Reconstruction of a time‐averaged midposition CT scan for radiotherapy planning of lung cancer patients using deformable registrationa)

The purpose of CT simulation in radiotherapy is to acquire patient geometrical information and to build a patient geometrical model for treatment planning. Errors in patient model caused by motion artifacts will influence all treatment fractions and therefore should be handled carefully. Due to the tumor respiratory motion, the captured tumor position and shape can be heavily distorted. The distortions along the axis of motion could result in either a lengthening or shortening of the target. The center of the imaged target can be displaced by as much as the amplitude of the motion.A newly developed technique that can reduce motion artifacts and provide patient geometry throughout the whole breathing cycle is called respiration‐correlated or 4D CT scan. The basic idea for 4D CT scan is that, at every position of interest along patient's long axis, images are over‐sampled and each image is tagged with breathing phase information. After the scan is done, images are sorted based on the corresponding breathing phase signals. Thus, many 3D CT sets are obtained, each corresponding to a particular breathing phase, and together constitutes a 4D CT set that covers that the whole breathing cycle. 4D CT scan has been developed at various institutions with slightly different flavors. In this lecture, we will provide an overview of various implementations of 4D CT scan.4D CT scan can be used to account for respiratory motion to generate images with less distortion than 3D CT scan. 4D images also contain respiratory motion information of tumor and organs that is not available in a 3D CT image. This technology can be used for respiratory‐gated treatment to identify the patient‐specific phase of minimum tumor motion, determine residual tumor motion within the gate interval, and compare treatment plans at different phases. It can also be used for non‐gated treatment planning to define ITV by combining gross tumor volume at all breathing phases or using a method called maximum intensity projection. Of course 4D CT will also play a vital role in the futuristic 4D radiotherapy where the tumor is tracked dynamically during the treatment using multi‐leaf collimator.Existing problems for 4D CT scan include the increased imaging dose, CT tube heating, and data management. More importantly, one has to keep in mind that 4D CT scan is not really 4D. Temporal information is mapped into one breathing cycle. Irregular respiration will cause artifacts in 4D CT images. Patient coaching can improve the regularity of breathing pattern and thus reduce the residual artifacts. However this issue still deserves further studies.Educational Objectives:1. Understand the origin and magnitude of motion artifacts in free breathing helical CT scan.2. Understand how 4D CT scan works.3. Understand how 4D CT can be used in radiotherapy.4. Understand the remaining artifacts in 4D CT scan and possible future improvements.

The purpose of CT simulation in radiotherapy is to acquire patient geometrical information and to build a patient geometrical model for treatment planning. Errors in patient model caused by motion artifacts will influence all treatment fractions and therefore should be handled carefully. Due to the tumor respiratory motion, the captured tumor position and shape can be heavily distorted. The distortions along the axis of motion could result in either a lengthening or shortening of the target. The center of the imaged target can be displaced by as much as the amplitude of the motion. A newly developed technique that can reduce motion artifacts and provide patient geometry throughout the whole breathing cycle is called respiration‐correlated or 4D CT scan. The basic idea for 4D CT scan is that, at every position of interest along patient's long axis, images are over‐sampled and each image is tagged with breathing phase information. After the scan is done, images are sorted based on the corresponding breathing phase signals. Thus, many 3D CT sets are obtained, each corresponding to a particular breathing phase, and together constitutes a 4D CT set that covers that the whole breathing cycle. 4D CT scan has been developed at various institutions with slightly different flavors. In this lecture, we will provide an overview of various implementations of 4D CT scan. 4D CT scan can be used to account for respiratory motion to generate images with less distortion than 3D CT scan. 4D images also contain respiratory motion information of tumor and organs that is not available in a 3D CTimage. This technology can be used for respiratory‐gated treatment to identify the patient‐specific phase of minimum tumor motion, determine residual tumor motion within the gate interval, and compare treatment plans at different phases. It can also be used for non‐gated treatment planning to define ITV by combining gross tumor volume at all breathing phases or using a method called maximum intensity projection. Of course 4D CT will also play a vital role in the futuristic 4D radiotherapy where the tumor is tracked dynamically during the treatment using multi‐leaf collimator. Existing problems for 4D CT scan include the increased imagingdose,CT tube heating, and data management. More importantly, one has to keep in mind that 4D CT scan is not really 4D. Temporal information is mapped into one breathing cycle. Irregular respiration will cause artifacts in 4D CTimages. Patient coaching can improve the regularity of breathing pattern and thus reduce the residual artifacts. However this issue still deserves further studies. Educational Objectives: 1. Understand the origin and magnitude of motion artifacts in free breathing helical CT scan. 2. Understand how 4D CT scan works. 3. Understand how 4D CT can be used in radiotherapy. 4. Understand the remaining artifacts in 4D CT scan and possible future improvements.

