Mitral prolapsing volume is associated with increased cardiac dimensions in patients with mitral annular disjunction.

INTRODUCTION: In patients with mitral annular disjunction (MAD), it can be difficult to assess the severity of mitral regurgitation (MR), as they present with a prolapsing volume (i.e. volume resulting from mitral valve prolapse, blood volume shift) rather than a regurgitant jet. The influence of the mitral prolapsing volume (MPV) on cardiac dimensions is unknown. We hypothesised that the severity of MR is underestimated in these patients. Our aim was to measure MPV and to investigate its influence on cardiac dimensions in patients with MAD. METHODS: We retrospectively included 131 consecutive patients with MAD from our institution's echocardiographic database. Transthoracic echocardiography was used to assess MPV. Additionally, we established a control group of 617 consecutive patients with degenerative mitral valve disease and performed propensity score matching. RESULTS: Median MPV in the MAD group was 12 ml. MPV was an independent predictor for left ventricular end-diastolic (LVEDD) and end-systolic diameter (LVESD) and left atrial volume (all p < 0.001). In patients with large prolapsing volumes (> 15 ml), LVEDD (56 ± 6 mm vs 51 ± 6 mm, p < 0.001), LVESD [38 mm (34-41) vs 34 mm (31-39), p < 0.01] and left atrial volume [105 ml (86-159) vs 101 ml (66-123), p = 0.04] were significantly increased compared to matched patients with degenerative mitral valve disease and similarly assessed severity of MR. CONCLUSION: Due to a volume shift based on the MPV rather than an actual regurgitant jet, MR severity cannot be assessed adequately in MAD patients. Increased MPV induces ventricular and atrial enlargement. These findings warrant future studies to focus on MPV as an additional parameter for assessment of the severity of MR in MAD patients.

Multidisciplinary decision-making in mitral valve disease: the mitral valve heart team.

BACKGROUND: Although decision-making using the heart-team approach is apparently intuitive and has a class I recommendation in most recent guidelines, supportive data is still lacking. The current study aims to demonstrate the individualised clinical pathway for mitral valve disease patients and to evaluate the outcome of all patients referred to the dedicated mitral valve heart team. METHODS: All patients who were evaluated for mitral valve pathology with or without concomitant cardiac disease between 1 January 2016 and 31 December 2016 were prospectively followed and included. Patients were evaluated, and a treatment strategy was determined by the dedicated mitral valve heart team. RESULTS: One hundred and fifty-eight patients were included; 67 patients were treated surgically (isolated and concomitant surgery), 20 by transcatheter interventions and 71 conservatively. Surgically treated patients had a higher 30-day mortality rate (4.4%), which decreased when specified to a dedicated surgeon (1.7%) and in primary, elective cases (0%). This was also observed for major adverse events within 30 days. Residual mitral regurgitation >grade 2 was more frequent in the catheter-based intervention group (23.5%) compared to the surgical group (4.8%). CONCLUSION: In conclusion, the implementation of a multidisciplinary heart team for mitral valve disease is a valuable approach for the selection of patients for different treatment modalities. Our research group will focus on a future comparative study using historical cohorts to prove the potential superiority of the dedicated multidisciplinary heart-team approach.

TNM-Classification for Lung Cancer: From the 7(th) to the 8(th) Edition.

Most tumors are staged according to the Tumor-Node-Metastasis (TNM) classification. For lung cancer a new edition was introduced in 2009 and generally applied since 2010. This 7(th) TNM-classification is based on a large, international retrospective database. Important changes were made regarding the T, N, M factors and specific subcategories were added. However, this 7(th) edition is still purely based on anatomical information. Other prognosticators such as laboratory results, histology, tumor markers and molecular genetic factors are not yet considered. To prepare the 8(th) TNM classification a prospective database developed by the International Association for the Study of Lung Cancer (IASLC), is currently enrolling patients from all continents. In this way, more precise and reliable data will become available on specific subdivisions of the T, N and M factors. If proven to be prognostically valid, other parameters will be included as histology, demographic data and specific biochemical and molecular predictive and prognostic factors. All centers with a large experience in thoracic oncology are encouraged to participate in this prospective database.

Quality of life after lung cancer surgery: a review.

The long-term goals of lung cancer surgery include cancer control, survival and quality of life (QoL). In a patient population with a high mortality rate, evaluation and preservation of QoL after treatment is imperative. Lung cancer patients already have a significant lower QoL compared to an age-matched healthy population with significant impairment in physical and emotional functioning. Lung cancer surgery causes further deterioration of QoL, especially in the first 3 to 6 months after surgery. While some studies suggest that QOL returns to baseline levels at 6 to 9 months postoperatively, others report that QOL is still significantly impaired at 6 and 12 months after surgery. Age, extent of surgery, preoperative lung function, access technique, and adjuvant treatment may all influence postoperative QoL. This review presents the basic concepts of QoL research, several commonly used QoL measurement instruments, and a summary of the available data on post-lung cancer surgery QoL.

Distinct angiogenic and non-angiogenic growth patterns of lung metastases from renal cell carcinoma.

AIMS: We have recently evaluated a classification of non-small-cell lung cancer based upon the presence of an angiogenic or a non-angiogenic growth pattern. The aim of the present study was to test the hypothesis that lung metastases of clear cell renal cell carcinoma (RCC) can grow without eliciting angiogenesis and give rise to the same set of growth patterns. METHODS AND RESULTS: Tissue sections of 24 patients with lung metastases from clear cell RCC were analysed. Haematoxylin and eosin and reticulin staining were performed to evaluate growth pattern. Double-labelling with antibodies to CD34 and proliferating cell nuclear antigen (PCNA) was performed to determine the endothelial cell proliferation fraction (ECPF) and the microvessel density (MVD). Three growth patterns were observed. In the destructive growth pattern (54%), the architecture of the lung was not preserved. In the alveolar (33%) and interstitial growth patterns (13%), the normal lung parenchyma was preserved within the metastases. MVD was higher in the destructive than in the alveolar growth pattern (P = 0.009). ECPF was higher in the destructive (mean 31.1 +/- 22.7%, median 30.0) than in the alveolar growth pattern (mean 3.6 +/- 2.8%, median 3.2; P = 0.005). CONCLUSIONS: The present study demonstrates that highly angiogenic primary tumours can give rise to non-angiogenic metastases. This type of metastasis may be resistant to antiangiogenic therapy.

Prognostic value of nonangiogenic and angiogenic growth patterns in non-small-cell lung cancer.

An essential prerequisite of nonangiogenic growth appears to be the ability of the tumour to preserve the parenchymal structures of the host tissue. This morphological feature is visible on a routine tissue section. Based on this feature, we classified haematoxylin and eosin-stained tissue sections from 279 patients with non-small-cell lung cancer into three growth patterns: destructive (angiogenic; n=196), papillary (intermediate; n=38) and alveolar (nonangiogenic; n=45). A Cox multiple regression model was used to test the prognostic value of growth patterns together with other relevant clinicopathological factors. For overall survival, growth pattern (P=0.007), N-status (P=0.001), age (P=0.020) and type of operation (P=0.056) were independent prognostic factors. For disease-free survival, only growth pattern (P=0.007) and N-status (P<0.001) had an independent prognostic value. Alveolar (hazard ratio=1.825, 95% confidence interval=1.117-2.980, P=0.016) and papillary (hazard ratio=1.977, 95% confidence interval=1.169-3.345, P=0.011) growth patterns were independent predictors of poor prognosis. The proposed classification has an independent prognostic value for overall survival as well as for disease-free survival, providing a possible explanation for survival differences of patients in the same disease stage.