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Purpose Assess the accuracy for quantitative measurements of electron density relative to water (ρe/ρe,w), effective atomic number (Zeff) and stopping power ratio relative to water (SPRw) using a dual-layer computed tomography (DLCT) system. Methods and Materials A tissue characterization phantom was scanned using DLCT with varying scanning parameters (i.e., tube voltage, rotation time, CTDIvol, and scanning mode) and different reference materials. Then, electron density ρe/ρe,w and atomic number Zeff images were reconstructed, and their values were determined for each reference materials. Based on these two values, SPRw was calculated. Finally, the percent error (PE) against the theoretical values was calculated for reference materials. Results Significant linear relationships (p 0.85). Conclusions DLCT provides a reasonable accuracy in the measurements of ρe/ρe,w, Zeff and SPRw, and could enhance radiotherapy treatment planning and the subsequent outcomes.

BACKGROUND/AIM To assess the impact of the width of multileaf collimator (MLC) on dose distributions on HyperArc fractionated stereotactic irradiation for multiple (5-10) brain metastases. PATIENTS AND METHODS Twenty-one HyperArc (HA) plans were generated using the high definition (HD) MLC (2.5 mm) to deliver 30-35 Gy in 3-5 fractions (HA-HD). The HyperArc plans using Millennium (ML) MLC (5 mm) were retrospectively generated (HA-ML) using the same planning parameters with HA-HD. Dosimetric parameters between the planning target volume (PTV) and organs at risk (OARs) were compared. RESULTS The conformity index was significantly higher (p

To construct a deep convolutional neural network that generates virtual monochromatic images (VMIs) from single-energy computed tomography (SECT) images for improved pancreatic cancer imaging quality.Fifty patients with pancreatic cancer underwent a dual-energy CT simulation and VMIs at 77 and 60 keV were reconstructed. A 2D deep densely connected convolutional neural network was modeled to learn the relationship between the VMIs at 77 (input) and 60 keV (ground-truth). Subsequently, VMIs were generated for 20 patients from SECT images using the trained deep learning model.The contrast-to-noise ratio was significantly improved (p 0.001) in the generated VMIs (4.1 ± 1.8) compared to the SECT images (2.8 ± 1.1). The mean overall image quality (4.1 ± 0.6) and tumor enhancement (3.6 ± 0.6) in the generated VMIs assessed on a five-point scale were significantly higher (p 0.001) than that in the SECT images (3.2 ± 0.4 and 2.8 ± 0.4 for overall image quality and tumor enhancement, respectively).The quality of the SECT image was significantly improved both objectively and subjectively using the proposed deep learning model for pancreatic tumors in radiotherapy.

Purpose: To evaluate customizing a knowledge-based planning (KBP) model using dosimetric analysis for volumetric modulated arc therapy for pancreatic cancer. Materials and Methods: The first model (M1) using 56 plans and the second model (M2) using 31 plans were created in the first 7 months of the study. The ratios of volume of both kidneys overlapping the expanded planning target volume to the total volume of both kidneys (Voverlap/Vwhole) were calculated in all cases to customize M1. Regression lines were derived from Voverlap/Vwhole and mean dose to both kidneys. The third model (M3) was created using 30 plans which data put them below the regression line. For validation, KBP was performed with the three models on 21 patients. Results: V18 of the left kidney for M1 plans was 7.3% greater than for clinical plans. Dmean of the left kidney for M2 plans was 2.2% greater than for clinical plans. There was no significant difference between all kidney doses in M3 and clinical plans. Dmean of the left kidney for M2 plans was 2.2% greater than for clinical plans. Dmean to both kidneys did not differ significantly between the three models in validation plans with Voverlap/Vwhole lower than average. In plans with larger than average volumes, the Dmean of validation plans created by M3 was significantly lower for both kidneys by 1.7 and 0.9 Gy than with M1 and M2, respectively. Conclusions: Selecting plans to register in a model by analyzing dosimetry and geometry is an effective means of improving the KBP model.

Background Total scalp irradiation presents technical and dosimetric challenges. While reports suggest that HyperArc, a new stereotactic radiosurgery planning technique applied to non-coplanar volumetric-modulated arc therapy (VMAT) technique, is associated with high conformity and rapid dose fall-off, the performance of HyperArc for total scalp irradiation has not been explored. The current study aimed to compare the dosimetric performance of HyperArc plans with those of non-coplanar VMAT plans in angiosarcoma of the scalp. Methods Ten patients with angiosarcoma of the scalp were included in this study. The performance of three different plans administered using TrueBeam Edge were compared: non-coplanar VMAT using flattening filter (FF) beams (VMAT-FF), HyperArc using FF beams (HyperArc-FF), and HyperArc using flattening filter free (FFF) beams (HyperArc-FFF). The dose distribution, dosimetric parameters, and dosimetric accuracy for each of these plans were evaluated. Results The three plans showed no statistically significant differences in target volume coverage, conformity, and homogeneity. The HyperArc-FF and HyperArc-FFF plans provided significantly lower mean brain doses (12.63 ± 3.31 Gy and 12.71 ± 3.40 Gy) than did the VMAT-FF plans (17.11 ± 5.25 Gy). There were almost no differences in sparing the organs at risk between the HyperArc-FF and HyperArc-FFF plans. The HyperArc-FF and HyperArc-FFF plans provided a shorter beam-on time than did the VMAT-FF plan. The 3%/2 mm gamma test pass rates were above 95% for all three plans. Conclusions Our results suggest that the HyperArc plan can be potentially used for radiation therapy of target regions with large and complicated shapes, such as the scalp, and that there are no advantages of using FFF beams.

BACKGROUND: The aim of this study was to clarify factors predicting the performance of knowledge-based planning (KBP) models in volume modulated arc therapy for prostate cancer in terms of sparing the organ at risk (OAR). MATERIALS AND METHODS: In three institutions, each KBP model was trained by more than 20 library plans (LP) per model. To validate the characterization of each KBP model, 45 validation plans (VP) were calculated by the KBP system. The ratios of overlap between the OAR volume and the planning target volume (PTV) to the whole organ volume (V(overlap)/V(whole)) were analyzed for each LP and VP. Regression lines between dose–volume parameters (V(90), V(75), and V(50)) and V(overlap)/V(whole) were evaluated. The mean OAR dose, V(90), V(75), and V(50) of LP did not necessarily match those of VP. RESULTS: In both the rectum and bladder, the dose–volume parameters for VP were strongly correlated with V(overlap)/V(whole) at institutes A, B, and C (R > 0.74, 0.85, and 0.56, respectively). Except in the rectum at institute B, the slopes of the regression lines for LP corresponded to those for VP. For dose–volume parameters for the rectum, the ratios of slopes of the regression lines in VP to those in LP ranged 0.51–1.26. In the bladder, most ratios were less than 1.0 (mean: 0.77). CONCLUSION: For each OAR, each model made distinct dosimetric characterizations in terms of V(overlap)/V(whole). The relationship between dose–volume parameters and V(overlap)/V(whole) of OARs in LP predicts the KBP models’ performance sparing OARs.

Background: The aim of the study was to evaluate analysis criteria for the identification of the presence of rectal gas during volumetric modulated arc therapy (VMAT) for prostate cancer patients by using electronic portal imaging device (EPID)-based in vivo dosimetry (IVD). Materials and methods: All measurements were performed by determining the cumulative EPID images in an integrated acquisition mode and analyzed using PerFRACTION commercial software. Systematic setup errors were simulated by moving the anthropomorphic phantom in each translational and rotational direction. The inhomogeneity regions were also simulated by the I’mRT phantom attached to the Quasar phantom. The presence of small and large air cavities (12 and 48 cm 3 ) was controlled by moving the Quasar phantom in several timings during VMAT. Sixteen prostate cancer patients received EPID-based IVD during VMAT. Results: In the phantom study, no systematic setup error was detected in the range that can happen in clinical ( < 5-mm and < 3 degree). The pass rate of 2% dose difference (DD2%) in small and large air cavities was 98.74% and 79.05%, respectively, in the appearance of the air cavity after irradiation three quarter times. In the clinical study, some fractions caused a sharp decline in the DD2% pass rate. The proportion for DD2% < 90% was 13.4% of all fractions. Rectal gas was confirmed in 11.0% of fractions by acquiring kilo-voltage X-ray images after the treatment. Conclusions: Our results suggest that analysis criteria of 2% dose difference in EPID-based IVD was a suitable method for identification of rectal gas during VMAT for prostate cancer patients.

