Dataset Information

Fractionated deep-inspiration breath-hold ZTE Compared with Free-breathing four-dimensional ZTE for detecting pulmonary nodules in oncological patients underwent PET/MRI.

ABSTRACT: The zero echo time (ZTE) technique has improved the detection of lung nodules in PET/MRI but respiratory motion remains a challenge in lung scan. We investigated the feasibility and performance of fractionated deep-inspiration breath-hold (FDIBH) three-dimensional (3D) ZTE FDG PET/MRI for assessing lung nodules in patients with proved malignancy. Sixty patients who had undergone ZTE FDG PET/MRI and chest CT within a three-day interval were retrospectively included. Lung nodules less than 2 mm were excluded for analysis. Two physicians checked the adequacy of FDIBH ZTE and compared the lung nodule detection rates of FDIBH 3D ZTE and free-breathing (FB) four-dimensional (4D) ZTE, with chest CT as the reference standard. FDIBH resolved the effect of respiratory motion in 49 patients. The mean number and size of the pulmonary nodules identified in CT were 15 ± 31.3 per patient and 5.9 ± 4.6 mm in diameter. The overall nodule detection rate was 71% for FDIBH 3D ZTE and 70% for FB 4D ZTE (p = 0.73). FDIBH 3D ZTE significantly outperformed FB 4DZTE in detecting lung base nodules (72% and 68%; p = 0.03), especially for detecting those less than 6 mm (61% and 55%; p = 0.03). High inter-rater reliability for FDIBH 3D ZTE and FB 4D ZTE (k = 0.9 and 0.92) was noted. In conclusion, the capability of FDIBH 3D ZTE in respiratory motion resolution was limited with a technical failure rate of 18%. However, it could provide full expansion of the lung in a shorter scan time which enabled better detection of nodules (< 6 mm) in basal lungs, compared to FB 4D ZTE.

SUBMITTER: Chang CY

PROVIDER: S-EPMC8417270 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:PurposeDeep inspiration breath hold (DIBH) and respiratory gating (RG) are widely used to reduce movement of target and healthy organs caused by breathing during irradiation. We hypothesized that accuracy and efficiency comparable to DIBH can be achieved with RG for pancreas treatment.Methods and materialsTwenty consecutive patients with pancreatic cancer treated with DIBH (eight) or RG (twelve) volumetric modulated arc therapy during 2017-2019 were included in this study, with radiopaque markers implanted near or in the targets. Seventeen patients received 25 fractions, while the other three received 15 fractions. Only patients who could not tolerate DIBH received RG treatment. While both techniques relied on respiratory signals from external markers, internal target motions were monitored with kV X-ray imaging during treatment. A 3-mm external gating window was used for DIBH treatment; RG treatment was centered on end-expiration with a duty cycle of 40%, corresponding to an external gating window of 2-3 mm. During dose delivery, kV images were automatically taken every 20? or 40? gantry rotation, from which internal markers were identified. The marker displacement from their initial positions and the residual motion amplitudes were calculated. For the analysis of treatment efficiency, the treatment time of every session was calculated from the motion management waveform files recorded at the treatment console.ResultsWithin one fraction, the displacement was 0-5 mm for DIBH and 0-6 mm for RG. The average magnitude of displacement for each patient during the entire course of treatment ranged 0-3 mm for both techniques. No statistically significant difference in displacement or residual motion was observed between the two techniques. The average treatment time was 15 min for DIBH and 17 min for RG, with no statistical significance.ConclusionsThe accuracy and efficiency were comparable between RG and DIBH treatment for pancreas irradiation. RG is a feasible alternative strategy to DIBH.

Project description:PurposeBeam gating with deep inspiration breath hold (DIBH) usually depends on some external surrogate to infer internal target movement, and the exact internal movement is unknown. In this study, we tracked internal targets and characterized residual motion during DIBH treatment, guided by a surface imaging system, for gastrointestinal cancer. We also report statistics on treatment time.Methods and materialsWe included 14 gastrointestinal cancer patients treated with surface imaging-guided DIBH volumetrically modulated arc therapy, each with at least one radiopaque marker implanted near or within the target. They were treated in 25, 15, or 10 fractions. Thirteen patients received treatment for pancreatic cancer, and one underwent separate treatments for two liver metastases. The surface imaging system monitored a three-dimensional surface with ± 3 mm translation and ± 3° rotation threshold. During delivery, a kilovolt image was automatically taken every 20° or 40° gantry rotation, and the internal marker was identified from the image. The displacement and residual motion of the markers were calculated. To analyze the treatment efficiency, the treatment time of each fraction was obtained from the imaging and treatment timestamps in the record and verify system.ResultsAlthough the external surface was monitored and limited to ± 3 mm and ± 3°, significant residual internal target movement was observed in some patients. The range of residual motion was 3-21 mm. The average displacement for this cohort was 0-3 mm. In 19% of the analyzed images, the magnitude of the instantaneous displacement was > 5 mm. The mean treatment time was 17 min with a standard deviation of 4 min.ConclusionsPrecaution is needed when applying surface image guidance for gastrointestinal cancer treatment. Using it as a solo DIBH technique is discouraged when the correlation between internal anatomy and patient surface is limited. Real-time radiographic verification is critical for safe treatments.

Dataset Information

Fractionated deep-inspiration breath-hold ZTE Compared with Free-breathing four-dimensional ZTE for detecting pulmonary nodules in oncological patients underwent PET/MRI.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets