4D PET/CT as a Strategy to Reduce Respiratory Motion Artifacts in FDG-PET/CT

Data-driven gated positron emission tomography/computed tomography for radiotherapy

Purpose

Software-based data-driven gated (DDG) positron emission tomography/computed tomography (PET/CT) has replaced hardware-based 4D PET/CT. The purpose of this article was to review DDG PET/CT, which could improve the accuracy of treatment response assessment, tumor motion evaluation, and target tumor contouring with whole-body (WB) PET/CT for radiotherapy (RT).

Material and methods

This review covered the topics of 4D PET/CT with hardware gating, advancements in PET instrumentation, DDG PET, DDG CT, and DDG PET/CT based on a systematic literature review. It included a discussion of the large axial field-of-view (AFOV) PET detector and a review of the clinical results of DDG PET and DDG PET/CT.

Results

DDG PET matched or outperformed 4D PET with hardware gating. DDG CT was more compatible with DDG PET than 4D CT, which required hardware gating. DDG CT could replace 4D CT for RT. DDG PET and DDG CT for DDG PET/CT can be incorporated in a WB PET/CT of less than 15 min scan time on a PET/CT scanner of at least 25 cm AFOV PET detector.

Conclusions

DDG PET/CT could correct the misregistration and tumor motion artifacts in a WB PET/CT and provide the quantitative PET and tumor motion information of a registered PET/CT for RT.

Improving the Feasibility of Mitigating Phase Errors in 4DCT caused by a Random Reference Breathing Pattern in the Quasar Phantom and the Role of Slice Thickness

PURPOSE

The study aimed to validate a method for minimizing phase errors by combining full-length lung 4DCT (f4DCT) scans with shorter tumor-restricted 4DCT (s4DCT) scans. It assessed the feasibility of integrating two scans one covering the entire phantom length and the other focused on the tumor area. The study also evaluated the impact of Maximum Intensity Projection (MIP) volume and imaging dose for different slice thicknesses (2.5mm and 1.25mm) in both full-length and short target-restricted 4DCT scans.

METHODS

The study utilized the Quasar Programmable Respiratory Motion Phantom, simulating tumor motion with a variable lung insert. The setup included a tumor replica and a six-dot IR reflector marker on the breathing platform. The objective was to analyze volume differences in fMIP_2.5mm compared to sMIP_1.25mm within their respective 4D_MIP CT series. This involved varying breathing periods (2.5s, 3.0s, 4.0s, and 5.0s) and longitudinal tumor sizes (6mm, 8mm, and 10mm). The study also assessed exposure time and expected CTDIvol of s4D_2.5mm and s4D_1.25mm for different breathing periods (5.0s to 2.0s) in the sinusoidal wave motion of the six-dot marker on the breathing platform.

RESULTS

Conducting two consecutive 4DCT scans is viable for patients with challenging breathing patterns or when the initial lung tumor scan is in close proximity to the tumor location, eliminating the need for an additional full-length 4DCT. The analysis involves assessing MIP volume, imaging dose (CTDIvol), and exposure time. Longitudinal tumor shifts for 6mm are [16.6-17.2] in fMIP_2.5mm and [16.8-17.5] in sMIP_1.25mm, for 8mm [17.2-18.3] in fMIP_2.5mm and [17.8-18.4] in sMIP_1.25mm, and for 10mm [19-19.9] in fMIP_2.5mm and [19.4-20] in sMIP_1.25mm (p≥ 0.005), respectively.

CONCLUSION

The Quasar Programmable Respiratory Motion Phantom accurately replicated varied breathing patterns and tumor motions. Comprehensive analysis was facilitated through detailed manual segmentation of Internal Target Volumes and Internal Gross Target Volumes.

Automated Lung Cancer Segmentation Using a PET and CT Dual-Modality Deep Learning Neural Network

PURPOSE

To develop an automated lung tumor segmentation method for radiation therapy planning based on deep learning and dual-modality positron emission tomography (PET) and computed tomography (CT) images.

METHODS AND MATERIALS

A 3-dimensional (3D) convolutional neural network using inputs from diagnostic PETs and simulation CTs was constructed with 2 parallel convolution paths for independent feature extraction at multiple resolution levels and a single deconvolution path. At each resolution level, the extracted features from the convolution arms were concatenated and fed through the skip connections into the deconvolution path that produced the tumor segmentation. Our network was trained/validated/tested by a 3:1:1 split on 290 pairs of PET and CT images from patients with lung cancer treated at our clinic, with manual physician contours as the ground truth. A stratified training strategy based on the magnitude of the gross tumor volume (GTV) was investigated to improve performance, especially for small tumors. Multiple radiation oncologists assessed the clinical acceptability of the network-produced segmentations.