The question remains regarding the dosimetric impact of intrafraction motion in 3D breast treatment. This study was conducted to investigate this issue utilizing the 4DCT scan. The 4D and helical CT scan sets were acquired for 12 breast cancer patients. For each of these patients, based on the helical CT scan, a conventional 3D conformal plan was generated. The breast treatment was then simulated based on the 4DCT scan. In each phase of the 4DCT scan, dose distribution was generated with the same beam parameters as the conventional plan. A software package was developed to compute the cumulative dose distribution from all the phases. Since the intrafraction organ motion is reflected by the 4DCT images, the cumulative dose computed based on the 4DCT images should be closer to what the patient received during treatment. Various dosimetric parameters were obtained from the plan and 4D cumulative dose distribution for the target volume and heart, and were compared to deduce the motion-induced impacts. The studies were performed for both whole breast and partial breast treatment. In the whole breast treatment, the average intrafraction motion induced changes in D95, D90, V100, V95, and V90 of the target volume were -5.4%, -3.1%, -13.4%, -5.1%, and -3.2%, respectively, with the largest values at -26.2%, -14.1%, -91.0%, -15.1%, and -9.0%, respectively. Motion had little impact on the Dmax of the target volume, but its impact on the Dmin of the target volume was significant. For left breast treatment, the motion-induced Dmax change to the heart could be negative or positive, with the largest increase at about 6 Gy. In partial breast treatment, the only non-insignificant impact was in the Dmin of the CTV (ranging from -15.2% to 11.7%). The results showed that the intrafraction motion may compromise target dose coverage in breast treatments and the degree of that compromise was correlated with motion magnitude. However, the dosimetric impact of the motion on the heart dose may be limited.

Purpose: Internal target volumes (ITVs) have been determined using both breath-hold CT scans (BHCTs) and four-dimensional CT (4DCT) to assess the extent of tumor motion during normal respiration. The purpose of this work is to compare the differences in tumor excursion when measured with BHCT and 4DCT. Method and Materials: All 4DCT and BHCT datasets in this study were acquired as a part of the radiotherapy simulation process using a commercial 4DCT system (Discovery ST, GE Healthcare, Waukesha, WI). Respiratory tracking was accomplished using a commercial system (RPM, Varian Medical Systems, Palo Alto, CA). A visual prompt from this system was displayed to patients to assist them in holding their breath at the correct level during BHCTs. The locations of the tumors with respect to a reference dataset (4DCT end-expiration) was determined using a rigid-body cross-correlation algorithm that found the location on each dataset that best matched the region of the physician-determined gross tumor volume (GTV) on the reference dataset. The patient did not move between the 4DCT and BHCT scans, thus differences in tumor location were due to tumor motion rather than bulk patient motion. Results: For 20 patients, the average difference in displacement of the GTV between BHCT and 4DCT scans was 5 mm at end-inspiration and 3 mm at end-expiration with maximum differences of 12 mm and 10 mm respectively. GTV motion on BHCTs was always greater than or equal to the motion on the 4DCT. The direction of tumor motion was also found to be different between 4DCT and BHCT images with the average difference in the vector angles being 14°. Conclusion: The results of this work suggests that patients being treated during normal breathing should be simulated during normal breathing (4DCT) and those to be treated using a breath-hold technique should be simulated using BHCT.

