Smart mA Research Articles

Virtual unenhanced images derived from dual-energy computed tomography for assessing bone mineral density and detecting osteoporosis.

The early detection and treatment of osteoporosis can help prevent osteoporosis-related fractures, especially in patients who undergo enhanced computed tomography (CT) scans for disease diagnosis or evaluation of treatment outcomes. Although Hounsfield unit (HU) measurement of the vertebral body has been shown to have a strong positive correlation with bone mineral density (BMD), the contrast media will impact the CT value of the vertebral body and decrease the accuracy. This study is aimed to examine the distinctions in vertebral body CT attenuation measurement on true unenhanced (TUE) and virtual unenhanced (VUE) images generated from triphasic enhanced dual-energy CT (DECT) scans and to determine the feasibility of assessing BMD and detecting osteoporosis on VUE images as compared to quantitative CT (QCT). A total of 235 patients underwent abdominal CT examinations that included unenhanced (with 120 kVp and Smart mA) and triphasic enhanced DECT scans. The BMD and CT attenuation values of the L1-L2 vertebrae were measured on TUE and VUE images reconstructed from the triphasic enhanced CT. The differences and associations between TUE and VUE generated from triphasic enhanced CT were analyzed. The diagnostic performances of HU measurements obtained from TUE and VUE images were evaluated using receiver operating characteristic curve. The BMD and HU measurements of the vertebrae showed good interobserver repeatability on both TUE and VUE images (all intercorrelation coefficients >0.92). The CT attenuation values of L1 and L2 and their average value showed no statistically significant difference among the triphasic VUE images (F=0.121, F=0.061, F=0.090; all P values >0.05) but were significantly lower than those obtained from the TUE images. HU measurements in both the TUE and triphasic VUE images, along with the reference BMD derived from QCT, demonstrated a strong positive correlation (rTUE =0.981, rVUEa =0.966, rVUEv =0.962, rVUEd =0.964; all P values <0.05), with excellent diagnostic performance for the diagnoses of osteoporosis and osteopenia (all areas under curve >0.95). The Bland-Altman scatter plot exhibited good agreement, as the deviations between the reference BMD and the calculated BMD were evenly distributed around 0. Although the attenuation values of the vertebrae on the VUE images were underestimated compared to those on the TUE images, the HU measurement on VUE image was effective in assessing BMD and detecting osteoporosis and osteopenia with good diagnostic performance.

Reducing both radiation and contrast doses for overweight patients in coronary CT angiography with 80-kVp and deep learning image reconstruction

PurposeTo investigate the use of an 80-kVp tube voltage combined with a deep learning image reconstruction (DLIR) algorithm in coronary CT angiography (CCTA) for overweight patients to reduce radiation and contrast doses in comparison with the 120-kVp protocol and adaptive statistical iterative reconstruction (ASIR-V). MethodsOne hundred consecutive CCTA patients were prospectively enrolled and randomly divided into a low-dose group (n = 50) with 80-kVp, smart mA for noise index (NI) of 36 HU, contrast dose rate of 18 mgI/kg/s and DLIR and 60 % ASIR-V and a standard-dose group (n = 50) with 120-kVp, smart mA for NI of 25 HU, contrast dose rate of 32 mgI/kg/s and 60 % ASIR-V. The radiation and contrast dose, subjective image quality score, attenuation values, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared. ResultsThe low-dose group achieved a significant reduction in the effective radiation dose (1.01 ± 0.45 mSv vs 1.85 ± 0.40 mSv, P < 0.001) and contrast dose (33.69 ± 3.87 mL vs 59.11 ± 5.60 mL, P < 0.001) compared to the standard-dose group. The low-dose group with DLIR presented similar enhancement but lower noise, higher SNR and CNR and higher subjective quality scores than the standard-dose group. Moreover, the same patient comparison in the low-dose group between different reconstructions showed that DLIR images had slightly and consistently higher CT values in small vessels, indicating better defined vessels, much lower image noise, higher SNR and CNR and higher subjective quality scores than ASIR-V images (all P < 0.001). ConclusionsThe application of 80-kVp and DLIR allows for significant radiation and dose reduction while further improving image quality in CCTA for overweight patients.