RESULTS

The mean Dice similarity coefficient, Hausdorff distance, and bidirectional local distance comparing manual versus automated contours were 0.79 ± 0.10, 5.8 ± 3.2 mm, and 2.8 ± 1.5 mm for the unstratified 3D dual-modality model. Stratification delivered the best results when the model for the large GTVs (>25 mL) was trained with all-size GTVs and the model for the small GTVs (<25 mL) was trained with small GTVs only. The best combined Dice similarity coefficient, Hausdorff distance, and bidirectional local distance from the 2 stratified models on their corresponding test data sets were 0.83 ± 0.07, 5.9 ± 2.5 mm, and 2.8 ± 1.4 mm, respectively. In the multiobserver review, 91.25% manual versus 88.75% automatic contours were accepted or accepted with modifications.

CONCLUSIONS

By using an expansive clinical PET and CT image database and a dual-modality architecture, the proposed 3D network with a novel GTVbased stratification strategy generated clinically useful lung cancer contours that were highly acceptable on physician review.

Respiratory gated multistatic PET reconstructions to delineate radiotherapy target volume in patients with mobile lung tumors

BACKGROUND

PET-CT with ¹⁸F-FDG or other radiopharmaceuticals is a recommended tool to help the delineation of lung cancers candidate to radiotherapy. The motion artifacts caused by respiratory movements are reduced by 4D acquisitions. We introduced an extended reconstruction algorithm (multiple reconstruct register and average [multi-RRA]) which requires much shorter acquisition times than standard 4D PET-CT. Our aim was to evaluate the interest on multi-RRA images as an alternative of 3D and 4D PET-CT for the delineation of lung lesion.

METHODS

PET acquisitions synchronized to the respiratory signal were obtained in 18 patients with mobile lung tumors. We compared the tumor volumes delineated on Multi-RRA images to 3D and 4D PET-CT, considering the 4D CT as a reference. The tumor volumes were delineated and compared with topologic similarity indexes (Dice, Jaccard and overlap).

RESULTS

Twenty tumors were delineated. The volumes delineated with multi-RRA and 4D PET were not significantly different (mean difference of 0.2±0.7 mL). Comparison by pairs (Tukey-Kramer test) showed that 3D-PET volumes were significantly smaller than 4D-PET and multi-RRA volumes (P<0.001). Topologic similarity indexes with 4D-PET were slightly statistically higher with multi-RRA than with 3D-PET (Dice and Jaccard) or 4D-CT (Dice, Jaccard and Overlap).

CONCLUSIONS

The tumor volumes delineated on multi-RRA are similar to the volumes obtained with 4D PET, with shorter acquisition time.

Data-driven gated PET/CT: implications for lesion segmentation and quantitation

Background

Data-driven gating (DDG) can improve PET quantitation and alleviate many issues with patient motion. However, misregistration between DDG-PET and CT may occur due to the distinct temporal resolutions of PET and CT and can be mitigated by DDG-CT. Here, the effects of misregistration and respiratory motion on PET quantitation and lesion segmentation were assessed with a new DDG-PET/CT method.

Methods

A low-dose cine-CT was acquired in misregistered regions to enable both average CT (ACT) and DDG-CT. The following were compared: (1) baseline PET/CT, (2) PET/ACT (attenuation correction, AC = ACT), (3) DDG-PET (AC = helical CT), and (4) DDG-PET/CT (AC = DDG-CT). For DDG-PET, end-expiration (EE) data were derived from 50% of the total PET data at 30% from end-inspiration. For DDG-CT, EE phase CT data were extracted from cine-CT data by lung Hounsfield unit (HU) value and body contour. A total of 91 lesions from 16 consecutive patients were assessed for changes in standard uptake value (SUV), lesion glycolysis (LG), lesion volume, centroid-to-centroid distance (CCD), and DICE coefficients.

Results

Relative to baseline PET/CT, median changes in SUV_max ± σ for all 91 lesions were 20 ± 43%, 26 ± 23%, and 66 ± 66%, respectively, for PET/ACT, DDG-PET, and DDG-PET/CT. Median changes in lesion volume were 0 ± 58%, − 36 ± 26%, and − 26 ± 40%. LG for individual lesions increased for PET/ACT and decreased for DDG-PET, but was not different for DDG-PET/CT. Changes in mean HU from baseline PET/CT were dramatic for most lesions in both PET/ACT and DDG-PET/CT, especially for lesions with mean HU < 0 at baseline. CCD and DICE were both affected more by motion correction with DDG-PET than improved registration with ACT or DDG-CT.