Purpose: Four‐dimensional (4D) imaging techniques can be used to obtain (respiration) artifact‐free CT images of the thorax. However, its use in radiotherapy is limited since clinical treatment planning systems are currently not able to use the full 4D data. The purpose of this study was to reconstruct a representative single 3D CT scan from the 4D data set (with tumor closest to the mean position) for use in radiotherapy planning of lung tumors to enable reduction of treatment error margins. Method and Materials: After acquisition of the 4D CT scan (10 frames), the tumor is manually segmented (roughly) in the first frame and automatically (gray‐value) registered to the tumor in the subsequent frames. This gives the motion of the tumor during the respiratory cycle in 3D. Subsequently, from the cranio‐caudal (CC) tumor motion curve, the mean tumor position and its corresponding mid‐ventilation (MV) time‐percentage are calculated. The CT scan for planning is reconstructed at this time‐percentage. As indication of the merit of this concept, its effect on margins from CTV to PTV and on the PTV volume was calculated covering respiratory motion, respiratory baseline variation and setup errors (systematic and random). Results: Based on 13 patients, the worst tumor position accuracy (with respect to the mean tumor position) in the mid‐ventilation CT scan occurred in the anterior‐posterior direction: −0.7±0.8 mm (due to hysteresis). For these patients, the errors in conventional free‐breathing CT were estimated to be 0±3.4 mm (CC) and 0±1.4 mm (AP). The mid‐ventilation concept resulted in margin reduction up to 45% and a PTV volume reduction up to 35%. Conclusion: The mid‐ventilation concept, based on tumor motion, is a simple method to obtain an artifact‐free CT scan with smaller systematic errors compared to conventional CT scans. Significant reduction of the PTV volume can be achieved.

Background Initial imaging work-up using radiography and CT arthrography sometimes can be insufficient to identify a scapholunate (SL) instability (SLI) in patients suspected of having SL ligament tears. Purpose To determine the diagnostic performance of four-dimensional (4D) CT in the identification of SLI and apply the findings to patients suspected of having SLI and with inconclusive findings on radiographs and CT arthrograms. Materials and Methods This prospective single-center study enrolled participants suspected of having SLI (recent trauma, dorsal pain, positive Watson test results, decreased grip strength) between March 2015 and March 2020. Participants with wrist fractures, substantial joint stiffness, or history of wrist surgery were excluded. Each participant underwent radiography, CT arthrography, and 4D CT on the same day. Participants were divided into three groups: those with no SLI, those with SLI, and those with inconclusive results. SL gap and radioscaphoid and lunocapitate angle were measured using semiautomatic quantitative analysis of 4D CT images by two independent readers. Receiver operating characteristic curves were used to evaluate the diagnostic performance of 4D CT. Thresholds were determined with the Youden index and were applied to the inconclusive group. Results Of the 150 included participants (mean age, 41 years ± 14 [SD]; 102 male, 48 female), there were 63 with no SLI, 48 with SLI, and 39 with inconclusive results. The maximum value and range of SL gap measurements on 4D CT scans showed high sensitivity (83% [40 of 48] and 90% [43 of 48], respectively) and high specificity (95% [59 of 62] and 81% [50 of 62], respectively) in the identification of SLI. At least one of these parameters was abnormal on 4D CT scans in 17 of 39 (44%) participants in the inconclusive group, and 10 of 17 (59%) participants had confirmed SLI. In the 22 participants in the inconclusive group with no indication of SLI at 4D CT, follow-up showed no evidence of SLI in 10 (45%) and enabled confirmation of SLI via arthroscopy in three (14%). Conclusion Scapholunate gap measurements on kinematic 4D CT scans enabled correct identification of SLI in 59% of participants with inconclusive results on conventional images. ClinicalTrials.gov registration no. NCT02401568 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Demehri and Ibad in this issue.

