Correction of oral contrast artifacts in CT-based attenuation correction of PET images using an automated segmentation algorithm

Variants and Pitfalls in PET/CT Imaging of Gastrointestinal Cancers

In the past two decades, PET/CT has become an essential modality in oncology increasingly used in the management of gastrointestinal (GI) cancers. Most PET/CT tracers used in clinical practice show some degree of GI uptake. This uptake is quite variable and knowledge of common patterns of biodistribution of various radiotracers is helpful in clinical practice. 18F-Fluoro-Deoxy-Glucose (FDG) is the most commonly used radiotracer and has quite a variable uptake within the bowel. 68Ga-Prostate specific membrane antigen (PSMA) shows intense uptake within the proximal small bowel loops. 11C-methyl-L-methionine (MET) shows high accumulation within the bowels, which makes it difficult to assess bowel or pelvic diseases. One must also be aware of technical artifacts causing difficulties in interpretations, such as high attenuation oral contrast material within the bowel lumen or misregistration artifact due to patient movements. It is imperative to know the common variants and benign diseases that can mimic malignant pathologies. Intense FDG uptake within the esophagus and stomach may be a normal variant or may be associated with benign conditions such as esophagitis, reflux disease, or gastritis. Metformin can cause diffuse intense uptake throughout the bowel loops. Intense physiologic uptake can also be seen within the anal canal. Segmental bowel uptake can be seen in inflammatory bowel disease, radiation, or medication induced enteritis/colitis or infection. Diagnosis of appendicitis or diverticular disease requires CT correlation, as normal appendix or diverticulum can show intense uptake. Certain malignant pathologies are known to have only low FDG uptake, such as early-stage esophageal adenocarcinoma, mucinous tumors, indolent lymphomas, and multicystic mesotheliomas. Response assessment, particularly in the neoadjuvant setting, can be limited by post-treatment inflammatory changes. Post-operative complications such as abscess or fistula formation can also show intense uptake and may obscure underlying malignant pathology. In the absence of clinical suspicion or rising tumor marker, the role of FDG PET/CT in routine surveillance of patients with GI malignancy is not clear.

Novel Quantitative PET Techniques for Clinical Decision Support in Oncology

Quantitative image analysis has deep roots in the usage of positron emission tomography (PET) in clinical and research settings to address a wide variety of diseases. It has been extensively employed to assess molecular and physiological biomarkers in vivo in healthy and disease states, in oncology, cardiology, neurology, and psychiatry. Quantitative PET allows relating the time-varying activity concentration in tissues/organs of interest and the basic functional parameters governing the biological processes being studied. Yet, quantitative PET is challenged by a number of degrading physical factors related to the physics of PET imaging, the limitations of the instrumentation used, and the physiological status of the patient. Moreover, there is no consensus on the most reliable and robust image-derived PET metric(s) that can be used with confidence in clinical oncology owing to the discrepancies between the conclusions reported in the literature. There is also increasing interest in the use of artificial intelligence based techniques, particularly machine learning and deep learning techniques in a variety of applications to extract quantitative features (radiomics) from PET including image segmentation and outcome prediction in clinical oncology. These novel techniques are revolutionizing clinical practice and are now offering unique capabilities to the clinical molecular imaging community and biomedical researchers at large. In this report, we summarize recent developments and future tendencies in quantitative PET imaging and present example applications in clinical decision support to illustrate its potential in the context of clinical oncology.

Quantification and reduction of respiratory induced artifacts in positron emission tomography/computed tomography using the time-of-flight technique

OBJECTIVE

The aim of this study was to investigate the impact of time-of-flight (TOF) on quantification and reduction of respiratory artifacts.

PATIENTS AND METHODS

The National Electrical Manufacturers Association phantom was used for optimization of reconstruction parameters. Twenty seven patients with lesions located in the diaphragmatic region were evaluated. The PET images were retrospectively reconstructed using non-TOF (routine protocol in our department) and TOF algorithms with different reconstruction parameters. Maximum standardized uptake value, estimated maximum tumor diameter, coefficient of variation, signal-to-noise ratio, and lesion-to-background-ratio were also evaluated.

