Target volume and artifact evaluation of a new data-driven 4D 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.

Validation of four-dimensional computed tomography without external reference respiratory signals for radiation treatment planning of lung tumors

Deviceless four-dimensional (4D) computed tomography (CT) allows the acquisition of respiratory signals from six features without requiring an external device for cine CT processing. This method has been recently introduced in radiation treatment planning of lung tumors. To validate deviceless 4D CT, it must be compared with conventional 4D CT, which requires an external monitoring device. We compared the two methods using a multicell 4D phantom that simulates patient's movement during respiration regarding the target volume (TV), target position (TP), and internal TV for lung tumor radiation therapy. We retrospectively obtained images of 10 patients who underwent radiation treatment planning of lung tumors and compared the two methods, as in the phantom study. For the phantom study, the mean TV, root mean square errors of the TP, and mean internal TV differences between the two methods ranged from -4.5% to 1.2%, 0.7 to 2.6 mm, and -1.1% to 3.4%, respectively. The corresponding results of the clinical study ranged from -1.5% to 14.9%, 0.1 to 5.9 mm, and -9.7% to 10.1%, respectively. The results of deviceless 4D CT for the clinical study were consistent with those of conventional 4D CT, except for target movements with high excursions. Therefore, deviceless 4D CT can be an alternative to conventional 4D CT for radiation treatment planning of lung tumors.

Data-driven gated (DDG) CT: An automated respiratory gating method to enable DDG PET/CT

BACKGROUND

The accuracy of PET quantification and localization can be compromised if a misregistered CT is used for attenuation correction (AC) in PET/CT. As data-driven gating (DDG) continues to grow in clinical use, these issues are becoming more relevant with respect to solutions for gated CT.

PURPOSE

In this work, a new automated data-driven gated (DDG) CT method was developed to provide average CT and DDG CT for AC of PET and DDG PET, respectively.

METHODS

An automatic DDG CT was developed to provide the end-expiratory (EE) and end-inspiratory (EI) phases of images from low-dose cine CT images, with all phases being averaged to generate an average CT. The respiratory phases of EE and EI were determined according to lung region Hounsfield unit (HU) values and body outline contours. The average CT was used for AC of baseline PET and DDG CT at EE phase was used for AC of DDG PET at the quiescent or EE phase. The EI and EE phases obtained with DDG CT were used for assessing the magnitude of respiratory motion. The proposed DDG CT was compared to two commercial CT gating methods: 1) 4D CT (external device based) and 2) D4D CT (DDG based) in 38 patient data sets with respect to respiratory phase image selection, lung HU, lung volume, and image artifacts. In a separate set of twenty consecutive PET/CT studies containing a mix of ¹⁸ F-FDG, ⁶⁸ Ga-Dotatate, and ⁶⁴ Cu-Dotatate scans, the proposed DDG CT was compared with D4D CT for impacts on registration and quantification in DDG PET/CT.

RESULTS

In the EE phase, the images selected by DDG CT and 4D CT were identical 62.5±21.6% of the time, while DDG CT and D4D CT were 6.5±9.7%, and 4D CT and D4D CT were 8.6±12.2%. These differences in EE phase image selection were significant (p<0.0001). In the EI phase, the images selected by DDG CT and 4D CT were identical 68.2±18.9% of the time, DDG CT and D4D CT were 63.9±18.8%, and 4D CT and D4D CT were 61.2±19.8%. These differences were not significant. The mean lung HU and volumes were not statistically different (p > 0.1) among the three methods. In some studies, DDG CT was better than D4D or 4D CT in appropriate selection of the EE and EI phases, and D4D CT was found to reverse the EE and EI phases or not select the correct images by visual inspection. A statistically significant improvement of DDG CT over D4D CT for AC of DDG PET was also demonstrated with PET quantification analysis. When irregular breath cycles were present in the cine CT, DDG CT could be used to replace average CT for improved AC of baseline PET.

CONCLUSION

A new automatic DDG CT was developed to tackle the issues of misregistration and tumor motion in PET/CT imaging. DDG CT was significantly more consistent than D4D CT in selecting the EE phase images as the clinical standard of 4D CT. When compared to both commercial gated CT methods of 4D CT and D4D CT, DDG CT appeared to be more robust in the lower lung and upper diaphragm regions where misregistration and tumor motion often occur. DDG CT offered improved AC for DDG PET relative to D4D CT. In cases with irregular respiratory motion, DDG CT improved AC over average CT for baseline PET. The new DDG CT provides the benefits of 4D CT without the need for external device gating. This article is protected by copyright. All rights reserved.

