Correlation of the ADC values assessed by diffusion-weighted MRI and 18F­FDG PET/ CT SUV in patients with lung cancer

Background: Diffusion-weighted magnetic resonance imaging (DW-MRI) provides information on the cellularity and movement of water molecules in tissues and 18F­fluorodeoxyglucose (18F­FDG) positron emission tomography/computed tomography (18F­FDG PET/CT) assesses cellular glucose metabolism, however both variables are related to tumour aggressiveness. The aim of this study is to investigate the potential correlation of the apparent diffusion coefficient (ADC) assessed by diffusion-weighted MRI (DWI) and glucose metabolism determined by the standardized uptake value (SUV) calculated from 18F­FDG PET/CT data in non-small cell lung cancer (NSCLC) with the occurrence of metastasis to the lymph nodes. Methods: 18F­FDG PET/CT and DWI (TR/TE, 1800/93 ms; b-values, 0 and 600 s/mm2) were performed in 37 consecutive patients with histologically verified NSCLC. SUVmax was calculated based on the PET-CT data. The minimum ADC (ADCmin) was determined by placing a region-of-interest (ROI) covering the entire tumou. Results of 18F­FDG PET/CT and DWI were compared on a per-patient basis. Pearson's correlation coefficient was used for statistical analysis. Results: Correlation analysis of the ADCmin and SUVmax revealed that the inverse correlation was good for all the masses (p< 0.001) and the lymph nodes (p < 0.001) for each histological subtype, for both adenocarcinomas (p < 0.001) lymph nodes (p = 0.005) and squamous cell carcinomas (p < 0.001). No significant correlation was found in the comparison of the ADCmin and SUVmax of the lymph nodes for squamous cell carcinomas (p = 0.066). Conclusions: This study verified the relationship between the SUVmax and the ADCmin in NSCLC. The significant inverse correlation of these two quantitative imaging approaches highlights the association between metabolic activity and tumour cellularity. Therefore, DWI with ADC measurement might represent a new biomarker in NSCLC.

Tumor size assessment of invasive breast cancers: which pathological features affect MRI-pathology agreement?

Background: Preoperative assessment of tumor size is important in breast cancer treatment planning, especially in breast conservation surgeries. The use of the Magnetic Resonance Imaging (MRI) is increasing among patients with newly diagnosed breast cancers. However, some pathological features can overestimate the measurement of tumor size by MRI, increasing mastectomy rates. The objective is to evaluate which pathological features may affect the agreement between MRI and pathologic tumor size on invasive breast carcinomas. Methods: Eighty seven patients with breast cancer who underwent preoperative breast MRI were retrospectively evaluated. The main tumor size measured by MRI was compared with pathology (gold standard) and concordance was defined as a greater diameter difference of less than 10 mm. Results: There was MRI-pathology concordance in 60 cases (69.0%), MRI overestimated tumor size in 21 (24.1%) and underestimated in 6 (6.9%). After multivariate analysis, only associated ductal carcinoma in situ (DCIS) remained significantly related to overestimation of tumor size on MRI (OR: 9.00; 95% IC:1.13-71.87; p = 0.038). Conclusion: There was good correlation between tumor size evaluation on MRI and pathology. The presence of associated DCIS was the only pathological parameter associated with size overestimation on MRI

CT assessment of nutritional status and lean body mass in gastric and esophageal cancer

Background: Malnutrition is common in patients with gastric and esophageal tumors, and is predominantly associated with loss of lean body mass. Adequate assessment of preoperative nutritional status is essential for prognostication and multidisciplinary treatment planning. The aim of this study was to ascertain whether anthropometric nutritional assessment correlates with computed tomography (CT) measured lean body mass in patients with gastric and/or esophageal cancer. Methods: This was a retrospective analysis of abdominal CT images and anthropometric nutritional assessments. The anthropometric parameters of interest were weight, height, body mass index, mid-upper arm circumference, triceps skinfold thickness, mid-arm muscle circumference, and nutritional diagnosis. The lean muscle mass area was calculated from axial-view CT images of the abdomen at the level of L3 and corrected by height for calculation of the lean mass index. Values below 55.4 cm2 /m2 for males and 38.9 cm2 /m2 for females were defined as low lean body mass. Results: The sample included 70 patients, of whom 67.1% were men. The mean lean body mass index assessed by computed tomography was 47.8 cm2 /m2 (range, 29.2­78.6cm2 /m2), with 54.3% of patients being classified as having low lean body mass. When classified by mid-arm muscle circumference, 74.2% of patients classified as undernourished had low lean body mass on CT, compared to 40.0% of patients classified as well-nourished (sensitivity 62.2%, specificity 72.4%, accuracy 66.7%). Conclusions: A substantial portion of patients with gastric and/or esophageal cancer exhibited low lean body mass on computed tomography. Anthropometric evaluation has limited capacity to identify these patients. Among the tested anthropometric parameter, mid-arm muscle circumference showed the best agreement with CT-measured lean body mass