IntroductionAccurate glenoid component placement is crucial for anatomic (TSA) or reverse (RSA) total shoulder arthroplasty. Preoperative glenoid assessment by using CT scans with or without planning software seems to be the established method to plan implant positions. MRI scans can also display the glenoid bone for preoperative assessment while reducing radiation exposure. Therefore, the objective of this study was to manually assess the glenoid version and inclination in 2D MRI and CT scans in cases with degenerative shoulder pathologies. The results were compared to those of an automated 3D planning software to validate the imaging modality for preoperative glenoid assessment. MethodsMRI and CT scans of 146 patients (n=41 aTSA; n=105 RSA) were included in this retrospective, single-center study. Glenoid version and inclination were measured manually according to Friedman et al and Maurer et al on CT and MRI scans by two observers. Subsequently, the results were compared to the automated measurements performed by a planning software. A repeated-measures analysis of variance (ANOVA) was performed to compare the measured angles and interobserver and intraobserver reliability was calculated using the intraclass correlation coefficients. The level of significance was set p<0.05. ResultsThe average glenoid inclination measured in CT scans was 7.94°±7.33°, in MRI scans 8.56°±7.34° and in automated planning software 7.87°±7.60°. The ANOVA analysis revealed significant differences in mean inclination between 2D MRI and 2D CT (p<0.0005) and between MRI and automated software (p=0.011). No significant difference was found between 2D CT scans and automated planning software (p=1.000). Mean glenoid version measured in 2D CT scans was -7.94°±10.86°, in 2D MRI scans it was -8.04°±10.80° and -8.32°±11.53° by the automated planning software. There was no significant difference in between measurement methods (p = 0.339). Interobserver error analysis showed no statistical differences between the two observers. All measurements had excellent intraobserver reliability. ConclusionPreoperative assessment of glenoid version and inclination is crucial in ensuring precise implant positioning and orientation in TSA and RSA. This study observed a significant level of concordance between manual and automated measuring techniques utilizing MRI and CT scans. Mean glenoid inclination exhibited a statistically significant difference of less than 1° across the assessment modalities and no difference for glenoid version was noted. It seems to be questionable if this finding is clinically relevant. MRI may serve as a viable and safe option for assessing glenoid morphology, version and inclination if CT scans are not available.

Background. In lung cancer radiotherapy, planning on the midventilation (MidV) bin of a four-dimensional (4D) CT scan can reduce the systematic errors introduced by respiratory tumour motion compared to conventional CT. In this study four different methods for MidV bin selection are evaluated. Material and methods. The study is based on 4DCT scans of 19 patients with a total of 23 peripheral lung tumours having peak-to-peak displacement ≥ 5 mm in at least one of the left-right (LR), anterior-posterior (AP) or cranio-caudal (CC) directions. For each tumour, the MidV bin was selected based on: 1) visual evaluation of tumour displacement; 2) rigid registration of tumour position; 3) diaphragm displacement in the CC direction; and 4) carina displacement in the CC direction. Determination of the MidV bin based on the displacement of the manually delineated gross tumour volume (GTV) was used as a reference method. The accuracy of each method was evaluated by the distance between GTV position in the selected MidV bin and the time-weighted mean position of GTV throughout the bins (i.e. the geometric MidV error). Results. Median (range) geometric MidV error was 1.4 (0.4–5.4) mm, 1.4 (0.4–5.4) mm, 1.9 (0.5–6.9) mm, 2.0 (0.5–12.3) mm and 1.1 (0.4–5.4) mm for the visual, rigid registration, diaphragm, carina, and reference method. Median (range) absolute difference between geometric MidV error for the evaluated methods and the reference method was 0.0 (0.0–1.2) mm, 0.0 (0.0–1.7) mm, 0.7 (0.0–3.9) mm and 1.0 (0.0–6.9) mm for the visual, rigid registration, diaphragm and carina method. Conclusion. The visual and semi-automatic rigid registration methods were equivalent in accuracy for selecting the MidV bin of a 4DCT scan. The methods based on diaphragm and carina displacement cannot be recommended without modifications.

