Molecular imaging with ¹⁸F-FDG PET has been proven useful in the management of colorectal cancer. ¹⁸F-FDG PET plays a pivotal role in staging before surgical resection of recurrent colorectal cancer and metastases, in the localization of recurrence in patients with an unexplained rise in serum carcinoembryonic antigen levels, and in the assessment of residual masses after treatment. Currently, there is increasing interest in the role of ¹⁸F-FDG PET beyond staging. The technique appears to have significant potential for the characterization of tumors and for the prediction of prognosis in the context of treatment stratification and early assessment of tumor response to therapy. This systematic review provides an overview of the literature on the value of ¹⁸F-FDG PET for monitoring and predicting the response to therapy in colorectal cancer. The review covers chemotherapy response monitoring in advanced colorectal cancer, monitoring of the effects of local ablative therapies, and preoperative radiotherapy and multimodality treatment response evaluation in primary rectal cancer. Given the added value of ¹⁸F-FDG PET for these indications, implementation in clinical practice and systematic inclusion in therapeutic trials to exploit the potential of ¹⁸F-FDG PET are warranted.

Purpose This review aims to provide insight into the factors that influence quantification of glucose metabolism by FDG PET images in oncology as well as their influence on repeated measures studies (i.e. treatment response assessment), offering improved understanding both for clinical practice and research. Methods Structural PubMed searches have been performed for the many factors affecting quantification of glucose metabolism by FDG PET. Review articles and references lists have been used to supplement the search findings. Results Biological factors such as fasting blood glucose level, FDG uptake period, FDG distribution and clearance, patient motion (breathing) and patient discomfort (stress) all influence quantification. Acquisition parameters should be adjusted to maximize the signal to noise ratio without exposing the patient to a higher than strictly necessary radiation dose. This is especially challenging in pharmacokinetic analysis, where the temporal resolution is of significant importance. The literature is reviewed on the influence of attenuation correction on parameters for glucose metabolism, the effect of motion, metal artefacts and contrast agents on quantification of CT attenuation-corrected images. Reconstruction settings (analytical versus iterative reconstruction, post-reconstruction filtering and image matrix size) all potentially influence quantification due to artefacts, noise levels and lesion size dependency. Many region of interest definitions are available, but increased complexity does not necessarily result in improved performance. Different methods for the quantification of the tissue of interest can introduce systematic and random inaccuracy. Conclusions This review provides an up-to-date overview of the many factors that influence quantification of glucose metabolism by FDG PET.

Indeterminate results at fine‐needle aspiration biopsy (FNAB) of thyroid nodules pose a clinical dilemma, because only 20% to 30% of patients suffer from malignancy. Previous studies suggested that the false‐negative ratio of [¹⁸F]‐2‐fluoro‐2‐deoxy‐D‐glucose–positron emission tomography (FDG‐PET) is very low; therefore, it may help identify patients who would benefit from (hemi)thyroidectomy. A systematic literature search was performed in 5 databases. After assessment, the identified studies were analyzed for heterogeneity, and the extracted data of test characteristics were pooled using a random‐effects model. Threshold effects were examined, and publication bias was assessed. The query resulted in 239 records, of which 6 studies met predefined inclusion criteria. Data from 225 of the 241 described patients could be extracted. There was mild to moderate heterogeneity in study results (inconsistency index [I²] = 0.390‐0.867). The pooled prevalence of malignancy was 26%. Pooled sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 95% (95% confidence interval [95% CI], 86%‐99%), 48% (95% CI, 40%‐56%), 39% (95% CI, 31%‐47%), 96% (95% CI, 90%‐99%), and 60% (95% CI, 53%‐67%), respectively. Sensitivity increased to 100% for the 164 lesions that measured >15 mm in greatest dimension. There was no evidence of threshold effects or publication bias. A negative FDG‐PET scan in patients who had thyroid nodules >15 mm with indeterminate FNAB results excluded thyroid cancer in a pooled population of 225 patients. Conversely, a positive FDG‐PET result did not identify cancer, because approximately 50% of these patients had benign nodules. The authors concluded that the incorporation of FDG‐PET into the initial workup of such patients before surgery deserves further investigation. Cancer 2011. © 2011 American Cancer Society

