Integrated (18)F-FDG PET/CT and perfusion CT of primary colorectal cancer: effect of inter- and intraobserver agreement on metabolic-vascular parameters.

OBJECTIVE: The purpose of this article is to assess the effect of observers on combined metabolic-vascular parameters in colorectal cancer. SUBJECTS AND METHODS: Twenty-five prospective patients (12 men and 13 women; mean age, 66.9 years) with proven primary colorectal adenocarcinoma underwent integrated (18)F-FDG PET/perfusion CT to assess tumor metabolism (mean and maximum standardized uptake value [SUV(mean) and SUV(max), respectively]) and vascularization (blood flow [BF], blood volume [BV], permeability surface-area product, and standardized perfusion value). Intra- and interobserver agreement for PET, perfusion CT, and combined metabolic-flow parameters were determined by Bland-Altman statistics and intraclass correlation coefficients (ICCs). RESULTS: The mean tumor size was 3.8 ± 1.6 cm; there were five stage IA/B, six stage IIA/B, eight stage IIIA/B, and six stage IV tumors. Intra- and interobserver agreement for individual parameters was fair to good, with mean differences between observers of -0.74 for SUV(max), -0.16 for SUV(mean), 9.72 for BF, 0.15 for BV, -0.76 for permeability surface-area product, and 0.09 for standardized perfusion value. ICCs were 0.44-0.99 and 0.38-0.89 for intra- and interobserver agreement, respectively. Interobserver agreement was variable for combined metabolic-flow parameters but better for metabolic-flow difference than for metabolic-flow ratio: ICCs were 0.69-0.88 for the metabolic-flow difference and 0.44-0.94 for the metabolic-flow ratio. CONCLUSION: Combined parameters to assess the metabolic-flow relationship are influenced by observer variation. Intra- and interobserver agreement are better for the metabolic-flow differences than for the ratios, suggesting that metabolic-flow differences may be a more robust parameter for clinical practice.

Assessment of the metabolic flow phenotype of primary colorectal cancer: correlations with microvessel density are influenced by the histological scoring method.

OBJECTIVES: To investigate how the histological scoring of microvessel density affects correlations between integrated (18)F-FDG-PET/perfusion CT parameters and CD105 microvessel density. METHODS: A total of 53 patients were enrolled from 2007 to 2010. Integrated (18)F-FDG-PET/perfusion CT was successful in 45 patients, 35 of whom underwent surgery without intervening treatment. Tumour SUV(max), SUV(mean) and regional blood flow (BF) were derived. Immunohistochemical staining for CD105 expression and analysis were performed for two hot spots, four hot spots and the Chalkley method. Correlations between metabolic flow parameters and CD105 expression were assessed using Spearman's rank correlation. RESULTS: Mean (SD) for tumour size was 38.5 (20.5) mm, for SUV(max), SUV(mean) and BF it was 19.1 (4.5), 11.6 (2.5) and 85.4 (40.3) mL/min/100 g tissue, and for CD105 microvessel density it was 71.4 (23.6), 66.8 (22.9) and 6.18 (2.07) for two hot spots, four hot spots and the Chalkley method, respectively. Positive correlation between BF and CD105 expression was modest but higher for Chalkley than for four hot spots analysis (r = 0.38, P = 0.03; r = 0.33, P = 0.05, respectively). There were no significant correlations between metabolic parameters (SUV(max) or SUV(mean)) and CD105 expression (r = 0.08-0.22, P = 0.21-0.63). CONCLUSIONS: The histological analysis method affects correlations between tumour CD105 expression and BF but not SUV(max) or SUV(mean). KEY POINTS: • FDG-PET/perfusion CT offers new surrogate biomarkers of angiogenesis. • Microvessel density scoring influences histopathological correlations with CT blood flow. • Highest correlations were found with the Chalkley analysis method. • Correlations between SUV and CD105 are not affected by the scoring method.

Development of an electronic web-based software for the management of colorectal cancer target referral patients.

In response to concern about lengthy waiting times for cancer treatment in the UK, the Department of Health introduced 'the colorectal cancer target referral scheme' to improve the referral process for suspected cancer. A user-centred web-based intranet software was developed reflecting the core work of the multi-disciplinary cancer team and the patient journey. The method used was primarily based on the concept of involving the end users (clinicians, nurses, administration staff) in the process of problem definition, software design, formative evaluation, development and implementation, from the very beginning, to ensure its relevance, functionality, and effectiveness. This software improved the interdisciplinary communication among doctors. All patients met the government waiting targets and proved to be a facilitative tool for audit, research and further prospective assessment of our service. Implementing a functional software design is mandatory for the management of target referral patients.

Commercial software upgrades may significantly alter Perfusion CT parameter values in colorectal cancer.

OBJECTIVE: To determine how commercial software platform upgrades impact on derived parameters for colorectal cancer. MATERIALS AND METHODS: Following ethical approval, 30 patients with suspected colorectal cancer underwent Perfusion CT using integrated 64 detector PET/CT before surgery. Analysis was performed using software based on modified distributed parameter analysis (Perfusion software version 4; Perfusion 4.0), then repeated using the previous version (Perfusion software version 3; Perfusion 3.0). Tumour blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface area product (PS) were determined for identical regions-of-interest. Slice-by-slice and 'whole tumour' variance was assessed by Bland-Altman analysis. RESULTS: Mean BF, BV and PS was 20.4%, 59.5%, and 106% higher, and MTT 14.3% shorter for Perfusion 4.0 than Perfusion 3.0. The mean difference (95% limits of agreement) were +13.5 (-44.9 to 72.0), +2.61 (-0.06 to 5.28), -1.23 (-6.83 to 4.36), and +14.2 (-4.43 to 32.8) for BF, BV, MTT and PS respectively. Within subject coefficient of variation was 36.6%, 38.0%, 27.4% and 60.6% for BF, BV, MTT and PS respectively indicating moderate to poor agreement. CONCLUSION: Software version upgrades of the same software platform may result in significantly different parameter values, requiring adjustments for cross-version comparison.