Purpose To develop a deep learning-based metal artifact reduction (DL-MAR) method using unpaired data and to evaluate its dosimetric impact in head and neck intensity-modulated radiation therapy (IMRT) compared with the water density override method. Methods The data set comprised the data of 107 patients who underwent radiotherapy. Fifteen patients with dental fillings were used as the test data set. The computed tomography (CT) images of the remaining 92 patients were divided into two domains: the metal artifact and artifact-free domains. CycleGAN was used for domain translation. The artifact index of the DL-MAR images was compared with that of the original uncorrected (UC) CT images. The dose distributions of the DL-MAR and UC plans were created by comparing the reference clinical plan with the water density override method (water plan) in each dataset. Dosimetric deviation in the oral cavity from the water plan was evaluated. Results The artifact index of the DL-MAR images was significantly smaller than that of the UC images in all patients (13.2 ± 4.3 vs. 267.3 ± 113.7). Compared with the reference water plan, dose differences of the UC plans were greater than those of the DL-MAR plans. DL-MAR images provided dosimetric results that were more similar to those of the water plan than the UC plan. Conclusions We developed a fast DL-MAR method using CycleGAN for head and neck IMRT. The proposed method could provide consistent dose calculation against metal artifact and improve the efficiency of the planning process by eliminating manual delineation.

Purpose: The aim of this study is to compare the interfractional setup reproducibility of two types of patient immobilization devices for prostate cancer receiving image-guided radiation therapy (IGRT). Materials and Methods: The MOLDCARE (MC) involves hydraulic fixation, whereas the BlueBAG (BB) and Vac-Lock (VL) involve vacuum fixation. For 72 patients, each immobilization device was individually customized during computed tomography (CT) simulation. Before the treatment, bony registration was performed using orthogonal kV images and digitally reconstructed radiographs. The shift of the treatment couch was recorded as a benchmark in the first session. In subsequent sessions, the shifts from the benchmark were measured and analyzed. Soft-tissue registration was performed weekly by cone-beam CT and CT images, and the shifts were measured and analyzed. Results: In the superior-inferior and left-right directions, there were nearly no changes in the overall mean among the immobilization devices. In the anterior-posterior (AP) direction, the overall mean for the MC, BB, and VL were 0.34 ± 1.33, −0.47 ± 1.27, and −1.82 ± 1.65 mm, respectively. The mean shifts along the AP direction were approximately 1 mm more in patients immobilized on the BB and 2.5 mm more in those on the VL, compared to those on the MC, after the twentieth treatment. No significant changes were observed among the patients immobilized on those devices, respectively, in soft-tissue registration. Conclusion: It can be concluded that the settling of the vacuum fixation was caused by air leakage in the latter-half treatment, and the immobilization device type has no effect on the treatment-position reproducibility in IGRT.

We investigated whether methods conventionally used to evaluate patient-specific QA in volumetric-modulated arc therapy (VMAT) for intracranial tumors detect clinically relevant dosimetric errors. VMAT plans with coplanar arcs were designed for 37 intracranial tumors. Dosimetric accuracy was validated by using a 3D array detector. Dose deviations between the measured and planned doses were evaluated by gamma analysis. In addition, modulation complexity score for VMAT (MCSv) for each plan was calculated. Three-dimensional dose distributions in patient anatomy were reconstructed using 3DVH software, and clinical deviations in dosimetric parameters between the 3DVH doses and planned doses were calculated. The gamma passing rate (GPR)/MCSv and the clinical dose deviation were evaluated using Pearson's correlation coefficient. Significant correlation (P

Background: This study aimed to evaluate knowledge-based volume modulated arc therapy (VMAT) plans for oesophageal cancers using a model trained with plans optimised with a different treatment plan...

OBJECTIVES The objective of this study was to assess the objective and subjective qualities of the contrast-enhanced 4-dimensional dual-energy computed tomography using adaptive statistical iterative reconstruction (ASiR) and ASiR-V. METHODS The virtual monochromatic images at 60 keV were reconstructed using filtered back projection, ASiR, and ASiR-V (10%-100%) for 14 patients with pancreatic cancer. The contrast-to-noise ratio (CNR) was calculated, and the subjective measurements were compared based on a 5-point score scale. RESULTS The ASiR-V yielded a significantly higher CNR than ASiR (P < 0.05). The subjective image quality (peak) was significantly improved (P < 0.01) with ASiR (50%) (3.8, 3.5, and 4.0; overall image quality, tumor delineation, and noise, respectively) and with ASiR-V (50%) (3.9, 3.5, and 4.2, respectively) compared with the filtered back projection (3.2, 3.2, and 3.0, respectively). CONCLUSIONS The ASiR-V yielded higher CNR than ASiR and provided the highest subjective scores regarding the overall image quality.