High-strength deep learning image reconstruction in coronary CT angiography at 70-kVp tube voltage significantly improves image quality and reduces both radiation and contrast doses

To explore the use of 70-kVp tube voltage combined with high-strength deep learning image reconstruction (DLIR-H) in reducing radiation and contrast doses in coronary CT angiography (CCTA) in patients with body mass index (BMI) < 26kg/m2, in comparison with the conventional scan protocol using 120 kVp and adaptive statistical iterative reconstruction (ASIR-V). A total of 100 patients referred to CCTA were prospectively enrolled and randomly divided into two groups: low-dose group (n = 50) with 70 kVp, Smart mA for noise index (NI) of 36HU, contrast dose rate of 16mgI/kg/s, and DLIR-H, and conventional group (n = 50) with 120kV, Smart mA for NI of 25HU, contrast dose rate of 32mgI/kg/s, and 60%ASIR-V. Radiation and contrast dose, subjective image quality score, and objective image quality measurement (image noise, contrast-noise-ratio (CNR), and signal-noise-ratio (SNR) for vessel) were compared between the two groups. Low-dose group used significantly reduced contrast dose (23.82 ± 3.69mL, 50.6% reduction) and radiation dose (0.75 ± 0.14mSv, 54.5% reduction) compared to the conventional group (48.23 ± 6.38mL and 1.65 ± 0.66mSv, respectively) (all p < 0.001). Both groups had similar enhancement in vessels. However, the low-dose group had lower background noise (23.57 ± 4.74 HU vs. 35.04 ± 8.41 HU), higher CNR in RCA (48.63 ± 10.76 vs. 29.32 ± 5.52), LAD (47.33 ± 10.20 vs. 29.27 ± 5.12), and LCX (46.74 ± 9.76 vs. 28.58 ± 5.12) (all p < 0.001) compared to the conventional group. The use of 70-kVp tube voltage combined with DLIR-H for CCTA in normal size patients significantly reduces radiation dose and contrast dose while further improving image quality compared with the conventional 120-kVp tube voltage with 60%ASIR-V. •The combination of 70-kVp tube voltage and high-strength deep learning image reconstruction (DLIR-H) algorithm protocol reduces approximately 50% of radiation and contrast doses in coronary computed tomography angiography (CCTA) compared with the conventional scan protocol. •CCTA of normal size (BMI < 26kg/m2) patients acquired at sub-mSv radiation dose and 24mL contrast dose through the combination of 70-kVp tube voltage and DLIR-H algorithm achieves excellent diagnostic image quality with a good inter-rater agreement. •DLIR-H algorithm shows a higher capacity of significantly reducing image noise than adaptive statistical iterative reconstruction algorithm in CCTA examination.

Experimental study on the effect of adaptive statistical iterative reconstruction algorithms on image quality and radiation dose in paranasal sinus CT

Objective To explore the effect of pre- and post-adaptive statistical iterative reconstruction-Veo (ASiR-V) on image quality and radiation dose in paranasal sinus CT, and to find the best combinations. Methods One head specimen was scanned with the routine spiral CT scanning parameters [noise index (NI)=8] and different levels of pre-ASiR-V (0—100%, with an interval of 10%). The images were reconstructed with different post-ASiR-V (0—100%, with an interval of 10%) for the bone algorithm and standard algorithm. All of 242 thin-layer images of paranasal sinuses were obtained. The region of interest (ROI) was selected to measure the CT value to calculate the contrast to noise ratio (CNR) and figure of merit (FOM). The volume CT dose index (CTDIvol) and Smart mA were recorded. The linear regression was conducted to analyze the relationship between CTDIvol, SmartmA, CNR and FOM. And with the same pose-ASiR-V level, the CNR of images which reconstructed by bone and soft algorithms were compared with pair-wise t test. The image quality was subjectively evaluated by three independent experienced radiologists using a 4-point scale (4 was the best). Results As the pre-ASiR-V levels (0—100%) increased, Smart mA and CTDIvol were reduced with a linear negative correlation (r=-0.981, -0.976, both P<0.001). The Smart mA decreased by 72.05% and CTDIvol by 71.22%. Keeping the same pre-ASiR-V level,the CNR increased with the increase of post-ASiR-V level (for the bone algorithm images:R2=0.976, 0.992, 0.982, 0.982, 0.975, 0.975, 0.979, 0.996, 0.952, 0.978, 0.965;for the standard algorithm images: R2=0.944, 0.990, 0.988, 0.993, 0.996, 0.987, 0.984, 0.996, 0.996, 0.990, 0.965).Under the same level of post-ASiR-V, the CNR and FOM fluctuated with the pre-ASiR-V level (for the bone algorithm images:R2=0.335, 0.341, 0.344, 0.364, 0.385, 0.405, 0.418, 0.429, 0.455, 0.474, 0.516; for the standard algorithm images: R2=0.223, 0.278, 0.327, 0.285, 0.309, 0.329, 0.325, 0.346, 0.360, 0.390, 0.380). All subjective image quality could meet the diagnostic requirements (the score≥3). Conclusion At NI=8, for the bone algorithm, the best combination is 80% pre-ASiR-V and 100% post-ASiR-V; for the standard algorithm, the best iteration combination is 100% and 100%. The appropriate choice of pre- and post-ASiR-V levels in paranasal sinus CT scan can effectively reduce the radiation dose under the premise of maintaining the image quality that meets the diagnostic needs. Key words: Paranasal sinuses; Tomography, X-ray computed; Radiation dosage; Image processing, computer-assisted; Image quality

Assessment of radiation dose and iodine load reduction in head-neck CT angiography using two scan protocols with wide-detector.

