The 7th lung cancer TNM classification and staging system:Review of the changes and implications

Lung cancer is the most common cause of death from cancer in males, accounting for more than 1.4 million deaths in 2008. It is a growing concern in China, Asia and Africa as well. Accurate staging of the disease is an important part of the management as it provides estimation of patient’s prognosis and identifies treatment sterategies. It also helps to build a database for future staging projects. A major revision of lung cancer staging has been announced with effect from January 2010. The new classification is based on a larger surgical and non-surgical cohort of patients, and thus more accurate in terms of outcome prediction compared to the previous classification. There are several original papers regarding this new classification which give comprehensive description of the methodology, the changes in the staging and the statistical analysis. This overview is a simplified description of the changes in the new classification and their potential impact on patients’ treatment and prognosis

Iterative reconstruction can permit the use of lower x-ray tube current in CT coronary artery calcium scoring

OBJECTIVE: CT coronary artery calcium scoring (CACS) is additive to traditional risk factors for predicting future cardiac events but is associated with relatively high radiation doses. We assessed the feasibility of CACS radiation dose reduction using a lower tube current and iterative reconstruction (IR). METHODS: Artificial noise was added to the raw data from 27 CACS studies from patients who were symptomatic to simulate lower tube current scanning (75, 50 and 25% original current). All studies were performed on the same CT scanner at 120 kVp. Data were reconstructed using filtered back projection [Quantum Denoising Software (QDS+)] and IR [adaptive iterative dose reduction three dimensional mild, standard and strong]. Agatston scores were independently measured by two readers. CACS percentile risk scores were calculated. RESULTS: At 75, 50 and 25% tube currents, all adaptive iterative dose reduction (AIDR) reconstructions decreased image noise relative to QDS+ (p < 0.05). All AIDR reconstructions resulted in small reductions in Agatston score relative to QDS+ at the standard tube current (p < 0.05). Agatston scores increased with QDS+ at 75, 50 and 25% tube current (p < 0.05), whereas no significant change was observed with AIDR mild at any tested tube current. No difference in the percentile risk score with AIDR mild at any tube current occurred compared with QDS+ at standard tube current (p > 0.05). Interobserver agreement for AIDR mild remained excellent even at 25% tube current (intraclass correlation coefficient 0.997). CONCLUSION: Up to 75% reduction in CACS tube current is feasible using AIDR mild. ADVANCES IN KNOWLEDGE: AIDR mild IR permits low tube current CACS whilst maintaining excellent intraobserver and interobserver variability and without altering risk classification

A multimodality cross-validation study of cardiac perfusion using MR and CT.

Modern advances in magnetic resonance (MR) and computed tomography (CT) perfusion imaging techniques have developed methods for myocardial perfusion assessment. However, individual imaging techniques present limitations that are possible to be surpassed by a multimodality cross-validation of perfusion imaging and analysis. We calculated the absolute myocardial blood flow (MBF) in MR using a Fermi function and the transmural perfusion ratio (TPR) in CT perfusion data in a patient with coronary artery disease (CAD). Comparison of MBF and TPR results showed good correlation emphasizing a promising potential to continue our multimodality perfusion assessment in a cohort of patients with CAD

Diagnostic performance of myocardial blood flow quantification in coronary artery disease by magnetic resonance.

Background Mathematical modelling of magnetic resonance (MR) perfusion imaging data allows myocardial blood flow (MBF) quantification and can potentially improve the diagnosis and prognostication of obstructive coronary artery disease (CAD). The diagnostic performance of distributed parameter (DP) modelling in detecting obstructive CAD has not yet been assessed. A model assessment in per vessel against per patient analysis has not been fully assessed yet in a single MR study. This work compares the diagnostic performance of DP modelling against the standard Fermi modelling, for the detection of obstructive CAD, in per vessel against per patient analysis. Methods After informed consent, a pilot cohort of 28 subjects with known or suspected CAD underwent adenosine stress-rest magnetic resonance perfusion imaging at 3T. Data were analysed using Fermi and DP modelling against invasive coronary angiography and fractional flow reserve, acquired in all subjects. Obstructive CAD was defined as luminal stenosis of ≥70% alone, or luminal stenosis ≥50% and fractional flow reserve ≤0.80. Results On ROC analysis, the diagnostic performance of all methods was improved in per patient analysis. DP modelling outperformed the standard Fermi model, in per vessel and per patient analysis. In per patient analysis, DP modelling-derived MBF at stress demonstrated the highest sensitivity and specificity (0.96, 0.92) in detecting obstructive CAD, against Fermi modelling (0.78, 0.88) and visual assessments (0.79, 0.88), respectively. Conclusions DP modelling consistently outperformed Fermi modelling and showed that it may have merit for robustly stratifying patients with at least one vessel with obstructive CA

Measurement of myocardial blood flow by cardiovascular magnetic resonance perfusion: comparison of distributed parameter and Fermi models with single and dual bolus

Background Mathematical modeling of cardiovascular magnetic resonance perfusion data allows absolute quantification of myocardial blood flow. Saturation of left ventricle signal during standard contrast administration can compromise the input function used when applying these models. This saturation effect is evident during application of standard Fermi models in single bolus perfusion data. Dual bolus injection protocols have been suggested to eliminate saturation but are much less practical in the clinical setting. The distributed parameter model can also be used for absolute quantification but has not been applied in patients with coronary artery disease. We assessed whether distributed parameter modeling might be less dependent on arterial input function saturation than Fermi modeling in healthy volunteers. We validated the accuracy of each model in detecting reduced myocardial blood flow in stenotic vessels versus gold-standard invasive methods. Methods Eight healthy subjects were scanned using a dual bolus cardiac perfusion protocol at 3T. We performed both single and dual bolus analysis of these data using the distributed parameter and Fermi models. For the dual bolus analysis, a scaled pre-bolus arterial input function was used. In single bolus analysis, the arterial input function was extracted from the main bolus. We also performed analysis using both models of single bolus data obtained from five patients with coronary artery disease and findings were compared against independent invasive coronary angiography and fractional flow reserve. Statistical significance was defined as two-sided P value <0.05. Results Fermi models overestimated myocardial blood flow in healthy volunteers due to arterial input function saturation in single bolus analysis compared to dual bolus analysis (P < 0.05). No difference was observed in these volunteers when applying distributed parameter-myocardial blood flow between single and dual bolus analysis. In patients, distributed parameter modeling was able to detect reduced myocardial blood flow at stress (<2.5 mL/min/mL of tissue) in all 12 stenotic vessels compared to only 9 for Fermi modeling. Conclusions Comparison of single bolus versus dual bolus values suggests that distributed parameter modeling is less dependent on arterial input function saturation than Fermi modeling. Distributed parameter modeling showed excellent accuracy in detecting reduced myocardial blood flow in all stenotic vessels