Impact of four-dimensional cone-beam computed tomography on target localization for gastric mucosa-associated lymphoid tissue lymphoma radiotherapy: reducing planning target volume

Background

Radiotherapy of gastric mucosa-associated lymphoid tissue (MALT) lymphoma should be delivered to the entire stomach with planning target volume (PTV) that accounts for variations in stomach volume, respiratory movement, and patient set-up error. In this study, we evaluated whether the use of four-dimensional cone-beam computed tomography (4D-CBCT) reduces the PTV.

Methods

Eight patients underwent radiotherapy with 15 fractions of gastric MALT lymphoma using 4D-CBCT. PTV structures of 5–30 mm margins (5 mm intervals) from the clinical target volume (CTV) delineated based on the 4D-CT images (CTV-4D) were generated. For the target localization, we performed matching based on skin marking (skin matching), bone anatomy (bone matching), and stomach anatomy (4D soft-tissue matching) based on registration between planning CT and 4D-CBCT images from 10 phases. For each patient, we calculated the covering ratio (CR) of the stomach with variable PTV structures, based on the 4D-CBCT images, with a total of 150 phases [CR (%) = (number of covering phases/150 phases) × 100], for three target localization methods. We compared the CR values of the different target localization methods and defined the PTV with an average CR of ≥ 95% for all patients.

Results

The average CR for all patients increased from 17.9 to 100%, 19.6 to 99.8%, and 33.8 to 100%, in the skin, bone, and 4D soft-tissue matchings, respectively, as the PTV structures increased from 5 to 30 mm. The CR obtained by 4D soft-tissue matching was superior to that obtained by skin (P = 0.013) and bone matching (P = 0.008) for a PTV structure of 15 mm margin. The PTV required an additional margin of 20 mm (average CR: 95.2%), 25 mm (average CR: 99.1%), and 15 mm (average CR: 98.0%) to CTV-4D for the skin, bone, and 4D soft-tissue matchings, respectively.

Conclusions

This study demonstrates that the use of 4D-CBCT reduces the PTV when applying 4D soft-tissue matching, compared to skin and bone matchings. Additionally, bone matching does not reduce the PTV as compared with traditional skin matching.

Current status of proton therapy techniques for lung cancer

Proton beams have been used for cancer treatment for more than 28 years, and several technological advancements have been made to achieve improved clinical outcomes by delivering more accurate and conformal doses to the target cancer cells while minimizing the dose to normal tissues. The state-of-the-art intensity modulated proton therapy is now prevailing as a major treatment technique in proton facilities worldwide, but still faces many challenges in being applied to the lung. Thus, in this article, the current status of proton therapy technique is reviewed and issues regarding the relevant uncertainty in proton therapy in the lung are summarized.

Real-time control of respiratory motion: Beyond radiation therapy

Motion management in radiation oncology is an important aspect of modern treatment planning and delivery. Special attention has been paid to control respiratory motion in recent years. However, other medical procedures related to both diagnosis and treatment are likely to benefit from the explicit control of breathing motion. Quantitative imaging - including increasingly important tools in radiology and nuclear medicine - is among the fields where a rapid development of motion control is most likely, due to the need for quantification accuracy. Emerging treatment modalities like focussed-ultrasound tumor ablation are also likely to benefit from a significant evolution of motion control in the near future. In the present article an overview of available respiratory motion systems along with ongoing research in this area is provided. Furthermore, an attempt is made to envision some of the most expected developments in this field in the near future.

Real-time data-driven motion correction in PET

PET imaging has been, and continues to be, an evolving diagnostic technology. In recent years, the modernizing digital landscape has opened new opportunities for data-driven innovation. One such facet has been data-driven motion correction (DDMC) in PET. As both research and industry propel this technology forward, we can recognize prospects and opportunities for further development. The concept of clinical practicality is supported by DDMC approaches—it is what sets them apart from traditional hardware-driven motion correction strategies that have largely not gained acceptance in routine diagnostic PET; the ease of use of DDMC may help propel acceptance of motion correction solutions in clinical practice. As we reflect on the present field, we should consider that DDMC can be made even more practical, and likely more impactful, if further developed to fit within a real-time acquisition framework. This vision for development is not new, but has been made more feasible with contemporary electronics, and has begun to be revisited in contemporary literature. The opportunities for development lie on a new forefront of innovation where medical physics integrates with engineering, data science, and modern computing capacities. Real-time DDMC is a systems integration challenge, and achieving it will require cooperation between hardware and software developers, and likely academia and industry. While challenges for development do exist, it is likely that we will see real-time DDMC come to fruition in the coming years. This effort may establish groundwork for developing similar innovations in the emerging digital innovation age.