RESULTS

On the basis of phantom experiments, TOF algorithms with two iterations, 18 subsets, and 5.4 mm and 6.4 mm postsmoothing filter reduced the noise by 3.1 and 12.6% in phantom with 2 : 1 activity ratio, and 3.0 and 13.1% in phantom with 4 : 1 activity ratio. The TOF algorithm with two iterations, 18 subsets, and 6.4 mm postsmoothing filter had the highest signal-to-noise value, and was selected as the optimal TOF reconstruction. Mean relative difference for signal-to-noise between non-TOF and optimal TOF in phantom with 2 : 1 and 4 : 1 activity ratio were 11.6 and 18.7%, respectively. In clinical data, the mean relative difference for estimated maximum tumor diameter and maximum standardized uptake value between routine protocol and optimal TOF algorithm were -6.3% (range: -20.4 to -0.6%) and 13.2% (range: 0.3-57.6%), respectively.

CONCLUSION

Integration of TOF in reconstruction algorithm remarkably improved the white band artifact in the diaphragmatic region. This technique affected the quantification accuracy and resulted in smaller tumor size and higher standardized uptake value in tumors located in/near the diaphragmatic region.

High (18)F-FDG uptake in urinary calculi on PET/CT: An unrecognized non-malignant accumulation

AIM

To assess the high (18)F-fluorodeoxyglucose ((18)F-FDG) uptake in urinary calculi on positron-emission tomography/computed tomography (PET/CT).

METHODS

In this study, (18)F-FDG PET/CT examinations were retrospectively reviewed from November 2013 to February 2016 in a single center, and patients with high (18)F-FDG uptake in urinary calculi were identified. The following data were collected from each patient, including age, sex, primary disease, method to verify the urinary calculus, and imaging characteristics of the calculus.

RESULTS

A total of 2758 PET/CT studies (2567 patients) were reviewed, and 52 patients with urinary calculi were identified, in which 6 (11.5%, 6/52) patients (5 males, 1 female, age 34-73 years, median age 60.5 years) demonstrated high (18)F-FDG uptake in the urinary calculi. Among the 6 patients, 3 patients had bladder calculi, 2 patients had renal calculi, and 1 patient had both bladder and renal calculi. The size of the urinary calculi varied from sandy to 19mm on CT. The maximal Hounsfield units of the calculi ranged from 153 to 1078. The SUVmax of the calculi on the routine PET/CT scan ranged from 11.7 to 143.0. Delayed PET/CT scans were performed on 4 patients, which showed the calculi SUVmax increasing in 2 patients, while decreasing in the other 2 patients. One patient with bladder calculus underwent a follow-up PET/CT, which showed enlargement of the calculus as well as the increased SUVmax.

CONCLUSION

This study shows an uncommon high (18)F-FDG uptake in urinary calculi. Recognition of this non-malignant accumulation in urinary calculi is essential for correct interpretation of PET/CT findings.

A novel approach to assess the treatment response using Gaussian random field in PET

PURPOSE

The assessment of early therapeutic response to anticancer therapy is vital for treatment planning and patient management in clinic. With the development of personal treatment plan, the early treatment response, especially before any anatomically apparent changes after treatment, becomes urgent need in clinic. Positron emission tomography (PET) imaging serves an important role in clinical oncology for tumor detection, staging, and therapy response assessment. Many studies on therapy response involve interpretation of differences between two PET images, usually in terms of standardized uptake values (SUVs). However, the quantitative accuracy of this measurement is limited. This work proposes a statistically robust approach for therapy response assessment based on Gaussian random field (GRF) to provide a statistically more meaningful scale to evaluate therapy effects.