To compare image quality, radiation dose, and iodine intake of head-neck CT angiography (CTA) acquired by wide-detector with the gemstone spectral imaging (GSI) combination with low iodine intake or routine scan protocol. Three hundred patients who had head-neck CTA were enrolled and divided into three groups according to their BMI values: group A (18.5 kg/m2 ≦ BMI <24.9 kg/m2), group B (24.9 kg/m2 ≦ BMI <29.9 kg/m2) and group C (29.9 kg/m2 ≦ BMI ≦ 34.9 kg/m2) with 100 patients in each group. Patients in each group were randomly divided into two subgroups (n = 50) namely, A1, A2, B1, B2, C1 and C2. The patients in subgroups A1, B1 and C1 underwent GSI with low iodine intake (270 mgI/ml, 50 ml) and combined with the ASiR-V algorithm. Other patients underwent three dimensional (3D) smart mA modulation with routine iodine intake (350 mgI/ml, 60 ml). Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of all images were calculated after angiography. Images were then subjectively assessed using a 5-point scale. CT dose index of volume and dose-length product (DLP) was converted to the effective dose (ED) and then compared. The mean CT values, SNR, CNR and subjective image quality in subgroups A2, B2 and C2 are significantly lower than in subgroups A1, B1, and C1 (P < 0.01), respectively. The ED values in subgroup A1, B1, and C1 are 55.18%, 61.89%, and 69.64% lower than those in A2, B2, and C2, respectively (P < 0.01). The total iodine intakes in subgroups A1, B1, and C1 are 35.72% lower than those in subgroups A2, B2, and C2. The gemstone spectral imaging with monochromatic images at 53-57 keV combined with ASiR-V algorithm allows significant reduction in iodine load and radiation dose in head-neck CT angiography than those yielded in routine scan protocol. It also enhances signal intensity of head-neck CTA and maintains image quality.

A feasibility study of pulmonary nodule detection by ultralow-dose CT with adaptive statistical iterative reconstruction-V technique

PurposeTo evaluate the clinical value of ultralow-dose CT (ULDCT) with adaptive statistical iterative reconstruction-V (ASiR-V) in the detection of pulmonary nodules in a Chinese population. MethodOne hundred eighty-eight patients (16.41 ≤ BMI ≤ 29.87 kg/m2) with pulmonary nodules detected on low-dose chest CT (LDCT) underwent local ULDCT at the center of the chosen nodule with a scan length of 3 cm. LDCT was performed using the Assist kV (120/100 kV)/Smart mA mode and at 120 kV/2.8 mAs for ULDCT. After scanning, CT images were reconstructed with ASiR-V 50%. For both scans, nodule diameters were measured and reference standards were established for the presence and types of lung nodules found on LDCT. The sensitivity of ULDCT was compared against the standard, and logistic regression analysis was used to determine the independent predictors for nodule detection. ResultsCompared with LDCT (0.93 ± 0.32 mSv), a 89.7% dose decrease was seen with ULDCT, for which the calculated effective dose was 0.096 ± 0.006 mSv (P < 0.001). LDCT showed 188 nodules, including 123 solid and 65 subsolid nodules. The overall sensitivity for nodule detection in ULDCT was 90.4% (170/188), and 98.2% (54/55) for nodules ≥ 6 mm. In multivariate analysis, nodule types and diameters were independent predictors of sensitivity (P < 0.05). However, patients’ BMI had no effect on nodule detection (P > 0.05). ConclusionsULDCT can be used in the management of pulmonary nodules for people with BMI ≤ 30 kg/m2 at 10% radiation dose of LDCT.

The investigation of dose and image quality of chest computed tomography using different combinations of noise index and adaptive statistic iterative reconstruction level.

Background:Computed tomography (CT) automatic tube current modulation (ATCM) systems and iterative reconstruction (IR) play an important role in CT radiation dose optimization. How the two can best be used together is one of the challenges faced by radiology professionals.Aim:To determine optimum settings of ATCM noise index (NI) together with adaptive statistic iterative reconstruction (ASIR) for a general electric (GE) scanner that aims to achieve similar image quality to the standard protocol used in the hospital (Smart mA technique with NI of 11.57 and 30% ASIR reconstruction) with a lower dose.Methods:Different NI and ASIR levels were set for scans of a phantom. Objective image quality assessments in terms of noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), low-contrast detectability (LCD), and modulation transfer function (MTF) were carried out in an anthropomorphic chest and a Catphan 700 phantom. Subjective image quality assessment was also performed with five readers to confirm whether the image quality of the new protocols was adequate.Result and Conclusion:SNR and CNR increased with the strength of ASIR, and decreased with higher NI settings. The MTF improved slightly for higher dose levels and from filtered back projection (FBP) to higher strength of ASIR. LCD improved with ASIR compared to FBP and with higher strengths of ASIR. Qualitative scoring ranged between 3.0 and 4.6. A moderate degree of reliability was found between scoring. Use of NI 15.04 with 70% ASIR can reduce dose by 41% compared to the standard protocol of NI 11.57 with 30% ASIR without degradation of image quality.