Conclusion

As misregistration becomes more prominent, the impact of motion correction with DDG-PET is diminished. The potential benefits of DDG-PET toward accurate lesion segmentation and quantitation could only be fully realized when combined with DDG-CT. These results impress upon the necessity of ensuring both misregistration and motion correction are accounted for together to optimize the clinical utility of PET/CT.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-021-00411-5.

Design of an anthropomorphic PET phantom with elastic lungs and respiration modeling

PURPOSE

Respiratory motion during positron emission tomography (PET) scans can be a major detriment to image quality in oncological imaging. The impact of motion on lesion quantification and detectability can be assessed using phantoms with realistic anatomy representation and motion modeling. In this work, we develop an anthropomorphic phantom for PET imaging that combines anatomic fidelity and a realistic breathing mechanism with deformable lungs.

METHODS

We start from a previously developed anatomically accurate but static phantom of a human torso, and add elastic lungs with a highly controllable actuation mechanism which replicates the physics of breathing. The space outside the lungs is filled with a radioactive water solution. To maintain anatomical accuracy and realistic gamma ray attenuation in the torso, all motion mechanisms and actuators are positioned outside of the phantom compartment. The actuation mechanism can produce custom respiratory waveforms with breathing rates up to 25 breaths per minute and tidal volumes up to 1200 mL.

RESULTS

Several tests were performed to validate the performance of the phantom assembly, in which the phantom was filled with water and given respiratory waveforms to execute. All parts demonstrated expected performance. Force requirements were not exceeded and no leaks were detected, although continued use of the phantom is required to evaluate wear. The motion of the lungs was determined to be within a reasonable realistic range.

CONCLUSIONS

The full mechanical design is described in this paper, as well as a software application with graphical user interface which was developed to plan and visualize respiratory patterns. Both are available online as open source files. The developed phantom will facilitate future work in evaluating the impact of respiratory motion on lesion quantification and detectability in clinical practice.

New Data-Driven Gated PET/CT Free of Misregistration Artifacts

PURPOSE

We developed a new data-driven gated (DDG) positron emission tomography (PET)/computed tomography (CT) to improve the registration of CT and DDG PET.

METHODS

We acquired 10 repeat PET/CT and 35 cine CT scans for the mitigation of misregistration between CT and PET data. We also derived end-expiration phase CT as DDG CT for attenuation correction of DDG PET. Radiation exposure, body mass index (BMI), scan coverage, and effective radiation dose were compared between repeat PET/CT and cine CT. Of the 35 cine CT patients, 14 (capturing 59 total tumors) were compared among average PET/CT (baseline PET attenuation correction by average CT), DDG PET (DDG PET attenuation correction by baseline CT), and DDG PET/CT (DDG PET attenuation correction by DDG CT) for registration and quantification without increasing the scan time for DDG PET.

RESULTS

Compared with repeat PET/CT, cine CT had significantly lower scan coverage (32.5 ± 11.5 cm vs 15.4 ± 4.7 cm; P < .001) and effective radiation dose (3.7 ± 2.6 mSv vs 1.3 ± 0.6 mSv; P < .01). Repeat PET/CT and cine CT did not differ significantly in BMI or radiation exposure (P > .1). Cine CT saved the scan time for not needing a repeat PET. The SUV ratios of average PET/CT, DDG PET, and DDG PET/CT to baseline PET/CT were 1.14 ± 0.28, 1.28 ± 0.20, and 1.63 ± 0.64, respectively (P < .0001), suggesting that the SUV_max increased consecutively from baseline PET/CT to average PET/CT, DDG PET, and DDG PET/CT. Motion correction with DDG PET had a larger impact on quantification than registration improvement with average CT did. The biggest improvement in quantification was from DDG PET/CT, in which both registration was improved and motion was mitigated.

CONCLUSION

Our new DDG PET/CT approach alleviates misregistration artifacts and, compared with DDG PET, improves quantification and registration. The use of cine CT in our DDG PET/CT method also reduces the effective radiation dose and scan coverage compared with repeat CT.

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.