Purpose This study aimed to generate a functional image of the liver using dual-energy computed tomography (DECT) and a functional-image-based stereotactic body radiation therapy plan to minimize the dose to the volume of the functional liver (Vfl). Material and methods A normalized iodine density (NID) map was generated for fifteen patients with liver tumors. The volume of liver with an NID Results FLR showed a significantly strong correlation with FIB-4 (r = −0.71, p 0.05). For Vfl, F-VMAT plans achieved lower V5Gy (122.4 ± 31.7 vs 181.1 ± 57.3 cc), V10Gy (44.4 ± 22.2 vs 98.2 ± 33.3 cc), V15Gy (22.6 ± 20.3 vs 49.8 ± 33.7 cc), V20Gy (11.6 ± 14.1 vs 24.9 ± 25.1 cc), and Dmean (3.9 ± 2.3 vs 5.8 ± 3.0 Gy) values than the C-VMAT plans (p Conclusions The functional image derived from DECT was successfully used, allowing for a reduction in the dose to the Vfl without compromising target coverage.

PURPOSE The aim of this study was to develop a deep learning (DL) method for generating virtual noncontrast (VNC) computed tomography (CT) images from contrast-enhanced (CE) CT images (VNCDL ) and to evaluate its performance in dose calculations for head and neck radiotherapy in comparison with VNC images derived from a dual-energy CT (DECT) scanner (VNCDECT ). METHODS This retrospective study included data for 61 patients who underwent head and neck radiotherapy. All planning CT images were obtained with a single-source DECT scanner (80 and 140 kVp) with rapid kVp switching. The DL-based method used a pair of virtual monochromatic images (VMIs) at 70 keV with and without contrast materials. VMIs without contrast materials were used as reference true noncontrast (TNC) images. Deformable image registration was used between the TNC and CE images. We used the data of 45 patients, chosen randomly, for training (7922 paired images), and data from the other 16 patients as test data. We generated the VNCDL images with a densely connected convolutional network. As the VNCDECT images, we used VMIs with the iodine signal suppressed, reconstructed from the CE images of the 16 test patients. The CT numbers of the tumor, common carotid artery, internal jugular vein, muscle, fat, bone marrow, cortical bone, and mandible of each VNC image were compared with those of the TNC image. The dose of the reference TNC plan was recalculated using the CE, VNCDL , and VNCDECT images. Difference maps of the dose distributions and dose-volume histograms were evaluated. RESULTS The mean prediction time for the VNCDL images was 3.4 s per patient, and the mean number of slices was 204. The absolute differences in CT numbers of the VNCDL images were significantly smaller than those of the VNCDECT images for the bone marrow (8.0 ± 6.5 vs 175.1 ± 40.9 HU; P 1.0% were observed in bone regions. The dose-volume histogram analysis showed that the VNCDL plans yielded the smallest errors for the primary target, although dose differences were

We assessed the effect of collimator angle on the dosimetric parameters for targets and organs at risk (OARs) for collimator-optimized HA (CO-HA) and non-CO-HA (nCO-HA) plans. The nCO-HA and CO-HA plans were retrospectively generated for 26 patients (1 to 8 brain metastases). The dosimetric parameters for planning target volume (homogeneity index [HI]; conformity index [CI]; gradient index [GI]) and for OARs were compared. The modulation complexity score for volumetric modulated arc therapy (MCSV) and monitor units (MUs) were calculated. Doses were measured using the electronic portal imaging device and compared with the expected doses. Dosimetric parameters of the HI, CI, and GI for single (n = 12) and multiple (n = 14) metastases cases were comparable (p > 0.05). For multiple metastases cases, the CO-HA plan provided lower V4Gy, V12Gy, V14Gy, V16Gy for brain tissue compared to the nCO-HA plan (p 0.05). For multiple metastases cases, the CO-HA plan resulted in less complex multileaf collimator (MLC) patterns (MCSV = 0.19 ± 0.04, p 0.05). The collimator optimization in the HA planning reduced doses to brain tissues and improved the treatment efficacy.

Objective: To evaluate and compare the dosimetric plan quality for noncoplanar volumetric arc therapy of single and multiple brain metastases using the linear accelerator-based radiosurgery system HyperArc and a robotic radiosurgery system. Methods: 31 tumors from 24 patients were treated by stereotactic radiosurgery using the CyberKnife system. CT images, structure sets, and dose files were transferred to the Eclipse treatment planning system for the HyperArc system. Dosimetric parameters for both plans were compared. The beam-on time was calculated from the total monitor unit and dose rate. Results: For normal brain tissue, the received volume doses were significantly lower for HyperArc than for CyberKnife_G4 and strongly correlated with the planning target volume (PTV) for cases of single brain metastasis. In addition, the difference in volume dose between CyberKnife_G4 and HyperArc was proportional to the PTV. For multiple brain metastases, no significant difference was observed between the two stereotactic radiosurgery systems, except for high-dose region in the normal tissue. In low dose for brain minus PTV, when the maximum distance among each target was above 8.0 cm, HyperArc delivered higher dose than CyberKnife_G4. The mean ± SDs for the beam-on time were 15.8 ± 5.3 and 5.6 ± 0.8 min for CyberKnife_G4 and HyperArc, respectively (p < .01). Conclusion: HyperArc is best suited for larger targets in single brain metastasis and for smaller inter tumor tumor distances in multiple brain metastases. Advances in knowledge: The performance of HyperArc in comparison with CyberKnife_G4 was depended on defined margin and tumor distances.