41 Evaluation of the dose delivered to patients during a bone scan coupled with an examination CT scan and practice optimization

Introduction An inventory of the use of CT coupled to SPECT and of CT patient exposure is carried out in our nuclear medicine department for bone scan examinations. Our goal is to optimize our CT scans based on medical needs in this context. Methods 50 patients who underwent a SPECT/CT bone scan on Discovery NM/CT 670 (GE Healthcare) from January 2017 to March 2018 are included in the study. For these acquisitions, CT parameters are: 2.5 mm slices, pitch of 1.375, rotation time 0.7 s, voltage 120 kV. The current is modulated according to the corpulence in z (AutomA®) and x,y (Smart mA®) with a maximum current (mAsmax) of 110 mA. The noise index (NI) is set to 26.9. Patient weight, height, activity of 99mTc administered (8 MBq/kg), anatomical area explored and the Dose Length Product (DLP) are recorded. For each patient, the absorbed dose delivered by the radionuclide, the effective dose delivered by the CT and the total effective dose are calculated. Several CT acquisitions are then performed with CT phantoms, varying the NI, pitch and mAsmax. The image quality of the CT obtained is analyzed in terms of spatial resolution, contrast and noise. Results For the anatomical area “head and neck (HN 157.1 and 260.4 mGy.cm and injected activity is 526; 625 and 573 MBq, respectively. The total effective dose is 3.6; 6.1 and 7.0 mSv. The CT exam contributes to: 3.6%; 36% and 48.9% of the total effective dose, respectively in average. For phantom acquisitions, only the reduction of the NI to 20 and the increase of the mAmax to 140 mA allowed a clear improvement of the image quality. Conclusions In the context of bone scintigraphy, CT for the H&N areas contributes little to the total dose delivered to the patient. However, its contribution is not negligible for the AP and TAP area. There are no diagnostic reference levels for SPECT/CT bone scan. However, the DLP recorded for the TAP is 2.1 times lower than the guide value proposed by the SFMN for PET/CT TAP (550 mGy.cm). After discussion with the medical team, an improvement in CT contrast in the soft tissues is desirable in an oncological context. For this purpose, we proposed to change the NI to 20 and increase the mAmax to 140 mA. This implies an increase in Computed Tomography Dose Index by a factor of 1.5. It is also proposed to adjust the voltage according to the patient’s body mass index. Following the implementation of these recommendations, it will be necessary to assess the dose and image quality indexes again. A similar study is underway for the other SPECT/CT exams performed in the department.

CT pulmonary angiography using organ dose modulation with an iterative reconstruction algorithm and 3D Smart mA in different body mass indices: image quality and radiation dose.

To investigate the differences in imaging quality and radiation dose in CT pulmonary angiography (CTPA) by organ dose modulation and 3D Smart mA modulation in different body mass indices (BMIs) with an adaptive statistical iterative reconstruction (ASiR-V) algorithm. Three hundred female patients who underwent CTPA were equally divided into three groups: A (18.5kg/m2 ≦ BMI < 24.9kg/m2), B (24.9kg/m2 ≦ BMI < 29.9kg/m2) and C (29.9kg/m2 ≦ BMI≦ 34.9kg/m2). The groups were randomly subdivided into two subgroups (n = 50): A1-A2, B1-B2 and C1-C2. The patients in subgroups A1, B1 and C1 underwent organ dose modulation with the ASiR-V algorithm. The other patients underwent 3D Smart mA modulation. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of all images were calculated after CTPA. Images were then subjectively evaluated using a 5-point scale. The volume CT dose index and dose-length product (DLP) were recorded and their means calculated. The DLP was converted to the effective dose (ED). In group A, the SNR, CNR, and subjective image scores showed no statistical differences (P > 0.05). The ED in subgroup A1 was 33.36% lower than that in A2. In group B and C, the variables showed no significant differences between the subgroups B1 and B2 (P > 0.05), and the subgroups C1 and C2 (P > 0.05), respectively. The ED in subgroup B1 and C1 was 36.15 and 38.22% lower than that in B2 and C2, respectively. Using organ dose modulation and applying the ASiR-V algorithm can more effectively reduce the radiation dose in CTPA than in 3D Smart mA modulation, while maintaining image quality.

