Assessing and accounting for the impact of respiratory motion on FDG uptake and viable volume for liver lesions in free-breathing PET using respiration-suspended PET images as reference

Current Applications of PET/MR: Part I: Technical Basics and Preclinical/Clinical Applications

Positron emission tomography/magnetic resonance (PET/MR) imaging has gone through major hardware improvements in recent years, making it a reliable state-of-the-art hybrid modality in clinical practice. At the same time, image reconstruction, attenuation correction, and motion correction algorithms have significantly evolved to provide high-quality images. Part I of the current review discusses technical basics, pre-clinical applications, and clinical applications of PET/MR in radiation oncology and head and neck imaging. PET/MR offers a broad range of advantages in preclinical and clinical imaging. In the preclinic, small and large animal-dedicated devices were developed, making PET/MR capable of delivering new insight into animal models in diseases and facilitating the development of methods that inform clinical PET/MR. Regarding PET/MR's clinical applications in radiation medicine, PET and MR already play crucial roles in the radiotherapy process. Their combination is particularly significant as it can provide molecular and morphological characteristics that are not achievable with other modalities. In addition, the integration of PET/MR information for therapy planning with linear accelerators is expected to provide potentially unique biomarkers for treatment guidance. Furthermore, in clinical applications in the head and neck region, it has been shown that PET/MR can be an accurate modality in head and neck malignancies for staging and resectability assessment. Also, it can play a crucial role in diagnosing residual or recurrent diseases, reliably distinguishing from oedema and fibrosis. PET/MR can furthermore help with tumour characterization and patient prognostication. Lastly, in head and neck carcinoma of unknown origin, PET/MR, with its diagnostic potential, may obviate multiple imaging sessions in the near future.

Preoperative 18F-FDG PET/CT and CT radiomics for identifying aggressive histopathological subtypes in early stage lung adenocarcinoma

Lung adenocarcinoma (ADC) is the most common non-small cell lung cancer. Surgical resection is the primary treatment for early-stage lung ADC while lung-sparing surgery is an alternative for non-aggressive cases. Identifying histopathologic subtypes before surgery helps determine the optimal surgical approach. Predominantly solid or micropapillary (MIP) subtypes are aggressive and associated with a higher likelihood of recurrence and metastasis and lower survival rates. This study aims to non-invasively identify these aggressive subtypes using preoperative 18F-FDG PET/CT and diagnostic CT radiomics analysis. We retrospectively studied 119 patients with stage I lung ADC and tumors ≤ 2 cm, where 23 had aggressive subtypes (18 solid and 5 MIPs). Out of 214 radiomic features from the PET/CT and CT scans and 14 clinical parameters, 78 significant features (3 CT and 75 PET features) were identified through univariate analysis and hierarchical clustering with minimized feature collinearity. A combination of Support Vector Machine classifier and Least Absolute Shrinkage and Selection Operator built predictive models. Ten iterations of 10-fold cross-validation (10 ×10-fold CV) evaluated the model. A pair of texture feature (PET GLCM Correlation) and shape feature (CT Sphericity) emerged as the best predictor. The radiomics model significantly outperformed the conventional predictor SUVmax (accuracy: 83.5% vs. 74.7%, p = 9e-9) and identified aggressive subtypes by evaluating FDG uptake in the tumor and tumor shape. It also demonstrated a high negative predictive value of 95.6% compared to SUVmax (88.2%, p = 2e-10). The proposed radiomics approach could reduce unnecessary extensive surgeries for non-aggressive subtype patients, improving surgical decision-making for early-stage lung ADC patients.

Abdominal Positron Emission Tomography/Magnetic Resonance Imaging

Hybrid positron emission tomography (PET)/magnetic resonance imaging (MRI) is highly suited for abdominal pathologies. A precise co-registration of anatomic and metabolic data is possible thanks to the simultaneous acquisition, leading to accurate imaging. The literature shows that PET/MRI is at least as good as PET/CT and even superior for some indications, such as primary hepatic tumors, distant metastasis evaluation, and inflammatory bowel disease. PET/MRI allows whole-body staging in a single session, improving health care efficiency and patient comfort.