To evaluate the effect of the saline flush (SF) technique on the depiction of lesions and the reduction of perivenous artefacts in the head and neck region using dual-energy computed tomography (CT) with virtual monochromatic imaging (VMI).Fifty patients with head and neck cancer were divided into two groups: group A, without a SF and group B, with a 30-ml SF. All images were acquired using fast kilovolt-switching CT (Revolution HD, GE Healthcare, Milwaukee, WI, USA). Contrast-to-noise ratios (CNRs) of the lesions were calculated at VMI energy levels ranging from 40 to 80 keV. Subjective analysis of overall image quality, delineation of lesions, and perivenous artefacts was conducted by two reviewers at both VMI energy level 40 keV and the optimal energy level (which showed optimal CNR by objective analysis).Optimal energy level was 63 keV for group A and 61 keV for group B. At VMI energy levels ranging from 40 to 80 keV, the CNR was higher for group B. The highest subjective overall image quality was shown for group B at the optimal energy level (subjective image quality mean value, 3.40). Subjective delineation of lesions was comparable. The perivenous artefact score was significantly higher for group B (2.44 versus 2.74 [p0.05] at 40 keV, 3.20 versus 3.46 [p0.05] at the optimal energy level).The SF technique results in an improvement of lesion CNR and a reduction of perivenous artefacts in VMI using duel-energy CT, especially at 40 keV.

The aim of this study was to compare three strategies for intensity-modulated radiotherapy (IMRT) for 20 head-and-neck cancer patients. For simultaneous integrated boost (SIB), doses were 66 and 54 Gy in 30 fractions for PTVboost and PTVelective, respectively. Two-phase IMRT delivered 50 Gy in 25 fractions to PTVelective in the First Plan, and 20 Gy in 10 fractions to PTVboost in the Second Plan. Sequential SIB (SEQ-SIB) delivered 55 Gy and 50 Gy in 25 fractions, respectively, to PTVboost and PTVelective using SIB in the First Plan and 11 Gy in 5 fractions to PTVboost in the Second Plan. Conformity indexes (CIs) (mean ± SD) for PTVboost and PTVelective were 1.09 ± 0.05 and 1.34 ± 0.12 for SIB, 1.39 ± 0.14 and 1.80 ± 0.28 for two-phase IMRT, and 1.14 ± 0.07 and 1.60 ± 0.18 for SEQ-SIB, respectively. CI was significantly highest for two-phase IMRT. Maximum doses (Dmax) to the spinal cord were 42.1 ± 1.5 Gy for SIB, 43.9 ± 1.0 Gy for two-phase IMRT and 40.3 ± 1.8 Gy for SEQ-SIB. Brainstem Dmax were 50.1 ± 2.2 Gy for SIB, 50.5 ± 4.6 Gy for two-phase IMRT and 47.4 ± 3.6 Gy for SEQ-SIB. Spinal cord Dmax for the three techniques was significantly different, and brainstem Dmax was significantly lower for SEQ-SIB. The compromised conformity of two-phase IMRT can result in higher doses to organs at risk (OARs). Lower OAR doses in SEQ-SIB made SEQ-SIB an alternative to SIB, which applies unconventional doses per fraction.

Purpose To investigate whether a novel iterative cone-beam computed tomography (CBCT) reconstruction algorithm reduces metal artifacts in head and neck patient images. Method An anthropomorphic phantom and 35 patients with dental metal prostheses or implants were analyzed. All CBCT images were acquired using a TrueBeam linear accelerator and reconstructed with a Feldkamp–Davis–Kress algorithm-based CBCT (FDK-CBCT) and an iterative CBCT algorithm. The mean Hounsfield unit (HU) and standard deviation values were measured on the tongue near the metal materials and the unaffected region as reference values. The artifact index (AI) was calculated. For objective image analysis, the HU value and AI were compared between FDK-CBCT and iterative CBCT images in phantom and clinical studies. Subjective image analyses of metal artifact scores and soft tissue visualizations were conducted using a five-point scale by two reviewers in the clinical study. Results The HU value and AI showed significant artifact reduction for the iterative CBCT than for the FDK-CBCT images (phantom study: 389.8 vs.−10.3 for HU value, 322.9 vs. 96.2 for AI, FDK-CBCT vs. iterative CBCT, respectively; clinical study: 210.3 vs. 69.0 for HU value, 149.6 vs. 70.7 for AI). The subjective scores in the clinical patient study were improved in the iterative CBCT images (metal artifact score: 1.1 vs. 2.9, FDK-CBCT vs. iterative CBCT, respectively; soft tissue visualization: 1.8 vs. 3.6). Conclusions The iterative CBCT reconstruction algorithm substantially reduced metal artifacts caused by dental metal prostheses and improved soft tissue visualization compared to FDK-CBCT in phantom and clinical studies.