PET and MRI based RT treatment planning: Handling uncertainties

Imaging provides the basis for radiotherapy. Multi-modality images are used for target delineation (primary tumor and nodes, boost volume) and organs at risk, treatment guidance, outcome prediction, and treatment assessment. Next to anatomical information, more and more functional imaging is being used. The current paper provides a brief overview of the different applications of imaging techniques used in the radiotherapy process, focusing on uncertainties and QA. The paper mainly focuses on PET and MRI, but also provides a short discussion on DCE-CT. A close collaboration between radiology, nuclear medicine and radiotherapy departments provides the key to improve the quality of radiotherapy. Jointly developed imaging protocols (RT position setup, immobilization tools, lasers, flat table…), and QA programs are mandatory. For PET, suitable windowing in consultation with a Nuclear Medicine Physician is crucial (differentiation benign/malignant lesions, artifacts…). A basic knowledge of MRI sequences is required, in such a way that geometrical distortions are easily recognized by all members the RT and RT physics team. If this is not the case, then the radiologist should be introduced systematically in the delineation process and multidisciplinary meetings need to be organized regularly. For each image modality and each image registration process, the associated uncertainties need to be determined and integrated in the PTV margin. When using functional information for dose painting, response assessment or outcome prediction, collaboration between the different departments is even more important. Limitations of imaging based biomarkers (specificity, sensitivity) should be known.

Adjuvant chemoradiation for gastric carcinoma: State of the art and perspectives

An estimated 990,000 new cases of gastric cancer are diagnosed worldwide each year. Surgical excision, the only chance for prolonged survival, is feasible in about 20% of cases. Even after surgery, the median survival is limited to 12 to 20 months due to the frequency of locoregional and/or metastatic recurrences. This led to clinical trials associating surgery with neoadjuvant or adjuvant treatments to improve tumor control and patient survival. The most studied modalities are perioperative chemotherapy and adjuvant chemoradiotherapy. To date, evidence has shown a survival benefit for postoperative chemoradiotherapy and for perioperative chemotherapy. Phase III trials are ongoing to compare these two modalities. The aim of this review is to synthesize current knowledge about adjuvant chemoradiotherapy in the management of gastric adenocarcinoma, and to consider its prospects by integrating modern radiotherapy techniques.

Impact of tumour motion compensation and delineation methods on FDG PET-based dose painting plan quality for NSCLC radiation therapy

INTRODUCTION

To quantitatively estimate the impact of different methods for both boost volume delineation and respiratory motion compensation of [18F] FDG PET/CT images on the fidelity of planned non-uniform 'dose painting' plans to the prescribed boost dose distribution.

METHODS

Six locally advanced non-small cell lung cancer (NSCLC) patients were retrospectively reviewed. To assess the impact of respiratory motion, time-averaged (3D AVG), respiratory phase-gated (4D GATED) and motion-encompassing (4D MIP) PET images were used. The boost volumes were defined using manual contour (MANUAL), fixed threshold (FIXED) and gradient search algorithm (GRADIENT). The dose painting prescription of 60 Gy base dose to the planning target volume and an integral dose of 14 Gy (total 74 Gy) was discretized into seven treatment planning substructures and linearly redistributed according to the relative SUV at every voxel in the boost volume. Fifty-four dose painting plan combinations were generated and conformity was evaluated using quality index VQ0.95-1.05, which represents the sum of planned dose voxels within 5% deviation from the prescribed dose. Trends in plan quality and magnitude of achievable dose escalation were recorded.

RESULTS

Different segmentation techniques produced statistically significant variations in maximum planned dose (P < 0.02), as well as plan quality between segmentation methods for 4D GATED and 4D MIP PET images (P < 0.05). No statistically significant differences in plan quality and maximum dose were observed between motion-compensated PET-based plans (P > 0.75). Low variability in plan quality was observed for FIXED threshold plans, while MANUAL and GRADIENT plans achieved higher dose with lower plan quality indices.

CONCLUSIONS

The dose painting plans were more sensitive to segmentation of boost volumes than PET motion compensation in this study sample. Careful consideration of boost target delineation and motion compensation strategies should guide the design of NSCLC dose painting trials.

18-Fluorodeoxy-Glucose Positron Emission Tomography- Computed Tomography (18-FDG-PET/CT) for Gross Tumor Volume (GTV) Delineation in Gastric Cancer Radiotherapy

Purpose:

Evaluation of the 18-fluorodeoxy-glucose positron emission tomography-computed tomography (18-FDG-PET/_CT) for gross tumor volume (GTV) delineation in gastric cancer patients undergoing radiotherapy.

