (OR 4.892, CI 3.655–6.548, P <0.01). In primary care patients treated for depression, successful treatment to remission at 6 months decreased the likelihood of the patient having more than 8 visits during the 6 months after diagnosis. ( Population Health Management 2014;17:180–184)

Purpose High-quality supportive care is an essential component of comprehensive cancer care. We implemented a patient-centered quality of cancer care survey to examine and identify predictors of quality of supportive care for bowel problems, pain, fatigue, depression, and other symptoms among 1,109 patients with colorectal cancer. Patients and Methods Patients with new diagnosis of colorectal cancer at any Veterans Health Administration medical center nationwide in 2008 were ascertained through the Veterans Affairs Central Cancer Registry and sent questionnaires assessing a variety of aspects of patient-centered cancer care. We received questionnaires from 63% of eligible patients (N = 1,109). Descriptive analyses characterizing patient experiences with supportive care and binary logistic regression models were used to examine predictors of receipt of help wanted for each of the five symptom categories. Results There were significant gaps in patient-centered quality of supportive care, beginning with symptom assessment. In multivariable modeling, the impact of clinical factors and patient race on odds of receiving wanted help varied by symptom. Coordination of care quality predicted receipt of wanted help for all symptoms, independent of patient demographic or clinical characteristics. Conclusion This study revealed substantial gaps in patient-centered quality of care, difficult to characterize through quality measurement relying on medical record review alone. It established the feasibility of collecting patient-reported quality measures. Improving quality measurement of supportive care and implementing patient-reported outcomes in quality-measurement systems are high priorities for improving the processes and outcomes of care for patients with cancer.