Diagnostic performance of 256-row detector coronary CT angiography in patients with high heart rates within a single cardiac cycle: a preliminary study

To evaluate the image quality and diagnostic performance of coronary computed tomography angiography (CCTA) in patients with high heart rate within a single cardiac cycle using a 256-row detector CT system. Eighty-four consecutive symptomatic patients (mean age 60.4±9.1 years, 52 men) with suspected coronary artery disease and heart rate ≥75 beats/min undergoing CCTA and invasive coronary angiography (ICA) were enrolled retrospectively. Prospective electrocardiography (ECG)-triggered volume CCTA within a single cardiac cycle was performed using a 256-row, 16cm detector CT system (Revolution CT, GE Healthcare) using automated tube voltage selection (kV Assist selecting 100 or 120kV) and tube current modulation (Smart mA) techniques, with images reconstructed using 50% of adaptive statistical iterative reconstruction-V (ASiR-V). The image quality of coronary artery segments was evaluated by two reviewers using a four-point scale based on 18-segment model. The diagnostic accuracy of CCTA to detect ≥50% stenosis on ICA was analysed. The sensitivity, specificity, positive predictive value, and negative predictive value of CCTA to detect a ≥50% diameter stenosis on ICA were calculated from the chi-squared test of the contingency table on a per-segment, per-vessel, and per-patient basis. The body mass index was 25.6±3.5kg/m2; the HR was 82.8±7.9 beats/min, and the mean HR variability was 8.3±4.8 beats/min. All of the coronary artery segments, 98.9% (1044/1056) of coronary segments were rated as having diagnostic image quality. The diagnostic sensitivity, specificity, positive predictive value, and negative predictive value of CCTA, were 91.5%, 95.6%, 77.7%, and 98.5% on a per-segment basis; 95.2%, 93.5%, 87%, and 97.7% on a per-vessel basis; 100%, 85.7%, 93.3%, and 100% on per-patient basis, respectively. The mean effective dose was 1.9±1mSv. CCTA using a 256-detector row CT with the snapshot freeze (SSF) technique can be performed in a single cardiac cycle with acquisition of images with high diagnostic value and low radiation dose in patients with high heart rates.

Noise indices adjusted to body mass index and an iterative reconstruction algorithm maintain image quality on low-dose contrast-enhanced liver CT.

Since body mass index (BMI) affects medical imaging quality or noise due to penetration of the radiation through bodies with varying sizes, this study aims to investigate and determine the optimal BMI-adjusted noise index (NI) setting on the contrast-enhanced liver CT scans obtained using 3D Smart mA technology with adaptive statistical iterative reconstruction (ASIR 2.0) algorithm. A total of 320 patients who had contrast-enhanced liver CT scans were divided into two equal-sized groups: A (18.5 kg/m2≤BMI<24.9 kg/m2) and B (24.9 kg/m2 ≤ BMI ≤34.9 kg/m2). The two groups were randomly divided into four subgroups with an NI of 11, 13, 15, and 17. All images were reconstructed with 50% ASIR 2.0. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated after the late arterial, portal venous, and equilibrium phases were completed. Images were evaluated by two radiologists using a subjective 0 -5 scale. Mean CT dose index of volume, dose-length product, and effective dose (ED) were calculated and compared using one-way ANOVA. In group A, the best-quality images obtained at the lowest ED were scanned at an NI of 15 in the late arterial phase, and at an NI of 17 in the portal venous and equilibrium phases. In group B, the best results were obtained at an NI of 13 in the late arterial phase, and at an NI of 15 in the portal venous and equilibrium phases. Adjusting NI and iterative reconstruction algorithm based on body mass index can help improve image quality on contrast-enhanced liver CT scans, even at low radiation dose.

SU‐G‐206‐08: How Should Focal Spot Be Chosen for Optimized CT Imaging with Dose Modulation?

Purpose:To choose the preferred focal spot for achieving optimized CT image quality with balanced tube heating considerations.Methods:An anthropomorphic pelvic phantom was scanned using a GE Discovery CT750 HD at 120 and 140kVp, 0.8s rotation time, and pitch of 0.984. “Smart mA” was enabled to simulate a routine abdomen–pelvis CT scan. Permissible mA values at 120 and 140 kVp were obtained from the Serial Load Rating table (for mimicking a busy CT clinical operation) in the scanner Technical Reference Manual. At each kVp station and two Noise Index levels, the mA Upper Limit was set above/below the permissible mA values. Scanned mA values and focal spot (FS) used were obtained from the DICOM header of each image, and the FS‐mA relationship was analyzed. For visual confirmation beyond recorded FS information, a CatPhan with a fat‐ring attached for mimicking patient size/shape was scanned at 120kVp. A group of radiologists/physicists compared a pair of CatPhan images qualitatively. Lastly, a number of patient cases were evaluated to confirm the FS‐mA relationship.Results:When preset Upper Limit values were above the permissible mA values, the Large FS (labeled 1.2) was used in scans, even if the maximum scanned mA values were much lower than the permissible values at both 120 and 140 kVp. Otherwise the Small FS (labeled 0.7) was used. Visual evaluation of the high contrast module of CatPhan and additional analysis of patient cases further confirmed that the preset Upper Limit determines which focal spot is to be used, not the actual maximum mA value to be scanned.Conclusion:Specific FS can be selected by setting up appropriate mA Upper Limit in a protocol. CT protocols could be optimized by selecting appropriate FS for improving patient image quality, especially benefiting the small size and pediatric patients.