The processes of wetting and solvent evaporation in the drying sessile conductive ink droplets formed by inkjet printing are clarified for characterization to be referenced for diverse applications. The electric resistance of the PEDOT:PSS ink line patterns on the nanopaper, the film material of cellulose nanofibers, is affected by the shape and structure of the wire, which are dominated by the elementary process of the droplet drying dynamics. The evaporation flow rate of the ink droplets on the nanopapers decreases at the later stage of the drying process. This is dominated by the decrease in the air–liquid interfacial surface area, while the evaporation flux is roughly constant. The wetting of droplets formed by the inkjet printer is different from the quasi-static droplet placement. The contact angles of sufficiently smaller droplets are smaller, indicating higher apparent wettability because of the momentum effect. This is distinguished from the gravity effect. The conductive particles in the ink help the droplet pinning on the substrate. The nanopapers also tend to pin the droplet peripheries compared to the slide glass. Nevertheless, the radii of both water and the conductive ink droplets on the nanopapers first increase and then decrease later. The initial slow increase in the radius is distinguished from the spreading by the inkjet momentum and is likely to be caused by the capillary effect of the fine texture of the nanopapers. This trend is significant for larger droplets, but the colored dry spots of the ink were smaller than the maximum droplet radii during drying.

Objective: Determination of the optimal energy level of virtual monochromatic image (VMI) for brain metastases in contrast-enhanced dual-energy CT (DECT) for radiosurgery and assessment of the subjective and objective image quality of VMI at the optimal energy level. Methods: 20 patients (total of 42 metastases) underwent contrast-enhanced DECT. Spectral image analysis of VMIs at energy levels ranging from 40 to 140 keV in 1 keV increments was performed to determine the optimal VMI (VMIopt) as the one corresponding to the highest contrast-to-noise ratio (CNR) between brain parenchyma and the metastases. The objective and subjective values of VMIopt were compared to those of the VMI with 120 kVp equivalent, defined as reference VMI (VMIref, 77 keV). The objective measurement parameters included mean HU value and SD of tumor and brain parenchyma, absolute lesion contrast (LC), and CNR. The subjective measurements included five-point scale assessment of “overall image quality” and “tumor delineation” by three radiation oncologists. Results: The VMI at 63 keV was defined as VMIopt. The LC and CNR of VMIopt were significantly (p < 0.01) higher than those of VMIref (LC: 37.4 HU vs 24.7 HU; CNR: 1.1 vs 0.8, respectively). Subjective analysis rated VMIopt significantly (p < 0.01) superior to VMIref with respect to the overall image quality (3.2 vs 2.9, respectively) and tumor delineation (3.5 vs 2.9, respectively). Conclusion: The VMI at 63 keV derived from contrast-enhanced DECT yielded the highest CNR and improved the objective and subjective image quality for radiosurgery, compared to VMIref. Advances in knowledge: This paper investigated for the first time the optimal energy level of VMI in DECT for brain metastases. The findings will lead to improvement in tumor visibility with optimal VMI and consequently supplement accuracy delineation of brain metastases.

Objective The aim of the study was to compare the accuracy of quantification of iodine and Hounsfield unit (HU) values on virtual monochromatic imaging (VMI) using dual-layer computed tomography (DLCT) and fast kilovolt-switching computed tomography (FKSCT). Materials and methods This study was performed in 2 phantoms (large and small) using 16 rods representing different materials (iodine, calcium, blood, and adipose tissue) with different dimensions and concentrations. The absolute percentage errors (absolute ratio of measurement error to true iodine concentration) for iodine concentration and HU value on VMI at 50, 70, and 100 keV were compared between DLCT and FKSCT. The Mann-Whitney U test was used to assess statistical significance. Results Overall, the absolute percentage errors for iodine concentration and HU value on VMI were smaller for DLCT than for FKSCT. Conclusions Overall, the accuracy of iodine and HU values was higher for DLCT than for FKSCT.

