The diaphragm is the primary muscle involved in active inspiration and serves also as an important anatomical landmark that separates the thoracic and abdominal cavity. However, the diaphragm muscle like other structures and organs in the human body has more than one function, and displays many anatomic links throughout the body, thereby forming a 'network of breathing'. Besides respiratory function, it is important for postural control as it stabilises the lumbar spine during loading tasks. It also plays a vital role in the vascular and lymphatic systems, as well as, is greatly involved in gastroesophageal functions such as swallowing, vomiting, and contributing to the gastroesophageal reflux barrier. In this paper we set out in detail the anatomy and embryology of the diaphragm and attempt to show it serves as both: an important exchange point of information, originating in different areas of the body, and a source of information in itself. The study also discusses all of its functions related to breathing.

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Background: There are no effective biomarkers for the management of bronchopulmonary carcinoids (BPC). We examined the utility of a neuroendocrine multigene transcript “liquid biopsy” (NETest) in BPC for diagnosis and monitoring of the disease status. Aim: To independently validate the utility of the NETest in diagnosis and management of BPC in a multicenter, multinational, blinded study. Material and Methods: The study cohorts assessed were BPC (n = 99), healthy controls (n = 102), other lung neoplasia (n = 101) including adenocarcinomas (ACC) (n = 41), squamous cell carcinomas (SCC) (n = 37), small-cell lung cancer (SCLC) (n = 16), large-cell neuroendocrine carcinoma (LCNEC) (n = 7), and idiopathic pulmonary fibrosis (IPF) (n = 50). BPC were histologically classified as typical (TC) (n = 62) and atypical carcinoids (AC) (n = 37). BPC disease status determination was based on imaging and RECIST 1.1. NETest diagnostic metrics and disease status accuracy were evaluated. The upper limit of normal (NETest) was 20. Twenty matched tissue-blood pairs were also evaluated. Data are means ± SD. Results: NETest levels were significantly increased in BPC (45 ± 25) versus controls (9 ± 8; p < 0.0001). The area under the ROC curve was 0.96 ± 0.01. Accuracy, sensitivity, and specificity were: 92, 84, and 100%. NETest was also elevated in SCLC (42 ± 32) and LCNEC (28 ± 7). NETest accurately distinguished progressive (61 ± 26) from stable disease (35.5 ± 18; p < 0.0001). In BPC, NETest levels were elevated in metastatic disease irrespective of histology (AC: p < 0.02; TC: p = 0.0006). In nonendocrine lung cancers, ACC (18 ± 21) and SCC (12 ± 11) and benign disease (IPF) (18 ± 25) levels were significantly lower compared to BPC level (p < 0.001). Significant correlations were evident between paired tumor and blood samples for BPC (R: 0.83, p < 0.0001) and SCLC (R: 0.68) but not for SCC and ACC (R: 0.25–0.31). Conclusions: Elevated ­NETest levels are indicative of lung neuroendocrine neoplasia. NETest levels correlate with tumor tissue and imaging and accurately define clinical progression.

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Background: There is a substantial unmet clinical need for an accurate and effective blood biomarker for neuroendocrine neoplasms (NEN). We therefore evaluated, under real-world conditions in an ENETS Center of Excellence (CoE), the clinical utility of the NETest as a liquid biopsy and compared its utility with chromogranin A (CgA) measurement. Methods: The cohorts were: gastroenteropancreatic NEN (GEP­NEN; n = 253), bronchopulmonary NEN (BPNEN; n = 64), thymic NEN (n = 1), colon cancer (n = 37), non-small-cell lung cancer (NSCLC; n = 63), benign lung disease (n = 59), and controls (n = 86). In the GEPNEN group, 164 (65%) had image-positive disease (IPD, n = 135) or were image-negative but resection-margin/biopsy-positive (n = 29), and were graded as G1 (n = 106), G2 (n = 49), G3 (n = 7), or no data (n = 2). The remainder (n = 71) had no evidence of disease (NED). In the BPNEN group, 43/64 (67%) had IPD. Histology revealed typical carcinoids (TC, n = 14), atypical carcinoids (AC, n = 14), small-cell lung cancer (SCLC, n = 11), and large-cell neuroendocrine carcinoma (LCNEC, n = 4). Disease status (stable or progressive) was evaluated according to RECIST v1.1. Blood sampling involved NETest (n = 563) and NETest/CgA analysis matched samples (n = 178). NETest was performed by PCR (on a scale of 0–100), with a score ≥20 reflecting a disease-positive status and >40 reflecting progressive disease. CgA positivity was determined by ELISA. Samples were deidentified and measurements blinded. The Kruskal-Wallis, Mann-Whitney U, and McNemar tests, and the area under the curve (AUC) of the receiver-operating characteristics (ROC) were used in the statistical analysis. Results: In the GEPNEN group, NETest was significantly higher (34.4 ± 1.8, p < 0.0001) in disease-positive patients than in patients with NED (10.5 ± 1, p < 0.0001), colon cancer patients (18 ± 4, p < 0.0004), and controls (7 ± 0.5, p < 0.0001). Sensitivity for detecting disease compared to controls was 89% and specificity was 94%. NETest levels were increased in G2 vs. G1 (39 ± 3 vs. 32 ± 2, p = 0.02) and correlated with stage (localized: 26 ± 2 vs. regional/distant: 40 ± 3, p = 0.0002) and progression (55 ± 5 vs. 34 ± 2 in stable disease, p = 0.0005). In the BPNEN group, diagnostic sensitivity was 100% and levels were significantly higher in patients with bronchopulmonary carcinoids (BPC; 30 ± 1.3) who had IPD than in controls (7 ± 0.5, p < 0.0001), patients with NED (24.1 ± 1.3, p < 0.005), and NSCLC patients (17 ± 3, p = 0.0001). NETest levels were higher in patients with poorly differentiated BPNEN (LCNEC + SCLC; 59 ± 7) than in those with BPC (30 ± 1.3, p = 0.0005) or progressive disease (57.8 ± 7), compared to those with stable disease (29.4 ± 1, p < 0.0001). The AUC for differentiating disease from controls was 0.87 in the GEPNEN group and 0.99 in BPC patients (p < 0.0001). Matched CgA analysis was performed in 178 patients. In the GEPNEN group (n = 135), NETest was significantly more accurate for detecting disease (99%) than CgA positivity (53%; McNemar...