Immuno-PET imaging for non-invasive assessment of cetuximab accumulation in non-small cell lung cancer.

BACKGROUNDS: Overexpression of epidermal growth factor receptor (EGFR) has been established as a valid therapeutic target of non-small cell lung cancer (NSCLC). However, the clinical benefit of cetuximab as an EGFR-targeting drug is still controversial, partially due to the lack of effective means to identify suitable patients. This study aimed to investigate the potential of radiolabeled cetuximab as a non-invasive tool to predict cetuximab accumulation in NSCLC tumor xenografts with varying EGFR expression levels. METHODS: The NSCLC tumors in model mice were subjected to in vivo biodistribution study and positron emission tomography (PET) imaging 48 h after injection of either 111In- or 64Cu-labeled cetuximab. The EGFR expression levels of NSCLC tumors were determined by ex vivo immunoblotting. RESULTS: We found that tumors with high EGFR expression had significantly higher [111In]In-DOTA-cetuximab accumulation than tumors with moderate to low EGFR expression (P < 0.05). Strong correlations were found between [111In]In-DOTA-cetuximab tumor uptake and EGFR expression level (r = 0.893), and between [64Cu]Cu-DOTA-cetuximab tumor uptake with EGFR expression level (r = 0.915). PET imaging with [64Cu]Cu-DOTA-cetuximab allowed clear visualization of tumors. CONCLUSION: Our findings suggest that this immuno-PET imaging can be clinically translated as a tool to predict cetuximab accumulation in NSCLC cancer patients prior to cetuximab therapy.

Automated Bone Scan Index as Predictors of Survival in Prostate Cancer.

Prostate cancer (PCa) is the second most diagnosed cancer in men. Early diagnosis and right management of PCa is critical to reducing deaths; the life expectancy is the main factors to be considered in the management of PCa. Among patients who die from PCa, the incidence of skeletal involvement appears to be >85%. Bone scan (BS) is the most common method for monitoring bone metastases in patients with PCa. The extent of bone metastasis was also associated with patient survival until now there is no clinically useful technique for measuring bone tumors and includes this information in the risk assessment. An alternative approach is to calculate a BS index (BSI) and it has shown clinical significance as a prognostic imaging biomarker. Some computer-assisted diagnosis (CAD) systems have been developed to measure BSI and are now available. The aim of this study was to investigate automated BSI (aBSI) measurements as predictors' survival in PCa. Retrospectively cohort studied fifty patients with PCa who had undergone BS between January 2010 and December 2011 at our institution. All data collected was updated up to August 2016. CAD system analyzing BS images to automatically compute BSI measurements. Patients were stratified into three BSI categories BSI value 0, BSI value ≤1 and BSI value >1. Kaplan-Meier estimates of the survival function and the log-rank test were used to indicate a significant difference between groups stratified in accordance with the BSI values. A total of 35 subjects deaths were registered, with a median survival time 36 months after the follow-up BS of 5 years. Subjects with low aBSI value had longer overall survival in comparison with the other subjects (P = 0.004). aBSI measurements were shown to be a strong prognostic survival indicator in PCa; survival is poor in high-BSI value.

Evaluation of bone scan index change over time on automated calculation in bone scintigraphy.

OBJECTIVE: Bone scintigraphy (bone scan) is useful in detecting metastatic bone lesions through visual assessment of hot spots. A semi-quantitative analysis method that evaluates bone scan images has been eagerly anticipated. BONENAVI is software that enables automatic assessment of bone scan index (BSI). BSI is useful for stratifying cancer patients and monitoring their therapeutic response. The purpose of this study was to evaluate the BONENAVI reading in determining BSI and hot spots at different time intervals after radioisotope injection. METHODS: We evaluated 32 patients, including 22 males and 10 females. Ten patients had breast cancer, 20 patients had prostate cancer, and 2 had malignant pheochromocytoma. Patients were injected with 740 MBq of (99m)Tc-methylene diphosphonate and bone scintigraphy was performed at 2, 4, and 6 h after injection on each patient. The BSI and the number of hot spots were obtained from BONENAVI software. Bone scan images were also visually assessed to exclude false positives due to artifacts. Analyses were performed in all lesions, selected true lesions, segment based and cancer type based. Non-parametric statistical analyses for pairwise multiple group comparison were performed using Friedman test followed with post hoc analysis. RESULTS: The BSIs and the number of hot spots were significantly increased with time, with significant differences between each of time points (P < 0.001). Analysis of regional BSI (rBSI) and hot spot number changes of selected 15 true lesions also showed similar increase (P < 0.001). In general, the pelvic segment was the most prone to rBSI changes and the chest segment was the most prone to hot spot number changes. Visual assessment showed that BONENAVI diagnosed some typical artifacts as metastases (hot spots). CONCLUSION: BONENAVI reading of BSIs and hot spot numbers was highly affected by acquisition time. In serial or follow-up examinations (in particular, for monitoring therapeutic efficacy), acquisition time should be fixed for each patient. Cautious interpretation should be made on segments with high physiological uptake. BONENAVI reading was prone to misinterpretation of artifacts. Visual assessment is necessary to rule out this possibility.