PURPOSE A contrast-enhancing agent is imperative for the accurate target delineation of pancreatic tumors. This study demonstrates the potential use of treatment planning for patients with pancreatic tumors based on the water density image (WDI) generated by dual-energy computed tomography (DECT). METHODS Tissue characterization and multi-energy phantom scanning were performed through DECT and the physical characteristics of the WDI and a virtual monochromatic image (VMI) were assessed. The measured and the corresponding theoretical electron density relative to water (RED) and mass density (MD) were compared. Treatment plans based on the WDI (TPWDI ) and VMI (TPVMI ) were compared for 22 pancreatic cancer patients who underwent contrast-enhanced DECT scan. RESULTS The total absolute difference in the HU value between the conventional 120 kVp images and the VMI was the smallest at the energy level of 77 keV (3.3 HU), and the VMI at 77 keV was used for subsequent analysis. The difference between the measured and theoretical values of RED and MD for iodine using the VMI (>15%) was larger than that using WDI (

OBJECTIVE The objective of this study was to assess the accuracy of the quantitative measurements obtained using dual-energy computed tomography with metal artifact reduction software (MARS). METHODS Dual-energy computed tomography scans (fast kV-switching) are performed on a phantom, by varying the number of metal rods (Ti and Pb) and reference iodine materials. Objective and subjective image analyses are performed on retroreconstructed virtual monochromatic images (VMIs) (VMI at 70 keV). RESULTS The maximum artifact indices for VMI-Ti and VMI-Pb (5 metal rods) with MARS (without MARS) were 17.4 (166.7) and 34.6 (810.6), respectively; MARS significantly improved the mean subjective 5-point score (P < 0.05). The maximum differences between the measured Hounsfield unit and theoretical values for 5 mg/mL iodine and 2-mm core rods were -42.2% and -68.5%, for VMI-Ti and VMI-Pb (5 metal rods), respectively, and the corresponding differences in the iodine concentration were -64.7% and -73.0%, respectively. CONCLUSIONS Metal artifact reduction software improved the objective and subjective image quality; however, the quantitative values were underestimated.

The aim of the this study was to validate the use of an average intensity projection (AIP) for volumetric-modulated arc therapy for stereotactic body radiation therapy (VMAT-SBRT) planning for a moving lung tumor located near the diaphragm. VMAT-SBRT plans were created using AIPs reconstructed from 10 phases of 4DCT images that were acquired with a target phantom moving with amplitudes of 5, 10, 20 and 30 mm. To generate a 4D dose distribution, the static dose for each phase was recalculated and the doses were accumulated by using the phantom position known for each phase. For 10 patients with lung tumors, a deformable registration was used to generate 4D dose distributions. Doses to the target volume obtained from the AIP plan and the 4D plan were compared, as were the doses obtained from each plan to the organs at risk (OARs). In both phantom and clinical study, dose discrepancies for all parameters of the dose volume (D(min), D(99), D(max), D(1) and D(mean)) to the target were

BACKGROUND AND PURPOSE The accurate delineation of pancreatic tumor with respiratory motion is challenging. This study demonstrates the application of contrast-enhanced four-dimensional dual-energy computed tomography (CE-4D-DECT) for tumor delineation and assesses the objective and subjective image quality. MATERIAL AND METHODS Twelve patients underwent CE-4D-DECT, and quantitative spectral analysis was performed on the resulting virtual monochromatic images (VMI) to determine the optimal VMI (O-VMI) with the highest contrast-to-noise ratio (CNR). The objective value of the CNR between pancreatic parenchyma and tumor, and the subjective measurement with five-point scale were compared between O-VMI, standard VMI (S-VMI, 77 keV) and single energy CT (SECT, 120 kVp). RESULTS The CNR was the highest in the VMI at 60 keV, and the corresponding CNR in the O-VMI (3.4) was significantly higher (p

Because it is imperative for understanding the performance of dual-energy computed tomography scanner to determine clinical diagnosis, we aimed to assess the accuracy of quantitative measurements using dual-energy computed tomography with fast kilovoltage switching.Quantitative measurements were performed for 16 reference materials (physical density, 0.965-1.550 g/cmFor high-density material, the maximum differences in Hounsfield unit values in the virtual monochromatic images at 50, 70, and 100 keV were -176.2, 61.0, and -35.2 HU, respectively, and the standard deviations over short- and long-term periods were 11.1, 6.1, and 3.5 HU at maximum. The accuracy of the Hounsfield unit measurement at 50 and 70 keV was significantly higher (P 0.05) with higher radiation output and smaller phantom size. The difference in the iodine and calcium measurements in the large phantom were up to -2.6 and -60.4 mg/mL for iodine (5 mg/mL with 2-mm diameter) and calcium (300 mg/mL) materials, and the difference was improved with a small phantom. Metal artifact reduction software improved subjective image quality; however, the quantitative values were significantly underestimated (P 0.05) (-49.5, -26.9, and -15.3 HU for 50, 70, and 100 keV, respectively; -1.0 and -17 mg/mL for iodine and calcium concentration, respectively) compared to that acquired without a metal material.The accuracy of quantitative measurements can be affected by material density and the size of the object, radiation output, phantom size, and the presence of metal materials.