SU‐F‐T‐403: Impact of Dose Reduction for Simulation CT On Radiation Therapy Treatment Planning

Purpose:To investigate the feasibility of applying ALARA principles to current treatment planning CT scans. The study aims to quantitatively verify lower dose scans does not alter treatment planning.Method:Gammex 467 tissue characterization phantom with inserts of 14 different materials was scanned at seven different mA levels (30∼300 mA). CT numbers of different inserts were measured. Auto contouring for bone and lung in treatment planning system (Pinnacle) was used to evaluate the effect of CT number accuracy from treatment planning aspect, on the 30 and 300 mA‐scanned images. A head CT scan intended for a 3D whole brain radiation treatment was evaluated. Dose calculations were performed on normal scanned images using clinical protocol (120 kVP, Smart mA, maximum 291 mA), and the images with added simulating noise mimicking a 70 mA scan. Plan parameters including isocenter, beam arrangements, block shapes, dose grid size and resolution, and prescriptions were kept the same for these two plans. The calculated monitor units (MUs) for these two plans were compared.Results:No significant degradation of CT number accuracy was found at lower dose levels from both the phantom scans, and the patient images with added noise. The CT numbers kept consistent when mA is higher than 60 mA. The auto contoured volumes for lung and cortical bone show 0.3% and 0.12% of differences between 30 mA and 300 mA respectively. The two forward plans created on regular and low dose images gave the same calculated MU, and 98.3% of points having &lt;1% of dose difference.Conclusion:Both phantom and patient studies quantitatively verified low dose CT provides similar quality for treatment planning at 20–25% of regular scan dose. Therefore, there is the potential to optimize simulation CT scan protocol to fulfil the ALARA principle and limit unnecessary radiation exposure to non‐targeted tissues.

Radiation dose calculations for CT scans with tube current modulation using the approach to equilibrium function.

The approach to equilibrium function has been used previously to calculate the radiation dose to a shift-invariant medium undergoing CT scans with constant tube current [Li, Zhang, and Liu, Med. Phys. 39, 5347-5352 (2012)]. The authors have adapted this method to CT scans with tube current modulation (TCM). For a scan with variable tube current, the scan range was divided into multiple subscan ranges, each with a nearly constant tube current. Then the dose calculation algorithm presented previously was applied. For a clinical CT scan series that presented tube current per slice, the authors adopted an efficient approach that computed the longitudinal dose distribution for one scan length equal to the slice thickness, which center was at z = 0. The cumulative dose at a specific point was a summation of the contributions from all slices and the overscan. The dose calculations performed for a total of four constant and variable tube current distributions agreed with the published results of Dixon and Boone [Med. Phys. 40, 111920 (14pp.) (2013)]. For an abdomen/pelvis scan of an anthropomorphic phantom (model ATOM 701-B, CIRS, Inc., VA) on a GE Lightspeed Pro 16 scanner with 120 kV, N × T = 20 mm, pitch = 1.375, z axis current modulation (auto mA), and angular current modulation (smart mA), dose measurements were performed using two lines of optically stimulated luminescence dosimeters, one of which was placed near the phantom center and the other on the surface. Dose calculations were performed on the central and peripheral axes of a cylinder containing water, whose cross-sectional mass was about equal to that of the ATOM phantom in its abdominal region, and the results agreed with the measurements within 28.4%. The described method provides an effective approach that takes into account subject size, scan length, and constant or variable tube current to evaluate CT dose to a shift-invariant medium. For a clinical CT scan, dose calculations may be performed with a water-containing cylinder whose cross-sectional mass is equal to that of the subject. This method has the potential to substantially improve evaluations of patient dose from clinical CT scans, compared to CTDIvol, size-specific dose estimate (SSDE), or the dose evaluated for a TCM scan with a constant tube current equal to the average tube current of the TCM scan.

