ABSTRACT
BACKGROUND: Despite the prognostic relevance of cachexia in pancreatic cancer, individual body composition has not been routinely integrated into treatment planning. In this multicenter study, we investigated the prognostic value of sarcopenia and myosteatosis automatically extracted from routine computed tomography (CT) scans of patients with advanced pancreatic ductal adenocarcinoma (PDAC). PATIENTS AND METHODS: We retrospectively analyzed clinical imaging data of 601 patients from three German cancer centers. We applied a deep learning approach to assess sarcopenia by the abdominal muscle-to-bone ratio (MBR) and myosteatosis by the ratio of abdominal inter- and intramuscular fat to muscle volume. In the pooled cohort, univariable and multivariable analyses were carried out to analyze the association between body composition markers and overall survival (OS). We analyzed the relationship between body composition markers and laboratory values during the first year of therapy in a subgroup using linear regression analysis adjusted for age, sex, and American Joint Committee on Cancer (AJCC) stage. RESULTS: Deep learning-derived MBR [hazard ratio (HR) 0.60, 95% confidence interval (CI) 0.47-0.77, P < 0.005] and myosteatosis (HR 3.73, 95% CI 1.66-8.39, P < 0.005) were significantly associated with OS in univariable analysis. In multivariable analysis, MBR (P = 0.019) and myosteatosis (P = 0.02) were associated with OS independent of age, sex, and AJCC stage. In a subgroup, MBR and myosteatosis were associated with albumin and C-reactive protein levels after initiation of therapy. Additionally, MBR was also associated with hemoglobin and total protein levels. CONCLUSIONS: Our work demonstrates that deep learning can be applied across cancer centers to automatically assess sarcopenia and myosteatosis from routine CT scans. We highlight the prognostic role of our proposed markers and show a strong relationship with protein levels, inflammation, and anemia. In clinical practice, automated body composition analysis holds the potential to further personalize cancer treatment.
Subject(s)
Deep Learning , Pancreatic Neoplasms , Sarcopenia , Humans , Prognosis , Sarcopenia/complications , Muscle, Skeletal/pathology , Retrospective Studies , Body Composition , Pancreatic Neoplasms/complications , Pancreatic Neoplasms/pathologyABSTRACT
Diagnostic guidelines for thyroid nodules focus on malignancy risk assessment to avoid unnecessary diagnostic operations. These guidelines recommend a combination of tests in form of a diagnostic algorithm. The present study analyzed the recommended algorithm and its implementation by different medical professionals. Preoperative diagnostic procedures, laboratory tests and histopathological findings of patients who underwent thyroid surgery between 2006 and 2013 were analyzed. The results were stratified by the assignation by specialized endocrinologists (ENP), general practitioners (GP) or Goethe-University Hospital Frankfurt (UKF). 677 patients were enrolled, of these 62% were assigned by UKF, 18.5% by an ENP and 19.5% by a GP. Ultrasonography rate was significantly higher in UKF (97.6%) compared to patients assigned by GP (90.9%, p<0.0001). Rates for fine-needle aspiration cytology ranged between 47.6% in UKF and 23.2% in ENP (p<0.0001). In over 93% of the patients an analysis of thyroid-stimulating hormone and triiodothyronine/thyroxin was realized. The overall malignancy rate was 11.82%. The malignancy rate was significantly higher if a FNA biopsy was performed (16.35 vs. 8.94%; p=0.0048). A higher malignancy rate could only be seen if the preoperative diagnostic workup included FNA. Besides this, the grade of algorithm adherence showed no effect on the malignancy rate.
Subject(s)
Algorithms , Guideline Adherence , Thyroid Nodule/surgery , Adolescent , Adult , Aged , Aged, 80 and over , Child , Female , Humans , Male , Middle Aged , Retrospective Studies , Risk Factors , Thyroid Nodule/epidemiology , United Kingdom/epidemiologyABSTRACT
UNLABELLED: Vascular endothelial growth factor (VEGF) is a critical regulator of angiogenesis and is involved in tumor development. To date, the role of VEGF in benign diseases of the thyroid is not well known. The purpose of the present study is to determine the expression of VEGF and its receptors in primary cultures of human thyrocytes. METHODS: 50 patients with uninodular (n=11), multinodular (n=15), recurrent goiter (n=14) and Graves' disease (n=10) were enrolled. Nodular and corresponding paranodular tissue was obtained after surgery and investigated. RNA and protein were extracted from primary thyrocyte cultures. PCR, western blot and ELISA were performed to evaluate VEGF isoforms and VEGF receptor 1 and 2. RESULTS: Significantly increased transcription and protein expression of VEGF and its receptors were detected in nodular tissue of uninodular and recurrent goiter compared to the corresponding normal tissue. Active secretion of VEGF by thyrocytes was confirmed by ELISA. In multinodu-lar goiter, no difference could be found between nodular and corresponding paranodular tissue in terms of expression of VEGF or its receptors. Furthermore, we found the highest levels of VEGF and its receptors in tissue obtained from patients with Graves' disease. CONCLUSION: Increased expression of VEGF and its receptors might be crucial in the proliferation of thyrocytes and therefore may contribute to the development of goiter and goiter recurrence.