The volume of targets to which a high radiation dose can be delivered is limited for pancreatic radiotherapy. We assessed changes in movements of pancreatic tumours between simulation and treatment and determined compensatory margins.For 23 patients, differences in implanted fiducial marker motion magnitude (MMM) and mean marker position (MMP) between four-dimensional CT and cone-beam CT were measured. Subsequently, residual uncertainty was simulated after no action level (NAL) and extended no action level (eNAL) protocols were adopted.With no correction, respective 95th percentile of MMM were 4.5 mm, 6.2 mm and 16.0 mm and systematic (random) errors of MMP were 2.8 mm (3.3 mm), 3.2 mm (2.0 mm) and 5.9 mm (4.0 mm) in the left-right (L-R), anteroposterior (A-P) and superoinferior (S-I) directions, so that large margins were required (L-R, 10.5 mm; A-P, 11.7 mm; and S-I, 24.8 mm). NAL reduced systematic errors of MMP, but resultant margins remained large (L-R, 8.0 mm; A-P, 9.6 mm; and S-I, 18.1 mm). eNAL compensated for time trends and obtained minimal margins (L-R, 6.7 mm; A-P, 6.7 mm; and S-I, 15.2 mm).Motion magnitude and position of pancreatic tumours during simulation are frequently not representative of that during treatment. eNAL compensated for systematic interfractional position change and would be a practical approach for improving targeting accuracy. Advances in knowledge: Considerably large margins, especially in the S-I direction, were required to compensate for intrafractional motion and interfractional position changes of the pancreatic tumour. An application of eNAL was an effective strategy to diminish these margins.

Several reports have dealt with correlations of late rectal toxicity with rectal dose-volume histograms (DVHs) for high dose levels. There are 2 techniques to assess rectal volume for reception of a specific dose: relative-DVH (R-DVH, %) that indicates relative volume for a vertical axis, and absolute-DVH (A-DVH, cc) with its vertical axis showing absolute volume of the rectum. The parameters of DVH vary depending on the rectum delineation method, but the literature does not present any standardization of such methods. The aim of the present study was to evaluate the effects of different delineation methods on rectal DVHs. The enrollment for this study comprised 28 patients with high-risk localized prostate cancer, who had undergone intensity-modulated radiation therapy (IMRT) with the prescription dose of 78 Gy. The rectum was contoured with 4 different methods using 2 lengths, short (Sh) and long (Lg), and 2 cross sections, rectum (Rec) and rectal wall (Rw). Sh means the length from 1 cm above the seminal vesicles to 1 cm below the prostate and Lg the length from the rectosigmoid junction to the anus. Rec represents the entire rectal volume including the rectal contents and Rw the rectal volume of the area with a wall thickness of 4 mm. We compared dose-volume parameters by using 4 rectal contour methods for the same plan with the R-DVHs as well as the A-DVHs. For the high dose levels, the R-DVH parameters varied widely. The mean of V 70 for Sh-Rw was the highest (19.4%) and nearly twice as high as that for Lg-Rec (10.4%). On the contrary, only small variations were observed in the A-DVH parameters (4.3, 4.3, 5.5, and 5.5 cc for Sh-Rw, Lg-Rw, Sh-Rec, and Lg-Rec, respectively). As for R-DVHs, the parameters of V 70 varied depending on the rectal lengths (Sh-Rec vs Lg-Rec: R = 0.76; Sh-Rw vs Lg-Rw: R = 0.85) and cross sections (Sh-Rec vs Sh-Rw: R = 0.49; Lg-Rec vs Lg-Rw: R = 0.65). For A-DVHs, however, the parameters of Sh rectal A-DVHs hardly changed regardless of differences in rectal length at all dose levels. Moreover, at high dose levels (V 70 ), the parameters of A-DVHs showed less dependence on rectal cross sections (Sh-Rec vs Sh-Rw: R = 0.66; Lg-Rec vs Lg-Rw: R = 0.59). This study showed that A-DVHs were less dependent on the delineation methods than R-DVHs, especially for evaluating the rectal dose at higher dose levels. It can therefore be assumed that, in addition to R-DVHs, A-DVHs can be used for evaluating rectal toxicity.