Advancements and Future Outlook of PET/CT-Guided Interventions

Advancements in minimally invasive technology, coupled with imaging breakthroughs, have empowered the field of interventional radiology to achieve unparalleled precision in image-guided diagnosis and treatment while simultaneously reducing periprocedural morbidity. Molecular imaging, which provides valuable physiological and metabolic information alongside anatomical localization, can expand the capabilities of image-guided interventions. Among various molecular imaging techniques, positron emission tomography (PET) stands out for its superior spatial resolution and ability to acquire quantitative data. PET has emerged as a crucial tool for oncologic imaging and plays a pivotal role in both staging and the assessment of treatment responses. Typically used in combination with computed tomography (CT) (PET/CT) and occasionally with magnetic resonance imaging MRI (PET/MRI), PET as a hybrid imaging approach offers enhanced insights into disease progression and response. In recent years, PET has also found its way into image-guided interventions, especially within the rapidly expanding field of interventional oncology. This review aims to explore the current and evolving role of metabolic imaging, specifically PET, in interventional oncology. By delving into the unique advantages and applications of PET in guiding oncological interventions and assessing response, we seek to highlight the increasing significance of this modality in the realm of interventional radiology.

Evaluation and optimization of radiomics features stability to respiratory motion in 18 F-FDG 3D PET imaging

PURPOSE

To evaluate the impact of respiratory motion on radiomics features in ¹⁸ F-fluoro-2-deoxy-D-glucose three dimensional positron emission tomography (¹⁸ F-FDG 3D PET) imaging and optimize feature stability by combining preprocessing configurations and aggregation strategies.

METHODS

An in-house developed respiratory motion phantom was imaged in 3D PET scanner under nine respiratory patterns including one reference pattern. In total, 487 radiomics features were extracted for each respiratory pattern. Feature stability to respiratory motion was first evaluated by metrics of coefficient of variation (COV) and relative difference (RD) in a fixed preprocessing configuration. Further, one-way ANOVA and trend analysis were performed to evaluate the impact of preprocessing configuration (voxel size, discretization scheme) and aggregation strategy on feature stability. Finally, an optimization framework was proposed by selected feature-specific configurations with minimum COV value, and the diagnostic performance was validated in stable versus unstable features and fixed versus optimal features by a set of 46 patients with lung disease.

RESULTS

PET radiomics features were sensitive to respiratory motion, only 79/487 (16%) features were identified to be very stable in the fixed configuration. Preprocessing configuration and aggregation strategy had an impact on feature stability. For different voxel size, bin number, bin size and aggregation strategy, 188/487 (39%), 70/487 (15%), 148/487 (30%), and 38/95 (29%) features appeared significant changes in feature stability. The optimized configuration had the potential to improve feature stability compared to fixed configuration, with the COV decreased from 22% ±24% to 16% ±20%. Regarding the diagnostic performance, the stable and optimal configuration features outperformed the unstable and fixed configuration features, respectively (AUC 0.88, 0.87 vs. 0.83, 0.85).

CONCLUSIONS

Respiratory motion shows considerable impact on feature stability in 3D PET imaging, while optimizing preprocessing configuration may improve feature stability and diagnostic performance.

Impact of the Noise Penalty Factor on Quantification in Bayesian Penalized Likelihood (Q.Clear) Reconstructions of 68Ga-PSMA PET/CT Scans

Functional imaging with ⁶⁸Ga prostate-specific membrane antigen (PSMA) and positron emission tomography (PET) can fulfill an important role in treatment selection and adjustment in prostate cancer. This article focusses on quantitative assessment of ⁶⁸Ga-PSMA-PET. The effect of various parameters on standardized uptake values (SUVs) is explored, and an optimal Bayesian penalized likelihood (BPL) reconstruction is suggested. PET acquisitions of two phantoms consisting of a background compartment and spheres with diameter 4 mm to 37 mm, both filled with solutions of ⁶⁸Ga in water, were performed with a GE Discovery 710 PET/CT scanner. Recovery coefficients (RCs) in multiple reconstructions with varying noise penalty factors and acquisition times were determined and analyzed. Apparent recovery coefficients of spheres with a diameter smaller than 17 mm were significantly lower than those of spheres with a diameter of 17 mm and bigger (p < 0.001) for a tumor-to-background (T/B) ratio of 10:1 and a scan time of 10 min per bed position. With a T/B ratio of 10:1, the four largest spheres exhibit significantly higher RCs than those with a T/B ratio of 20:1 (p < 0.0001). For spheres with a diameter of 8 mm and less, alignment with the voxel grid potentially affects the RC. Evaluation of PET/CT scans using (semi-)quantitative measures such as SUVs should be performed with great caution, as SUVs are influenced by scanning and reconstruction parameters. Based on the evaluation of multiple reconstructions with different β of phantom scans, an intermediate β (600) is suggested as the optimal value for the reconstruction of clinical ⁶⁸Ga-PSMA PET/CT scans, considering that both detectability and reproducibility are relevant.

A modern review of the uncertainties in volumetric imaging of respiratory-induced target motion in lung radiotherapy

Radiotherapy has become a critical component for the treatment of all stages and types of lung cancer, often times being the primary gateway to a cure. However, given that radiation can cause harmful side effects depending on how much surrounding healthy tissue is exposed, treatment of the lung can be particularly challenging due to the presence of moving targets. Careful implementation of every step in the radiotherapy process is absolutely integral for attaining optimal clinical outcomes. With the advent and now widespread use of stereotactic body radiation therapy (SBRT), where extremely large doses are delivered, accurate, and precise dose targeting is especially vital to achieve an optimal risk to benefit ratio. This has largely become possible due to the rapid development of image-guided technology. Although imaging is critical to the success of radiotherapy, it can often be plagued with uncertainties due to respiratory-induced target motion. There has and continues to be an immense research effort aimed at acknowledging and addressing these uncertainties to further our abilities to more precisely target radiation treatment. Thus, the goal of this article is to provide a detailed review of the prevailing uncertainties that remain to be investigated across the different imaging modalities, as well as to highlight the more modern solutions to imaging motion and their role in addressing the current challenges.

Fluorodeoxyglucose-PET for Ablation Treatment Planning, Intraprocedural Monitoring, and Response

PET has become an essential tool for staging and response assessment in oncologic imaging. Over the past decade it has also evolved into a tool for image-guided interventions, specifically in the rapidly growing field of interventional oncology. PET-guided biopsies have greater sensitivity and diagnostic yield for fluorodeoxyglucose-avid lesions. Real-time PET imaging can also provide valuable image guidance during therapeutic minimally invasive procedures such as ablation of PET-avid tumors. The increasing use of PET in the assessment of therapeutic response results in earlier identification of disease that is amenable to image-guided therapies.

Management implications of fluorodeoxyglucose positron emission tomography/magnetic resonance in untreated intrahepatic cholangiocarcinoma

PURPOSE

Intrahepatic cholangiocarcinoma (ICC) is associated with a poor prognosis with surgical resection offering the best chance for long-term survival and potential cure. However, in up to 36% of patients who undergo surgery, more extensive disease is found at time of operation requiring cancellation of surgery. PET/MR is a novel hybrid technology that might improve local and whole-body staging in ICC patients, potentially influencing clinical management. This study was aimed to investigate the possible management implications of PET/MR, relative to conventional imaging, in patients affected by untreated intrahepatic cholangiocarcinoma.

METHODS

Retrospective review of the clinicopathologic features of 37 patients with iCCC, who underwent PET/MR between September 2015 and August 2018, was performed to investigate the management implications that PET/MR had exerted on the affected patients, relative to conventional imaging.

RESULTS

Of the 37 patients enrolled, median age 63.5 years, 20 (54%) were female. The same day PET/CT was performed in 26 patients. All patients were iCCC-treatment-naïve. Conventional imaging obtained as part of routine clinical care demonstrated early-stage resectable disease for 15 patients and advanced stage disease beyond the scope of surgical resection for 22. PET/MR modified the clinical management of 11/37 (29.7%) patients: for 5 patients (13.5%), the operation was cancelled due to identification of additional disease, while 4 "inoperable" patients (10.8%) underwent an operation. An additional 2 patients (5.4%) had a significant change in their operative plan based on PET/MR.

CONCLUSIONS

When compared with standard imaging, PET/MR significantly influenced the treatment plan in 29.7% of patients with iCCC.

TRIAL REGISTRATION

2018P001334.

Comparison of the clinical performance of upper abdominal PET/DCE-MRI with and without concurrent respiratory motion correction (MoCo)

PURPOSE

To compare the clinical performance of upper abdominal PET/DCE-MRI with and without concurrent respiratory motion correction (MoCo).

METHODS

MoCo PET/DCE-MRI of the upper abdomen was acquired in 44 consecutive oncologic patients and compared with non-MoCo PET/MRI. SUVmax and MTV of FDG-avid upper abdominal malignant lesions were assessed on MoCo and non-MoCo PET images. Image quality was compared between MoCo DCE-MRI and non-MoCo CE-MRI, and between fused MoCo PET/MRI and fused non-MoCo PET/MRI images.

RESULTS

MoCo PET resulted in higher SUVmax (10.8 ± 5.45) than non-MoCo PET (9.62 ± 5.42) and lower MTV (35.55 ± 141.95 cm³) than non-MoCo PET (38.11 ± 198.14 cm³; p < 0.005 for both). The quality of MoCo DCE-MRI images (4.73 ± 0.5) was higher than that of non-MoCo CE-MRI images (4.53±0.71; p = 0.037). The quality of fused MoCo-PET/MRI images (4.96 ± 0.16) was higher than that of fused non-MoCo PET/MRI images (4.39 ± 0.66; p < 0.005).