Methods:

In this study, 29 gastric cancer patients (17 unresectable and 7 inoperable) were initially enrolled for radical chemoradiotherapy (45Gy/25 fractions + chemotherapy based on 5 fluorouracil) or radiotherapy alone (45Gy/25 fractions) with planning based on the 18-FDG-PET/CT images. Five patients were excluded due to excess blood glucose levels (1), false-negative positron emission tomography (1) and distant metastases revealed by 18-FDG-PET/CT (3). The analysis involved measurement of metabolic tumor volumes (MTVs) performed on PET/CT workstations. Different threshold levels of the standardized uptake value (SUV) and liver uptake were set to obtain MTVs. Secondly, GTV_PET values were derived manually using the positron emission tomography (PET) dataset blinded to the computed tomography (CT) data. Subsequently, GTV_CT values were delineated using a radiotherapy planning system based on the CT scans blinded to the PET data. The referenced GTV_CT values were correlated with the GTV_PET and were compared with a conformality index (CI).

Results:

The mean CI was 0.52 (range, 0.12-0.85). In 13/24 patients (54%), the GTV_PET was larger than GTV_CT, and in the remainder, GTV_PET was smaller. Moreover, the cranio-caudal diameter of GTV_PET in 16 cases (64%) was larger than that of GTV_CT, smaller in 7 cases (29%), and unchanged in one case. Manual PET delineation (GTVPET) achieved the best correlation with GTV_CT (Pearson correlation = 0.76, p <0.0001). Among the analyzed MTVs, a statistically significant correlation with GTV_CT was revealed for MTV_10%SUVmax (r = 0.63; p = 0.0014), MTV_liv (r = 0.60; p = 0.0021), MTV_SUV2.5 (r = 0.54; p = 0.0063); MTV_20%SUVmax (r = 0.44; p = 0.0344); MTV_30%SUVmax (r = 0.44; p = 0.0373).

Conclusion:

18-FDG-PET/_CT in gastric cancer radiotherapy planning may affect the GTV delineation.

Frequency based gating: An alternative, conformal, approach to 4D PET data utilization

PURPOSE

Respiratory gating is a strategy for overcoming image degradation caused by patient motion in Positron Emission Tomography (PET) imaging. Traditional methods for sorting data, namely, phase-based gating or amplitude-based gating, come with an inherent trade-off between resolution improvements and added noise present in the subjugated data. If the goal of motion correction in PET is realigned from creating 4D images that attempt to mimic nongated images, towards ideal utilization of the information available, then new paths for data management emerge. In this work, the authors examine the application of a method in a new class of frequency based data subjugation algorithms, termed gating +. This strategy utilizes data driven information to locally adapt signal to its optimal segregation, thereby creating a new approach to 4D data utilization PET.

METHODS

189 (18)F-fluorodeoxyglucose (FDG) PET scans were acquired at a single bed position centered on the thorax region. 4D gated image sets were reconstructed using data driven gating. The gating+ signal optimization algorithm, previously presented in small animal PET images and simulations, was used to segregate data in frequency space to generate optimized 4D images in the population-the first application and analysis of gating+ in human PET scans. The nongated, phase gated, and gating+ representations of the data were compared using FDG uptake analysis in the identified lesions and noise measurements from background regions.

RESULTS

Optimized processing required less than 1 min per scan on a standard PC (plus standard reconstruction time), and yielded entire 4D optimized volumes plus motion maps. Optimized scans had noise characteristics similar to nongated images, yet also contained much of the resolution and motion information found in the gated images. The average SUVmax increase in the lesion sample between gated/nongated and gating+/nongated (±SD in population) was 35.8% ± 34.6% and 28.6% ± 27.9%, respectively. The average percent standard deviation (%SD ± SD in population) in liver volumes of interest (VOIs) across the sample for the nongated, gated, and gating+ scans was 6.7% ± 2.4%, 13.6% ± 3.3%, and 7.1% ± 2.5%, respectively. In all cases, the noise in the gating+ liver VOIs was closer to the nongated measurements than to the gated.

CONCLUSIONS

The gating+ algorithm introduces the notion of conforming 4D data segregation to the local information and statistics that support it. By segregating data in frequency space, the authors are able to generate low noise motion information rich image sets, derived solely from selective use of raw data. Their work shows that the gating+ algorithm can be robustly applied in populations, and across varying qualities of motion and scans statistics, and be integrated as part of a fully automated motion correction workflow. Furthermore, the idea of smart signal utilization underpins a new concept of low risk or even risk-free motion correction application in PET.

[Positron emission tomography and stereotactic body radiation therapy for lung cancer: From treatment planning to response evaluation]

Stereotactic body radiation therapy is the standard treatment for inoperable patients with early-stage lung cancer. Local control rates range from 80 to 90 % 2 years after treatment. The role of positron emission tomography in patient selection is well known, but its use for target definition or therapeutic response evaluation is less clear. We reviewed the literature in order to assess the current state of knowledge in this area.