Objective To conduct a computer simulation to evaluate the discrepancy between the cumulative doses calculated by four-dimensional computed tomography (4DCT) images and 4DCT scans (for real-time respiratory motions) due to the patient’s irregular breathing. Methods A series of digital phantoms were generated from a patient’s 4DCT images to simulate 4DCT images and 4DCT scans (for real-time respiratory motions) resulting from various irregular breathing curves. A six-field intensity-modulated radiotherapy plan was generated. Two cumulative doses in the target were calculated. The first one, named Dall, was calculated by tracking the point displacements in the target manifested on the 4DCT images; the second one, named D4D, was calculated based on the point displacements along the whole breathing motion during 4DCT scanning. Dose discrepancy between D4D and Dall was calculated to evaluate the correlation between breathing pattern and dose discrepancy in the target. Results The dose discrepancy in the target was correlated with mean motion excursion and the standard deviation of motion excursion.ΔDmin(ΔD99) in the target increased from 2.39%(2.04%) to 11.91%(5.24%) as the mean motion excursion increased from 5 mm to 15 mm, and increased from 5.93%(2.15%) to 14.65%(5.01%) as the standard deviation of motion excursion increased from 15% to 45% of the mean motion excursion. When the mean period increased from 3 s to 5 s or the standard deviation of period increased from 10% to 40% of the mean period, ΔDmin(ΔD99) in the target was greater than 6.0%(2.0%), but less than 9.0%(3.0%). When the target diameter was 2 cm, 3 cm, and 4 cm, ΔDmin(ΔD99) in the target was 11.88%(5.50%), 6.91%(2.42%), and 7.53%(3.62%), respectively. Conclusions There is a large discrepancy between the cumulative doses calculated using 4DCT images and 4DCT scans (for real-time respiratory motions) when the patient has irregular breathing. This dose discrepancy depends on mean motion excursion and the standard deviation of motion excursion, but has little relationship with mean period, the standard deviation of period, and tumor volume. Key words: Tomography, X-ray computed; Respiratory-induced motion; Accumulative dose

Four-dimensional (4D) CT imaging is a central part of current treatment planning workflows in 4D radiotherapy (RT). However, clinical 4D CT image data often suffer from severe artifacts caused by insufficient projection data coverage due to the inability of current commercial 4D CT imaging protocols to adapt to breathing irregularity. We propose an intelligent sequence mode 4D CT imaging protocol (i4DCT) that builds on online breathing curve analysis and respiratory signal-guided selection of beam on/off periods during scan time in order to fulfill projection data coverage requirements. i4DCT performance is evaluated and compared to standard clinical sequence mode 4D CT (seq4DCT) and spiral 4D CT (spiral4DCT) approaches. i4DCT consists of three main blocks: (a) an initial learning period to establish a patient-specific reference breathing cycle representation for data-driven i4DCT parameter selection, (b) online respiratory signal-guided sequence mode scanning (i4DCT core), (c) rapid breathing record analysis and quality control after scanning to trigger potential local rescanning (i4DCT rescan). Based on a phase space representation of the patient's breathing signal, i4DCT core implements real-time analysis of the signal to appropriately switch on and off projection data acquisition even during irregular breathing. Performance evaluation was based on 189 clinical breathing records acquired during spiral 4D CT scanning for RT planning (data acquisition period: 2013-2017; Siemens Somatom with Varian RPM system). For each breathing record, i4DCT, seq4DCT, and spiral4DCT scanning protocol variants were simulated. Evaluation measures were local projection data coverage ; number of local projection data coverage failures; and number of patients with coverage failures; average beam on time as a surrogate for imaging dose and total patient on table time as the time between first and last beam on signal. Using i4DCT, mean inhalation and exhalation projection data coverage increased significantly compared to standard spiral 4D CT scanning as applied for the original clinical data acquisition and conventional 4D CT sequence scanning modes. The improved projection data coverage translated into a reduction of coverage failures by 89% without and 93% when allowing for a rescanning at up to five z-positions compared to spiral scanning and between 76% and 82% without and 85% and 89% with rescanning when compared to seq4DCT. Similar numbers were observed for . Simultaneously, i4DCT (without rescanning) reduced the beam on time on average by 3%-17% compared to standard spiral 4D CT. In turn, the patient on table time increased by between 35% and 66%. Allowing for rescanning led on average to additional 5.9 s beam on and 10.6 s patient on table time. i4DCT outperformed currently implemented clinical fixed beam on period 4D CT scanning approaches by means of a significantly smaller data coverage failure rate without requiring additional beam on time compared to, for example, conventional spiral 4D CT protocols.