CONCLUSION

MoCo PET/MRI provided qualitatively better images than non-MoCo PET/MRI, and upper abdominal malignant lesions demonstrated higher SUVmax and lower MTV on MoCo PET/MRI.

Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211

PURPOSE

The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application.

APPROACH

A brief description of the different types of PET-AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET-AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET-AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto-segmentation are addressed.

FINDINGS

A large number of PET-AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi-automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal-to-noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol.

CONCLUSIONS

Available comparison studies suggest that PET-AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to evaluating both existing and future PET-AS algorithms needs to be designed, to aid clinicians in evaluating and selecting PET-AS algorithms and to establish performance limits for their acceptance for clinical use. The initial steps toward designing and building such a standard are undertaken by the task group members.

A Novel Respiratory Motion Perturbation Model Adaptable to Patient Breathing Irregularities

PURPOSE

To develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities.

METHODS AND MATERIALS

A novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The motion perturbation was derived from the patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied, and 2 amplitude-binned 4DCT images for each patient were acquired within 2 weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate the TV and BP as functions of the breathing phase. The motion was predicted from the simulation 4DCT scan to the treatment 4DCT scan, and vice versa, resulting in 800 predictions. For comparison, noncorrected motion differences and the predictions from a published 5-dimensional model were used.

RESULTS

The average motion range in the superoinferior direction was 9.4 ± 4.4 mm, the average ΔTV ranged from 10 to 248 mm³ (-26% to 61%), and the ΔBP ranged from 0 to 0.2 (-71% to 333%) between the 2 4DCT scans. The mean noncorrected motion difference was 2.0 ± 2.8 mm between 2 4DCT motion trajectories. After applying the RMP model, the mean motion difference was reduced significantly to 1.2 ± 1.8 mm (P=.0018), a 40% improvement, similar to the 1.2 ± 1.8 mm (P=.72) predicted with the 5-dimensional model.

CONCLUSIONS

A novel physical RMP model was developed with an average accuracy of 1.2 ± 1.8 mm for interfraction motion prediction, similar to that of a published lung motion model. This physical RMP was analytically derived and is able to adapt to breathing irregularities. Further improvement of this RMP model is under investigation.

Interventional Molecular Imaging

Although molecular imaging has had a dramatic impact on diagnostic imaging, it has only recently begun to be integrated into interventional procedures. Its significant impact is attributed to its ability to provide noninvasive, physiologic information that supplements conventional morphologic imaging. The four major interventional opportunities for molecular imaging are, first, to provide guidance to localize a target; second, to provide tissue analysis to confirm that the target has been reached; third, to provide in-room, posttherapy assessment; and fourth, to deliver targeted therapeutics. With improved understanding and application of(18)F-FDG, as well as the addition of new molecular probes beyond(18)F-FDG, the future holds significant promise for the expansion of molecular imaging into the realm of interventional procedures.

Correcting for respiratory motion in liver PET/MRI: preliminary evaluation of the utility of bellows and navigated hepatobiliary phase imaging

Background

The purpose of this study was to evaluate the utility of bellows-based respiratory compensation and navigated hepatobiliary phase imaging to correct for respiratory motion in the setting of dedicated liver PET/MRI.

Methods

Institutional review board approval and informed consent were obtained. Six patients with metastatic neuroendocrine tumor were imaged using Ga-68 DOTA-TOC PET/MRI. Whole body imaging and a dedicated 15-min liver PET acquisition was performed, in addition to navigated and breath-held hepatobiliary phase (HBP) MRI. Liver PET data was reconstructed three ways: the entire data set (liver PET), gated using respiratory bellows (RC-liver PET), and a non-gated data set reconstructed using the same amount of data used in the RC-liver PET (shortened liver PET). Liver lesions were evaluated using SUV_max, SUV_peak, SUV_mean, and Vol_isocontour. Additionally, the displacement of each lesion between the RC-liver PET images and the navigated and breath-held HBP images was calculated.

Results

Respiratory compensation resulted in a 43 % increase in SUVs compared to ungated data (liver vs RC-liver PET SUV_max 26.0 vs 37.3, p < 0.001) and a 25 % increase compared to a non-gated reconstruction using the same amount of data (RC-liver vs shortened liver PET SUV_max 26.0 vs 32.6, p < 0.001). Lesion displacement was minimized using navigated HBP MRI (1.3 ± 1.0 mm) compared to breath-held HBP MRI (23.3 ± 1.0 mm).

Conclusions

Respiratory bellows can provide accurate respiratory compensation when imaging liver lesions using PET/MRI, and results in increased SUVs due to a combination of increased image noise and reduced respiratory blurring. Additionally, navigated HBP MRI accurately aligns with respiratory compensated PET data.