Which patients are prone to undergo disproportionate recurrent CT imaging and should we worry?

Purpose: To identify the spectrum of patients who undergo disproportionate recurrent computed tomography (CT) imaging, and to explore the cumulative effects of radiation exposure and intravenously injected contrast agents in these patients. Methods: This retrospective study investigated all patients who had undergone 40 or more CT scans at a tertiary care center between 2007–2017. Results: Fifty-six patients who had undergone a median of 47 (range: 40–92) CT scans were included. The main reason for CT scanning in all patients was oncological, and 55 patients (98.2 %) had metastatic disease. Twenty-six patients (45.6) had received chemotherapy, 35 (62.5 %) radiation therapy, 38 (67.9 %) targeted therapy, 12 (21.4 %) liver tumor microwave ablation, 44 (78.6 %) major surgery, and 34 (60.7 %) had participated in a therapeutic trial. Mean cumulative effective dose was 187.4 mSv (range: 120.7–278.4 mSv). Median estimated radiation-induced lifetime attributable risk (LAR) of cancer incidence was 1.0 % (range: 0.20–2.36 %). Mean estimated radiation-induced LAR of cancer mortality was 0.68 % (range: 0.18–1.37 %). Mean cumulative volume of intravenously injected iomeprol was 2339 mL (range: 540−3605 mL). Three patients (5.4 %) had developed severely decreased kidney function (estimated glomerular filtration rate between 15 and 29 mL/min per 1.73 m² for at least 3 months). Conclusion: Patients with metastatic disease who experience a relatively long survival may be prone to undergo disproportionate recurrent CT imaging. The non-negligible CT radiation-induced cancer risk and mortality should be taken into account in these patients, while the effect of cumulatively administered CT contrast agents on kidney function requires further investigation

Human stromal cells are required for an anti-breast cancer effect of zoledronic acid

Previous studies suggested that bisphosphonate zoledronic acid exerts an antitumor effect by interacting with the microenvironment. In this study, we aimed to elucidate the mechanism behind the anti-breast cancer effect of zoledronic acid.Here we showed that zoledronic acid did not influence in vitro human breast cancer cell survival, but did affect human stromal cell survival. Breast cancer cell death in co-culture with stromal cells was analyzed in vitro by fluorescent microscopy and flowcytometry analysis. In co-culture, the addition of stromal cells to breast cancer cells induced tumor cell death by zoledronic acid, which was abolished by transforming growth factor (TGF)-beta. In the in vivo chicken chorioallantoic membrane model, zoledronic acid reduced the breast cancer cells fraction per tumor only in the presence of human stromal cells. Zoledronic acid decreased TGF-beta excretion by stromal cells and co-cultures. Moreover, supernatant of zoledronic acid treated stromal cells reduced phospho-Smad2 protein levels in breast cancer cells. Thus, zoledronic acid exerts an anti-breast cancer effect via stromal cells, accompanied by decreased stromal TGF-beta excretion and reduced TGF-beta signaling in cancer cells.</p

The analysis of longitudinal quality of life measures with informative drop-out: a pattern mixture approach

The analysis of longitudinal health-related quality of life measures (HRQOL) can be seriously hampered due to informative drop-out. Random effects models assume Missing At Random and do not take into account informative drop-out. We therefore aim to correct the bias due to informative drop-out. Analyses of data from a trial comparing standard-dose and high-dose chemotherapy for patients with breast cancer with respect to long-term impact on HRQOL will serve as illustration. The subscale Physical Function (PF) of the SF36 will be used. A pattern mixture approach is proposed to account for informative drop-out. Patterns are defined based on events related to HRQOL, such as death and relapse. The results of this pattern mixture approach are compared to the results of the commonly used random effects model. The findings of the pattern mixture approach are well interpretable, and different courses over time in different patterns are distinguished. In terms of estimated differences between standard dose and high dose, the results of both approaches are slightly different, but have no consequences for the clinical evaluation of both doses. Under the assumption that drop-out is at random within the patterns, the pattern mixture approach adjusts the estimates to a certain degree. This approach accounts in a relatively simple way for informative drop-out

Positron emission tomography of tumour [18F]fluoroestradiol uptake in patients with acquired hormone-resistant metastatic breast cancer prior to oestradiol therapy

Purpose Whereas anti-oestrogen therapy is widely applied to treat oestrogen receptor (ER) positive breast cancer, paradoxically, oestrogens can also induce tumour regression. Upregulation of ER expression is a marker for oestrogen hypersensitivity. We, therefore, performed an exploratory study to evaluate positron emission tomography (PET) with the tracer 16 alpha-[F-18] fluoro-17 beta-oestradiol (F-18-FES) as potential marker to select breast cancer patients for oestradiol therapy. Methods Eligible patients had acquired endocrine-resistant metastatic breast cancer that progressed after >= 2 lines of endocrine therapy. All patients had prior ER-positive histology. Treatment consisted of oestradiol 2 mg, three times daily, orally. Patients underwent F-18-FES-PET/CT imaging at baseline. Tumour F-18-FES-uptake was quantified for a maximum of 20 lesions and expressed as maximum standardised uptake value (SUVmax). CT-scan was repeated every 3 months to evaluate treatment response. Clinical benefit was defined as time to radiologic or clinical progression >= 24 weeks. Results F-18-FES uptake, quantified for 255 lesions in 19 patients, varied greatly between lesions (median 2.8; range 0.6-24.3) and between patients (median 2.5; range 1.1-15.5). Seven (37 %) patients experienced clinical benefit of oestrogen therapy, eight progressed (PD), and four were non-evaluable due to side effects. The positive and negative predictive value PPV/NPV) of F-18-FES-PET for response to treatment were 60 % (95 % CI: 31-83 %) and 80 % (95 % CI: 38-96 %), respectively, using SUVmax >1.5. Conclusion F-18-FES-PET may aid identification of patients with acquired antihormone resistant breast cancer that are unlikely to benefit from oestradiol therapy