For the quantification of dynamic ¹⁸F-FDG PET studies, the arterial plasma time–activity concentration curve (APTAC) needs to be available. This can be obtained using serial sampling of arterial blood or an image-derived input function (IDIF). Arterial sampling is invasive and often not feasible in practice; IDIFs are biased because of partial-volume effects and cannot be used when no large arterial blood pool is in the field of view. We propose a mathematic function, consisting of an initial linear rising activity concentration followed by a triexponential decay, to describe the APTAC. This function was fitted to 80 oncologic patients and verified for 40 different oncologic patients by area-under-the-curve (AUC) comparison, Patlak glucose metabolic rate (MR_glc) estimation, and therapy response monitoring (ΔMR_glc). The proposed function was compared with the gold standard (serial arterial sampling) and the IDIF. Methods: To determine the free parameters of the function, plasma time–activity curves based on arterial samples in 80 patients were fitted after normalization for administered activity (AA) and initial distribution volume (iDV) of ¹⁸F-FDG. The medians of these free parameters were used for the model. In 40 other patients (20 baseline and 20 follow-up dynamic ¹⁸F-FDG PET scans), this model was validated. The population-based curve, individually calibrated by AA and iDV (APTAC_AA/iDV), by 1 late arterial sample (APTAC_1sample), and by the individual IDIF (APTAC_IDIF), was compared with the gold standard of serial arterial sampling (APTAC_sampled) using the AUC. Additionally, these 3 methods of APTAC determination were evaluated with Patlak MR_glc estimation and with ΔMR_glc for therapy effects using serial sampling as the gold standard. Results: Excellent individual fits to the function were derived with significantly different decay constants (P < 0.001). Correlations between AUC from APTAC_AA/iDV, APTAC_1sample, and APTAC_IDIF with the gold standard (APTAC_sampled) were 0.880, 0.994, and 0.856, respectively. For MR_glc, these correlations were 0.963, 0.994, and 0.966, respectively. In response monitoring, these correlations were 0.947, 0.982, and 0.949, respectively. Additional scaling by 1 late arterial sample showed a significant improvement (P < 0.001). Conclusion: The fitted input function calibrated for AA and iDV performed similarly to IDIF. Performance improved significantly using 1 late arterial sample. The proposed model can be used when an IDIF is not available or when serial arterial sampling is not feasible.

Accurate measurement of intratumor heterogeneity using parameters of texture on PET images is essential for precise characterization of cancer lesions. In this study, we investigated the influence of respiratory motion and varying noise levels on quantification of textural parameters in patients with lung cancer. Methods: We used an optimal-respiratory-gating algorithm on the list-mode data of 60 lung cancer patients who underwent ¹⁸F-FDG PET. The images were reconstructed using a duty cycle of 35% (percentage of the total acquired PET data). In addition, nongated images of varying statistical quality (using 35% and 100% of the PET data) were reconstructed to investigate the effects of image noise. Several global image-derived indices and textural parameters (entropy, high-intensity emphasis, zone percentage, and dissimilarity) that have been associated with patient outcome were calculated. The clinical impact of optimal respiratory gating and image noise on assessment of intratumor heterogeneity was evaluated using Cox regression models, with overall survival as the outcome measure. The threshold for statistical significance was adjusted for multiple comparisons using Bonferroni correction. Results: In the lower lung lobes, respiratory motion significantly affected quantification of intratumor heterogeneity for all textural parameters (P < 0.007) except entropy (P > 0.007). The mean increase in entropy, dissimilarity, zone percentage, and high-intensity emphasis was 1.3% ± 1.5% (P = 0.02), 11.6% ± 11.8% (P = 0.006), 2.3% ± 2.2% (P = 0.002), and 16.8% ± 17.2% (P = 0.006), respectively. No significant differences were observed for lesions in the upper lung lobes (P > 0.007). Differences in the statistical quality of the PET images affected the textural parameters less than respiratory motion, with no significant difference observed. The median follow-up time was 35 mo (range, 7–39 mo). In multivariate analysis for overall survival, total lesion glycolysis and high-intensity emphasis were the two most relevant image-derived indices and were considered to be independent significant covariates for the model regardless of the image type considered. Conclusion: The tested textural parameters are robust in the presence of respiratory motion artifacts and varying levels of image noise.

Indeterminate thyroid cytology (Bethesda III and IV) corresponds to follicular-patterned benign and malignant lesions, which are particularly difficult to differentiate on cytology alone. As approximately 25% of these nodules harbor malignancy, diagnostic hemithyroidectomy is still custom. However, advanced preoperative diagnostics are rapidly evolving. This review provides an overview of additional molecular and imaging diagnostics for indeterminate thyroid nodules in a pre-operative clinical setting, including considerations regarding cost-effectiveness, availability, and feasibility of combining techniques. Addressed diagnostics include gene mutation analysis, microRNA, immunocytochemistry, ultrasonography, elastosonography, CT, sestamibi scintigraphy, FDG-PET and diffusion-weighted MRI. The best rule-out tests for malignancy were the Afirma® GEC and FDG-PET. The most accurate rule-in test was sole BRAF mutation analysis. No diagnostic had both near-perfect sensitivity and specificity, and estimated cost-effectiveness. Molecular techniques are rapidly advancing. However, given the currently available techniques a multimodality stepwise approach likely offers the most accurate diagnosis, sequentially applying one sensitive rule-out test and one specific rule-in test. Geographical variations in cytology (e.g. Hürthle cell neoplasms) and tumor genetics strongly influence local test performance and clinical utility. Multidisciplinary collaboration and implementation studies can aid the local decision for one or more eligible diagnostics.