Volumetric evaluation of hepatic tumors: multi-vendor, multi-reader liver phantom study

To compare liver lesion volume measurement on multiple 3D software platforms using a liver phantom. An anthropomorphic phantom constructed with ten liver lesions of varying size, attenuation, and shape with known volume and long axis measurement was scanned (120 kVp, 80-440 smart mA, NI 12). DICOM data were uploaded to five commercially available 3D visualization systems and manual tumor volume was obtained by three-independent readers. Accuracy and reproducibility of linear and volume measurements were compared. The two most promising systems were then compared with an additional prototype system by two readers using both manual and semi-automated measurement with similar comparison between linear and volume measures. Measurements were performed on 5- and 1.25-mm data sets. Inter- and intra-observer variability was also assessed. Overall mean % volume error on the five commercially available software systems (averaging all ten liver lesions among all three readers) was 8.0% ± 7.5%, 13.7% ± 11.2%, 14.2% ± 15.2%, 16.4% ± 14.8 %, and 16.9% ± 13.8%, varying almost twofold across vendor. Moderate inter-observer variability was present. Volume measurement was slightly more accurate than linear measurement, but linear measurement was more reproducible across readers and systems. On the two "best" systems, the manual measurement method was more accurate than the automated method (p = 0.001). The prototype system demonstrated superior semi-automated assessment, with a mean % volume error of 5.3% ± 4.1% (vs. 17.8% ± 11.1% and 31.5% ± 19.7%, p < 0.001), with improved inter- and intra-observer variability. Accuracy and reproducibility of volume assessment of liver lesions varies significantly by vendor, which has important implications for clinical use.

Low dose interpolated average CT for thoracic PET/CT attenuation correction using an active breathing controller

The temporal mismatch between PET and standard helical CT (HCT) causes substantial respiratory artifacts in PET reconstructed images when using HCT as the attenuation map. Previously we developed an interpolated average CT (IACT) method for attenuation correction (AC) and demonstrated its merits in simulations. In this study we aim to apply IACT in patients with thoracic lesions using an active breathing controller (ABC). Under local ethics approval, we recruited 15 patients with a total of 18 lesions in different thoracic regions: left upper lobe (2), right upper lobe (4), right hilum (3), right lower lobe (3), left hilum (2), and esophagus (4). All patients underwent whole body PET scans 1 h after 300-480 MBq (18)F-FDG injection, depending on the patients' weight. The PET sinograms were reconstructed with AC using: (i) standard HCT [120 kV, smart mA (30-150 mA), 0.984:1 pitch] and (ii) IACT obtained from end-inspiration and end-expiration breath-hold HCTs (120 kV, 10 mA, 0.984:1 pitch) aided by ABC. IACT was obtained by averaging the intensity of two extreme phases and the interpolated phases between them, where the nonlinear interpolation was obtained by B-spline registration and with an empirical sinusoidal function. The SUV max, SUV mean, and the differences of centroid-of-lesion (d) between PET and different CT schemes were measured for each lesion. From visual inspection, the respiratory artifacts and blurring generally reduced in the thoracic region for PET IACT. Matching between CT and PET improved for PET IACT, with an average decrease of d for 1.34 ± 1.79 mm as compared to PET HCT. The SUV max and SUV mean were consistently higher for PET IACT versus PET HCT for all lesions, with (30.95 ± 18.63)% and (22.39 ± 15.91)% average increase, respectively. IACT-ABC reduces respiratory artifacts, PET/CT misregistration and enhances lesion quantitation. This technique is a robust and low dose AC protocol for clinical oncology application especially in the thoracic region.

WE‐C‐103‐04: The Optimization of CT Protocols Using Plots of CTDIvol and of Max and Min MA Versus Patient Size for Actual Clinical Scans Using Automatic Exposure Control (AEC)

Purpose: To determine the usefulness of the knowledge of CTDIvol and mA variations as a function of patient size for optimizing scan parameters in CT imaging using AEC. Methods: Data was collected from actual patient scans for a number of different CT protocols such as standard chest, body, head, vascular imaging, and pediatric body. A GE LightSpeed VCT scanner was used in Smart mA mode in which the user can select the Noise Index, and the maximum and minimum mA allowed during mA modulation. For each different protocol the CTDIvol, minimum mA, maximum mA and patient size where determined for at least 40 patients, along with information on when the mA had reached its specified minimum or maximum value. Plots were made of the CTDIvol versus patient size and of the maximum and minimum mA versus patient size. Results: Initial results demonstrated a significant variation in CTDIvol over the range of adult patient sizes of more than a factor of ten for abdominal imaging. The observation that clinical scans frequently reached the minimum allowed mA indicated that reduction of the rotation time and lowering of the minimum mA parameter would allow lower patient dose and better operation of the AEC system. These results also led us to create separate protocols for small, medium, and large patients, each with a different optimized Noise Index, kV, rotation time, and mA range. These were created in consultation with our radiologists in determining the lowest dose that would provide a clinically acceptable image after the AEC was deemed to be operating optimally. Conclusion: The above analysis can provide significant help in improving CT protocols and lowering patient dose. The plots of CTDIvol versus patient size also helped to educate radiologists in the dose variations to be expected for a range of patient sizes. Equipment grant from GE healthcare.