Mitigation of noise-induced bias of PET radiomic features

INTRODUCTION: One major challenge in PET radiomics is its sensitivity to noise. Low signal-to-noise ratio (SNR) affects not only the precision but also the accuracy of quantitative metrics extracted from the images resulting in noise-induced bias. This phantom study aims to identify the radiomic features that are robust to noise in terms of precision and accuracy and to explore some methods that might help to correct noise-induced bias. METHODS: A phantom containing three 18F-FDG filled 3D printed inserts, reflecting heterogeneous tracer uptake and realistic tumor shapes, was used in the study. The three different phantom inserts were filled and scanned with three different tumor-to-background ratios, simulating a total of nine different tumors. From the 40-minute list-mode data, ten frames each for 5 s, 10 s, 30 s, and 120 s frame duration were reconstructed to generate images with different noise levels. Under these noise conditions, the precision and accuracy of the radiomic features were analyzed using intraclass correlation coefficient (ICC) and similarity distance metric (SDM) respectively. Based on the ICC and SDM values, the radiomic features were categorized into four groups: poor, moderate, good, and excellent precision and accuracy. A "difference image" created by subtracting two statistically equivalent replicate images was used to develop a model to correct the noise-induced bias. Several regression methods (e.g., linear, exponential, sigmoid, and power-law) were tested. The best fitting model was chosen based on Akaike information criteria. RESULTS: Several radiomic features derived from low SNR images have high repeatability, with 68% of radiomic features having ICC ≥ 0.9 for images with a frame duration of 5 s. However, most features show a systematic bias that correlates with the increase in noise level. Out of 143 features with noise-induced bias, the SDM values were improved based on a regression model (53 features to excellent and 67 to good) indicating that the noise-induced bias of these features can be, at least partially, corrected. CONCLUSION: To have a predictive value, radiomic features should reflect tumor characteristics and be minimally affected by noise. The present study has shown that it is possible to correct for noise-induced bias, at least in a subset of the features, using a regression model based on the local image noise estimates

(89)Zr-Onartuzumab PET imaging of c-MET receptor dynamics

PURPOSE: c-MET and its ligand hepatocyte growth factor are often dysregulated in human cancers. Dynamic changes in c-MET expression occur and might predict drug efficacy or emergence of resistance. Noninvasive visualization of c-MET dynamics could therefore potentially guide c-MET-directed therapies. We investigated the feasibility of (89)Zr-labelled one-armed c-MET antibody onartuzumab PET for detecting relevant changes in c-MET levels induced by c-MET-mediated epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor erlotinib resistance or heat shock protein-90 (HSP90) inhibitor NVP-AUY-922 treatment in human non-small-cell lung cancer (NSCLC) xenografts. METHODS: In vitro membrane c-MET levels were determined by flow cytometry. HCC827ErlRes, an erlotinib-resistant clone with c-MET upregulation, was generated from the exon-19 EGFR-mutant human NSCLC cell line HCC827. Mice bearing HCC827 and HCC827ErlRes tumours in opposite flanks underwent (89)Zr-onartuzumab PET scans. The HCC827-xenografted mice underwent (89)Zr-onartuzumab PET scans before treatment and while receiving biweekly intraperitoneal injections of 100 mg/kg NVP-AUY-922 or vehicle. Ex vivo, tumour c-MET immunohistochemistry was correlated with the imaging results. RESULTS: In vitro, membrane c-MET was upregulated in HCC827ErlRes tumours by 213 ± 44% in relation to the level in HCC827 tumours, while c-MET was downregulated by 69 ± 9% in HCC827 tumours following treatment with NVP-AUY-922. In vivo, (89)Zr-onartuzumab uptake was 26% higher (P < 0.05) in erlotinib-resistant HCC827ErlRes than in HCC827 xenografts, while HCC827 tumour uptake was 33% lower (P < 0.001) following NVP-AUY-922 treatment. CONCLUSION: The results show that (89)Zr-onartuzumab PET effectively discriminates relevant changes in c-MET levels and could potentially be used clinically to monitor c-MET status

Mass spectrometric quantification of urinary 6-sulfatoxymelatonin:age-dependent excretion and biological variation

Objectives: Regulators of circadian rhythm, including melatonin, influence fundamental biological processes. Measuring the melatonin metabolite 6-sulfatoxymelatonin in urine can estimate melatonin production. 6-sulfatoxymelatonin is mainly analyzed by immunoassays, but these methods are hampered by cross-reactivity and poor reproducibility when used to analyze small molecules. Therefore, we validated a high-throughput liquid chromatography with tandem mass spectrometry (LC-MS/MS) method to quantify 6-sulfatoxymelatonin in urine. We evaluated age-dependent 24-h excretion of 6-sulfatoxymelatonin into urine and the biological variation of urinary excretion in healthy individuals. Methods: The online solid phase extraction method combined with LC-MS/MS was validated according to international guidelines, and used to measure the excretion of 6-sulfatoxymelatonin into urine of 240 healthy individuals. Biological variation of 6-sulfatoxymelatonin excretion was examined in 10 healthy individuals. Results: Urinary 6-sulfatoxymelatonin results were well within the validation criteria (interassay coefficient of variation: Conclusions: This MS-based method enables straightforward, reproducible, and sensitive quantification of 6-sulfatoxymelatonin in urine. Urinary 6-sulfatoxymelatonin levels decreased with age. Biological variation of 6-sulfatoxymelatonin excretion into urine was high between subjects and lower within subjects, indicating that repeated measurements of 6-sulfatoxymelatonin in 24-h urine are needed in future studies