Four‐dimensional computed tomography (4D CT), also called respiratory correlated CT, was first published on, and commercially available in 2003. Since then this technology has gained widespread acceptance and clinical use. The 4D CT acquisition concept is relatively simple: acquire CT scans synchronized with the respiratory cycle such that sufficient data exists to reconstruct a volumetric image at or near a number of respiratory phases. There are a variety of commercial implementations of the basic acquisition concept. There are several limitations of 4D CT. One problem is artifacts. Though 4D CT was developed to account for the deleterious effects of respiratory motion on 3D image acquisition techniques, irregular respiratory motion causes artifacts in 4D scans. Free breathing, unlike the cardiac cycle on which the technology is based, is typically irregular and artifacts can be found in nearly all 4D CT scans with current technology. There are several strategies to deal with this irregular signal: (1) improve the regularity of the signal itself, using audio‐visual biofeedback tools, (2) during imaging only acquire data during regular cycles and (3) use post‐processing methods to reduce artifacts. Another limitation of 4D CT, at least in its application to radiotherapy, is that the time interval during which images are acquired over, ∼5 seconds per anatomic location for a ∼1 minute total scan time, is a small sample of the respiratory induced anatomic changes occurring over a course of radiotherapy, which can be between a single fraction to several weeks. Despite these limitations 4D CT has been found to be very useful for a number of applications in radiotherapy planning. 4D CT can be used for measuring target motion, and motion inclusive, respiratory gated and target tracking treatment scenarios. Fully utilizing 4D CTimages for treatment planning requires deformable image registration algorithms for automatic contour propagation and dose summation. For this application, several studies have shown that current algorithms have acceptable geometric performance with respect to expert observers. The dosimetric impact of the geometric uncertainty of deformable registration algorithms appears low. A more recent development in 4D CT is the extension to 4D cone beam CT (4D CBCT) which offers the ability for pre‐treatment anatomic position and motion verification. This application is a major innovation and will increase treatment accuracy. Residual uncertainties from anatomic changes between the time of imaging and time of treatment have been observed, and intra‐fraction position monitoring is desired to complement 4D CBCT. Educational Objectives: 1. Understand the principles of 4D CTimage acquisition and reconstruction. 2. Understand the limitations of current 4D CT technology. 3. Understand the ongoing developments in 4D CT and 4D CBCTimaging. 4. Understand the application of 4D CT to treatment planning.

To compare the position, displacement, degree of inclusion (DI) and matching index (MI) of the gross tumor volume (GTV) for peripheral lung cancer based on 4-dimensional CT (4D CT) and 3-dimensional CT (3D CT) assisted with active breathing control (ABC). Eighteen patients with peripheral lung cancer underwent 4D CT simulation scan during free breathing and 3D CT simulation scans in end-inspiratory hold (CTEIH) and end-expiratory hold (CTEEH) in turn. The 4D CT images from each respiratory cycle were sorted into 10 phases. phase 0 was defined as end-inspiratory phase (CT0), and phase 50 was defined as end-expiratory phase (CT50). The GTVs were delineated separately on CT0, CT50, CTEIH and CTEEH images, and then GTV0, GTV50, GTVEIH and GTVEEH were constructed, respectively. The median distances between the centroids of GTV0 and GTVEIH, GTV50 and GTVEEH were 3.9 mm and 3.4 mm in all patients, 3.2 mm and 3.1 mm in the upper lobe group, and 5.0 mm and 4.7 mm in the lower lobe group, respectively. In the upper lobe group, the GTV0 and GTVEIH were 65.9% and 63.1%, and the median mutual DIs of GTV50 and GTVEEH were 67.5%, 63.1%, respectively. In the lower lobe group, the GTV0 and GTVEIH were 35.3% and 21.4%, and the median mutual DIs of GTV50 and GTVEEH were 27.8% and 24.8%, respectively. In the upper lobe group, the median MI of GTV0 and GTVEIH was 0.5, and the median MI of GTV50 and GTVEEH was 0.6. In the lower lobe group, the median MI of GTV0 and GTVEIH was 0.2, and the median MI of GTV50 and GTVEEH was 0.3. Whether in the upper or lower lobe groups, all the differences between displacements of centroid positions of GTVEIH and GTVEEH (ABC displacement) and GTV0 and GTV50 (4D displacement ) were <1 mm in three dimensional directions (all P>0.05). The target displacement of tumors based on 3D CT scanning in end-inspiratory hold and end-expiration hold can be used to construct internal target volume instead of that based on 4D CT scanning in extreme phase for peripheral lung cancers, but spatital mismatches of GTVs are obvious between extreme phases in 4D CT and corresponding phases in 3D CT assisted with ABC, especially for tumors of smaller volume and with larger motion amplitude.

