Gated Radiotherapy Development and its Expansion

Statistical evaluation of the effectiveness of dual amplitude-gated stereotactic body radiotherapy using fiducial markers and lung volume

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Approximately 30% of the fiducial markers demonstrated a low correlation on comparing lung volumes.

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Monitoring of lung volume can achieve stable tracking of lung tumors.

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Dual monitoring by employing the marker and lung volume may possibly avoid the deterioration of monitoring accuracy.

Background and purpose

The low tracking accuracy of lung stereotactic body radiotherapy (SBRT) risks reduced treatment efficacy. We used four-dimensional computed tomography (4DCT) images to determine the correlation between changes in fiducial marker positions and lung volume for lung tumors, and we evaluated the effectiveness of the combined use of these images in lung SBRT.

Materials and methods

Data of 30 patients who underwent fiducial marker placement were retrospectively analyzed. We calculated the motion amplitudes of the center of gravity coordinates of the lung tumor and fiducial markers in each phase and the ipsilateral, contralateral, and bilateral lung volumes using 4DCT. Moreover, we calculated the cross-correlation coefficient between the fiducial marker position and the lung volume changes waveform for the motion amplitude waveform of the lung tumor over three gating windows (all phases, ≤2 mm³, and ≤3 mm³).

Results

Compared with the lung volume, approximately 30 % of the fiducial markers demonstrated a low correlation with the lung tumor. In the ≤2 mm³ and ≤3 mm³ gating windows, the cross-correlation coefficients between the lung tumor and the optimal marker (r > 0.9: 83 % and 86 %) were significantly different for all fiducial markers (r > 0.9: 39 %, 53 %) and the ipsilateral (r > 0.9: 35 % and 40 %), contralateral (r > 0.9: 44 % and 41 %), and bilateral (r > 0.9: 39 % and 45 %) lung volumes.

Conclusions

Some of the fiducial markers showed a low correlation with the lung tumor. This study indicated that the combined use of lung volume monitoring can improve tracking accuracy.

A novel bone suppression algorithm in intensity‐based 2D/3D image registration for real‐time tumour motion monitoring: development and phantom‐based validation

Background

Real‐time tumor motion monitoring (TMM) is a crucial process for intra‐fractional respiration management in lung cancer radiotherapy. Since the tumor can be partly or fully located behind the ribs, the TMM is challenging.

Purpose

The aim of this work was to develop a bone suppression (BS) algorithm designed for real‐time 2D/3D marker‐less TMM to increase the visibility of the tumor when overlapping with bony structures and consequently to improve the accuracy of TMM.

Method

A BS method was implemented in the in‐house developed software for ultrafast intensity‐based 2D/3D tumor registration (Fast Image‐based Registration [FIRE]). The method operates on both, digitally reconstructed radiograph (DRR) and intra‐fractional X‐ray images. The bony structures are derived from computed tomography data by thresholding during ray‐casting, and the resulting bone DRR is subtracted from intra‐fractional X‐ray images to obtain a soft‐tissue‐only image for subsequent tumor registration. The accuracy of TMM utilizing BS was evaluated within a retrospective phantom study with nine different 3D‐printed tumor phantoms placed in the in‐house developed Advanced Radiation DOSimetry (ARDOS) breathing phantom. A 24 mm craniocaudal tumor motion, including rib eclipses, was simulated, and X‐ray images were acquired on the Elekta Versa HD Linac in the lateral and posterior–anterior directions. An error assessment for BS images was evaluated with respect to the ground truth tumor position.

Results

A total error (root mean square error) of 0.87 ± 0.23 mm and 1.03 ± 0.26 mm was found for posterior–anterior and lateral imaging; the mean time for BS was 8.03 ± 1.54 ms. Without utilizing BS, TMM failed in all X‐ray images since the registration algorithm focused on the rib position due to the predominant intensity of this tissue within DRR and X‐ray images.

Conclusion

The BS algorithm developed and implemented improved the accuracy, robustness, and stability of real‐time TMM in lung cancer in a phantom study, even in the case of rib interlude where normal tumor registration fails.

Stereotactic radiotherapy for lung oligometastases

30–60% of cancer patients develop lung metastases, mostly from primary tumors in the colon-rectum, lung, head and neck area, breast and kidney. Nowadays, stereotactic radiotherapy (SRT ) is considered the ideal modality for treating pulmonary metastases.

When lung metastases are suspected, complete disease staging includes a total body computed tomography (CT ) and/or positron emission tomography-computed tomography (PET -CT ) scan. PET -CT has higher specificity and sensitivity than a CT scan when investigating mediastinal lymph nodes, diagnosing a solitary lung lesion and detecting distant metastases. For treatment planning, a multi-detector planning CT scan of the entire chest is usually performed, with or without intravenous contrast media or esophageal lumen opacification, especially when central lesions have to be irradiated. Respiratory management is recommended in lung SRT, taking the breath cycle into account in planning and delivery. For contouring, co-registration and/or matching planning CT and diagnostic images (as provided by contrast enhanced CT or PET-CT ) are useful, particularly for central tumors. Doses and fractionation schedules are heterogeneous, ranging from 33 to 60 Gy in 3–6 fractions. Independently of fractionation schedule, a BED₁₀ > 100 Gy is recommended for high local control rates. Single fraction SRT (ranges 15–30 Gy) is occasionally administered, particularly for small lesions. SRT provides tumor control rates of up to 91% at 3 years, with limited toxicities.

The present overview focuses on technical and clinical aspects related to treatment planning, dose constraints, outcome and toxicity of SRT for lung metastases.

Monitoring Respiratory Motion during VMAT Treatment Delivery Using Ultra-Wideband Radar

The goal of this paper is to evaluate the potential of a low-cost, ultra-wideband radar system for detecting and monitoring respiratory motion during radiation therapy treatment delivery. Radar signals from breathing motion patterns simulated using a respiratory motion phantom were captured during volumetric modulated arc therapy (VMAT) delivery. Gantry motion causes strong interference affecting the quality of the extracted respiration motion signal. We developed an artificial neural network (ANN) model for recovering the breathing motion patterns. Next, automated classification into four classes of breathing amplitudes is performed, including no breathing, breath hold, free breathing and deep inspiration. Breathing motion patterns extracted from the radar signal are in excellent agreement with the reference data recorded by the respiratory motion phantom. The classification accuracy of simulated deep inspiration breath hold breathing was 94% under the worst case interference from gantry motion and linac operation. Ultra-wideband radar systems can achieve accurate breathing rate estimation in real-time during dynamic radiation delivery. This technology serves as a viable alternative to motion detection and respiratory gating systems based on surface detection, and is well-suited to dynamic radiation treatment techniques. Novelties of this work include detection of the breathing signal using radar during strong interference from simultaneous gantry motion, and using ANN to perform adaptive signal processing to recover breathing signal from large interference signals in real time.