METHODS

The authors propose a new criterion for therapeutic assessment by incorporating image noise into traditional SUV method. An analytical method based on the approximate expressions of the Fisher information matrix was applied to model the variance of individual pixels in reconstructed images. A zero mean unit variance GRF under the null hypothesis (no response to therapy) was obtained by normalizing each pixel of the post-therapy image with the mean and standard deviation of the pretherapy image. The performance of the proposed method was evaluated by Monte Carlo simulation, where XCAT phantoms (128(2) pixels) with lesions of various diameters (2-6 mm), multiple tumor-to-background contrasts (3-10), and different changes in intensity (6.25%-30%) were used. The receiver operating characteristic curves and the corresponding areas under the curve were computed for both the proposed method and the traditional methods whose figure of merit is the percentage change of SUVs. The formula for the false positive rate (FPR) estimation was developed for the proposed therapy response assessment utilizing local average method based on random field. The accuracy of the estimation was validated in terms of Euler distance and correlation coefficient.

RESULTS

It is shown that the performance of therapy response assessment is significantly improved by the introduction of variance with a higher area under the curve (97.3%) than SUVmean (91.4%) and SUVmax (82.0%). In addition, the FPR estimation serves as a good prediction for the specificity of the proposed method, consistent with simulation outcome with ∼1 correlation coefficient.

CONCLUSIONS

In this work, the authors developed a method to evaluate therapy response from PET images, which were modeled as Gaussian random field. The digital phantom simulations demonstrated that the proposed method achieved a large reduction in statistical variability through incorporating knowledge of the variance of the original Gaussian random field. The proposed method has the potential to enable prediction of early treatment response and shows promise for application to clinical practice. In future work, the authors will report on the robustness of the estimation theory for application to clinical practice of therapy response evaluation, which pertains to binary discrimination tasks at a fixed location in the image such as detection of small and weak lesion.

An update on novel quantitative techniques in the context of evolving whole-body PET imaging

Since its foundation PET has established itself as one of the standard imaging modalities enabling the quantitative assessment of molecular targets in vivo. In the past two decades, quantitative PET has become a necessity in clinical oncology. Despite introduction of various measures for quantification and correction of PET parameters, there is debate on the selection of the appropriate methodology in specific diseases and conditions. In this review, we have focused on these techniques with special attention to topics such as static and dynamic whole body PET imaging, tracer kinetic modeling, global disease burden, texture analysis and radiomics, dual time point imaging and partial volume correction.

Tumor quantification in clinical positron emission tomography

Positron emission tomography (PET) is used extensively in clinical oncology for tumor detection, staging and therapy response assessment. Quantitative measurements of tumor uptake, usually in the form of standardized uptake values (SUVs), have enhanced or replaced qualitative interpretation. In this paper we review the current status of tumor quantification methods and their applications to clinical oncology. Factors that impede quantitative assessment and limit its accuracy and reproducibility are summarized, with special emphasis on SUV analysis. We describe current efforts to improve the accuracy of tumor uptake measurements, characterize overall metabolic tumor burden and heterogeneity of tumor uptake, and account for the effects of image noise. We also summarize recent developments in PET instrumentation and image reconstruction and their impact on tumor quantification. Finally, we offer our assessment of the current development needs in PET tumor quantification, including practical techniques for fully quantitative, pharmacokinetic measurements.

Quantitative analysis shows that contrast medium in positron emission tomography/computed tomography may cause significant artefacts

OBJECTIVES

Attenuation correction algorithms are required for accurate quantification of PET data and for mapping of radioactive tracers. Modern PET systems incorporate computed tomography (CT) systems to perform attenuation correction. However, high-density media, such as contrast agents, may introduce potentially clinically significant artefacts in PET images when CT-based attenuation correction algorithms are used. Although various groups have investigated this issue, no study has quantitatively assessed the clinical significance of these artefacts by comparing artefact and lesion standardized uptake values (SUVs) in controlled phantom experiments. Furthermore, previous studies have focussed on the effects of increasing the concentration of contrast medium, without investigating the effects of increasing its transaxial area. This study quantifies the clinical significance of increasing the concentration and transaxial area of contrast agents and evaluates a commercially available contrast agent correction algorithm.

METHODS

Images of a phantom containing background activity, a volume of contrast agent and varying sizes of hot lesions were acquired using clinical acquisition protocols. Quantitative analysis was performed on transaxial image slices of PET data.

RESULTS

The densest medium caused a 125% SUV(mean) increase in the area containing, and immediately adjacent to, contrast medium when compared with a reference water phantom. As the transaxial area of the contrast medium increased, artefacts appeared as a ring of activity around the periphery of the contrast medium. The contrast correction algorithm reduced these artefacts to within ± 39% of the reference results.

CONCLUSION

Oral and IV contrast agents can cause clinically significant artefacts in CT-based attenuation-corrected PET images and should be used with caution.

Comparative assessment of energy-mapping approaches in CT-based attenuation correction for PET

INTRODUCTION

Reliable quantification in positron emission tomography (PET) requires accurate attenuation correction of emission data, which in turn entails accurate determination of the attenuation map (µ-map) of the object under study. One of the main steps involved in CT-based attenuation correction (CTAC) is energy-mapping, or the conversion of linear attenuation coefficients (µ) calculated at the effective CT energy to those corresponding to 511 keV.

MATERIALS AND METHODS

The aim of this study is to compare different energy-mapping techniques including scaling, segmentation, the hybrid method, the bilinear calibration curve technique and the dual-energy approach to generate the µ-maps required for attenuation correction. In addition, our newly proposed method involving a quadratic polynomial calibration curve was also assessed. The µ-maps generated for both phantom and clinical studies were assessed qualitatively and quantitatively. A cylindrical polyethylene phantom containing different concentrations of K(2)HPO(4) in water was scanned and the µ-maps calculated from the corresponding CT images using the above-referenced energy-mapping methods. The CT images of five whole-body data sets acquired on a GE Discovery LS PET/CT scanner were employed to generate µ-maps using different energy-mapping approaches that were compared with the µ-maps generated at 511 keV using (68)Ge/(68)Ga rod sources. In another experiment, the evaluation was performed on PET images of a clinical study corrected for attenuation using µ-maps generated using the above described methods. The evaluation was performed for three different tissue types, namely, soft tissue, lung, and bone.

RESULTS AND DISCUSSION

All energy-mapping methods yielded almost similar results for soft tissues. The mean relative differences between scaling, segmentation, hybrid, bilinear, and quadratic polynomial calibration curve methods and the transmission scan serving as reference were 6.60%, 6.56%, 6.60%, 5.96%, and 7.36%, respectively. However, the scaling method produced the largest difference (16%) for bone tissues. For lung tissues, the segmentation method produced the largest difference (14.9%). The results for reconstructed PET images followed a similar trend. For soft tissues, all energy-mapping methods yield results in nearly the same range. However, in bone tissues, the scaling method resulted in considerable bias in the µ-maps and the reconstructed PET images. The segmentation method also produced noticeable bias especially in regions with variable densities such as the lung, since a single µ is assigned to the lungs. Apart from the aforementioned case, despite small differences in the generated µ-maps, the use of different energy-mapping methods does not affect, to a visible or measurable extent, the reconstructed PET images.

The clinical role of fusion imaging using PET, CT, and MR imaging

Multimodality image registration and fusion have a key role in routine diagnosis, staging, restaging, and the assessment of response to treatment, surgery, and radiotherapy planning of malignant disease. The complementarity between anatomic (CT and MR imaging) and molecular (SPECT and PET) imaging modalities is well established and the role of fusion imaging widely recognized as a central piece of the general tree of clinical decision making. Moreover, dual modality imaging technologies including SPECT/CT, PET/CT, and, in the future, PET/MR imaging, now represent the leading component of contemporary health care institutions. This article discusses recent advances in clinical multimodality imaging, the role of correlative fusion imaging in a clinical setting, and future opportunities and challenges facing the adoption of multimodality imaging.