Objective To investigate the target volume displacements of primary thoracic esophageal carcinoma (TEC) based on repeated enhanced four-dimensional computed tomography (4DCT) scans during fractionated radiotherapy.Methods Twenty-nine patients with TEC underwent enhanced 4DCT before and in the 10th,20th,and 30th fractions of radiotherapy to delineate the gross tumor volumes (GTVs) and internal gross tumor volumes (IGTVs) in all phases.The GTV displacements of upper,middle,or lower TEC in three-dimensional directions in each time of 4DCT were compared,and the GTV displacements of upper,middle,or lower TEC in the same direction in all 4DCT scans were also compared.The changes in the centroid positions and volumes of IGTV during radiotherapy were determined.Results For the patients with middle TEC,significant differences were found between the GTV displacements in leftright (LR) direction,anterior-posterior (AP) direction,and superor-inferior (SI) direction when 4DCT was performed before or in the 20th fraction of radiotherapy (P =0.000-0.016),and significant differences were found between the GTV displacements in SI direction and LR and AP directions when 4DCT was performed in the 10th fraction of radiotherapy (P =0.000-0.006).For the patients with lower TEC,there were significant differences between the GTV displacements in SI direction and AP direction when 4DCT was performed before or in the 10th or 20th fraction of radiotherapy (P =0.004-0.013).There were no significant differences between the GTV displacements in the same direction in all 4DCT scans (P =0.102-0.823).There were no significant changes in the centroid positions of IGTV during radiotherapy (P =0.6 8 9-0.999),and the most significant decreases in IGTV volumes were seen in the 20th fraction of radiotherapy (P =0.012-0.029).Conclusions Under free breathing,the GTV displacement of upper,middle,or lower TEC in the same direction shows no significant changes in different 4DCT scans during radiotherapy;the IGTV volumes decrease significantly in the 20th fraction of radiotherapy,but there are no significant changes in the centroid positions of IGTV during radiotherapy. Key words: Esophageal neoplasm/ radiotherapy; Tomography, X-ray computed, four-dimensional; Gross tumor volume; Intrafraction target displacement

In many patients respiratory motion causes motion artifacts in CT images, thereby inhibiting precise treatment planning and lowering the ability to target radiation to tumors. The 4D Phantom, which includes a 3D stage and a 1D stage that each are capable of arbitrary motion and timing, was developed to serve as an end-to-end radiation therapy QA device that could be used throughout CT imaging, radiation therapy treatment planning, and radiation therapy delivery. The dynamic accuracy of the system was measured with a camera system. The positional error was found to be equally likely to occur in the positive and negative directions for each axis, and the stage was within 0.1 mm of the desired position 85% of the time. In an experiment designed to use the 4D Phantom's encoders to measure trial-to-trial precision of the system, the 4D Phantom reproduced the motion during variable bag ventilation of a transponder that had been bronchoscopically implanted in a canine lung. In this case, the encoder readout indicated that the stage was within 10 microns of the sent position 94% of the time and that the RMS error was 7 microns. Motion artifacts were clearly visible in 3D and respiratory-correlated (4D) CT scans of phantoms reproducing tissue motion. In 4D CT scans, apparent volume was found to be directly correlated to instantaneous velocity. The system is capable of reproducing individual patient-specific tissue trajectories with a high degree of accuracy and precision and will be useful for end-to-end radiation therapy QA.

Can Mediastinal Nodal Mobility Explain the Low Yield Rates for Transbronchial Needle Aspiration Without Real-Time Imaging?