High-resolution computed tomography with 16-row mdct: a comparison regarding visibility and motion artifacts of dose-modulated thin slices and “step and shoot” images

Dose modulation can be used to reduce the radiation dose in computed tomography (CT) examinations while still obtaining the necessary diagnostic image quality. Multidetector-row computed tomography (MDCT) provides the possibility of simultaneous reconstruction of thin and thick slices from the same raw data. To compare thin slices reconstructed from a dose-modulated helical acquisition and conventional high-resolution computed tomography (HRCT) images taken with the "step and shoot" technique in terms of visibility and motion artifacts, in order to investigate the possibility of excluding "step and shoot" acquisition from the HRCT examination. Twenty patients were examined by a dose-modulated helical acquisition, "MDCT smart mA," and by a noncontiguous cross-sectional high-resolution 16-row MDCT examination, "MDCT step and shoot." Images from four anatomical levels, made anonymous regarding identity and technical data, were analyzed in random order by four thoracic radiologists. "MDCT smart mA" was worse than "MDCT step and shoot" in terms of visibility. Concerning motion artifacts, "MDCT smart mA" was better than "MDCT step and shoot." Thin images reconstructed from a dose-modulated 16-row helical MDCT acquisition ("MDCT smart mA"), as performed in our study, do not provide sufficient image quality regarding visibility compared to the "MDCT step and shoot" technique for the latter technique to be excluded from the HRCT examination.

Automatic tube current modulation technique for multidetector CT: is it effective with a 64-detector CT?

To investigate whether it is possible to obtain adequate images at uniform image noise levels and reduced radiation exposure with our automatic tube current modulation (ATCM) technique for 64-detector CT. The study population consisted of 64 patients with known or suspected lung or abdominal disease. We used a 64-detector CT scanner (LightSpeed VCT, GE Healthcare, Waukesha, WI, USA) and a combined angular and longitudinal tube current modulation technique (Smart mA, GE Healthcare, Waukesha, WI, USA) to examine 34 patients. The scanning parameters were identical; the minimum and maximum tube current thresholds were 50 and 800 mA, respectively. For study of the constant tube current technique, 30 additional patients were examined at 350 mA. The CT number and image noise (SD of the CT number) were measured in the 64 patients at six levels, i.e., the center of the left ventricle, the liver dome, the porta hepatis, the center of the spleen and the right and left renal pelvis. When we used the ATCM technique, the mean image noise ranged from 8.40 at the center of the left ventricle to 11.31 at the porta hepatis; the mean tube current ranged from 105.9 mAs at the center of the left ventricle to 169.6 mAs at the center of the spleen. The mean dose reduction rate per constant tube current at 175 mAs ranged from 3.1 to 39.5%. By use of the ATCM technique, it is possible to maintain a constant image noise level with a 64-detector CT.

Matters of the mind, heart, and soul

D r Martha Rogers is a Canadian nurse-futurist whose research re- veals that adult responses to learning about the future can be classified 3 ways. Accord- ing to Dr Rogers, learning about the future involves patterns of the mind, heart, and soul. 1,2 Future thinking requires a keen mind that understands and appreciates the complexity of systems thinking; taken se- riously, future-oriented discussions and consequences of human action generate strong feelings; and finally, learning and wondering about the future taps existen- tial anxieties and confronts people with questions of meaning, purpose, and soul. scenarios. Dr Rogers suggests use of the fol. lowing questions 3 to aid reflection: How plausible does the scenario seem? What thoughts does it bring to mind? What feel- ings does it generate? What are the impli- cations for society, health care, and nurs- ing? If parts of the scenario are desirable, what actions need to be taken to increase the chances of the scenario happening? If parts are undesirable, what actions need to be taken to prevent them from happening? The first 2020 scenario is Technology Eclipses Care. In this story, health care is driven by technology. Hospitals become high-tech centers. Sensors, monitors, voice-activated equipment, and smart ma- chines monitor and adjust care param- eters. Genetic engineering decreases or eliminates disease development. A cast of health supporters develops, which in- cludes massage therapists, palliative care assistants, elder care assistants, health communication specialists, and child de- velopment specialists. Nursing disappears. Analysis reveals that the reason for nursing's disappearance was that nursing was defined by skills and tasks rather than by knowledge. The second 2020 scenario is Control, Manage, and Measure. In this scenario, social programs are eliminated because of debt. The business of health care is orga- nized around programs of managed care. Health activities are centralized. Genetic fingerprints result in predicted illness pat- terns. People are given personalized care maps based on genetic analysis. Compli- ance with the care maps is monitored via personal health record smart cards. Persons who do not follow the care map are re- quired to finance their own health care. Doctors choose whom to hire. i The num- ber of nurses on the teams decrease because others are cheaper to employ. A small band of nurses who believe in the power of nurs- ing continues to exist.