Dosimetry and efficiency comparison of knowledge-based and manual planning using volumetric modulated arc therapy for craniospinal irradiation.

BACKGROUND: Craniospinal irradiation (CSI) poses a challenge to treatment planning due to the large target, field junction, and multiple organs at risk (OARs) involved. The aim of this study was to evaluate the performance of knowledge-based planning (KBP) in CSI by comparing original manual plans (MP), KBP RapidPlan initial plans (RPI), and KBP RapidPlan final plans (RPF), which received further re-optimization to meet the dose constraints. PATIENTS AND METHODS: Dose distributions in the target were evaluated in terms of coverage, mean dose, conformity index (CI), and homogeneity index (HI). The dosimetric results of OARs, planning time, and monitor unit (MU) were evaluated. RESULTS: All MP and RPF plans met the plan goals, and 89.36% of RPI plans met the plan goals. The Wilcoxon tests showed comparable target coverage, CI, and HI for the MP and RPF groups; however, worst plan quality was demonstrated in the RPI plans than in MP and RPF. For the OARs, RPF and RPI groups had better dosimetric results than the MP group (P < 0.05 for optic nerves, eyes, parotid glands, and heart). The planning time was significantly reduced by the KBP from an average of 677.80 min in MP to 227.66 min (P < 0.05) and 307.76 min (P < 0.05) in RPI, and RPF, respectively. MU was not significantly different between these three groups. CONCLUSIONS: The KBP can significantly reduce planning time in CSI. Manual re-optimization after the initial KBP is recommended to enhance the plan quality.

Quantitative Assessment of Lipiodol-Related Artifact Reduction for Dual-Energy Computed Tomography After Transcatheter Arterial Chemoembolization: A Phantom Study Evaluating the Use of Metal Artifact Reduction Algorithms.

OBJECTIVE: This study used metal artifact reduction (MAR) software to examine the computed tomography (CT) number of dual-energy CT (DECT) of hepatocellular carcinoma after transcatheter arterial chemoembolization. METHODS: Hollow columnar acrylic phantoms were filled with lipiodol and inserts of 2 sizes (large and small) were used to simulate liver tumors on a Revolution GSI CT scanner. The CT numbers of a single test object were collected twice: once with and once without the MAR algorithm. Lipiodol beam-hardening artifacts were quantified by measuring CT numbers in a region of interest around the tumor-simulating insert. RESULTS: The virtual monochromatic CT numbers of large and small tumors were closely related to energy. For small tumors, CT numbers increased with energy. For large tumors, CT numbers increased with energy at 1 cm from the margin but decreased with an increase in energy at 5 cm. Regardless of the size, distance, or location of the tumor, the CT numbers fluctuated more at low energy levels. CONCLUSIONS: At 1 cm from the margin, the CT numbers with MAR were significantly different from those without MAR. Low-energy CT numbers with MAR were near reference values. Metal artifact reduction exhibited superior performance for small tumors. Tumor margin images are affected by artifacts caused by Lipiodol. However, with MAR, CT numbers can be effectively calibrated, thus enabling clinicians to more accurately evaluate hepatocellular carcinoma development and identify residual tumors and recurrent or metastatic lesions.

Integrating subvolume dose and myocardial perfusion imaging parameters to assess the impact of radiation therapy on heart function in breast cancer patients: A comparative analysis between left- and right-sided breast cancer.

BACKGROUND: This study aimed to utilize an innovative method of integrating the 20 subvolume dose of left ventricle and the Tl-201 single photon emission computed tomography (SPECT) with myocardial perfusion imaging (MPI) parameters in patients with left- and right-sided breast cancer after radiation therapy. METHODS: Female patients with breast cancer underwent SPECT MPI before commencing radiotherapy and 12 months later were enrolled from January 2014 to December 2018. The images of CT simulation and SPECT MPI were integrated into the treatment planning system. The differences of doses and parameters of MPI in all cardiac subvolumes between left- and right-sided breast cancer patients were analyzed. RESULTS: Patients with left-sided breast cancer (n = 61) received a higher radiation dose to the heart, left ventricular, and its territories and subvolumes, compared to patients with right-sided breast cancer (n = 19). The 20-segment analysis also showed statistically significant disparities in the average radiation doses received by the two groups. In different coronary artery territories, the end-diastolic perfusion and end-systolic perfusion showed a decrease in both sides, with no significant differences. However, the wall motion and wall thickening showed a significant decline in subregions within the left- and right-sided coronary artery territories. CONCLUSION: This study demonstrates an innovative integrated method combining the left ventricular 20 regional doses with SPECT MPI which shows that left-sided breast cancer patients receive a higher subvolume dose than right-sided breast cancer patients. Further research is needed to confirm the potential impact on heart function after radiotherapy on both sides.

Evaluation of the cardiac subvolume dose and myocardial perfusion in left breast cancer patients with postoperative radiotherapy: a prospective study.

Adjuvant breast radiotherapy could reduce the risk of local recurrence. However, the radiation dose received by the heart also increases the risk of cardiotoxicity and causes consequential heart diseases. This prospective study aimed to evaluate more precisely cardiac subvolume doses and corresponding myocardial perfusion defects according to the American Heart Association (AHA)'s 20-segment model for single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) interpretation for breast cancer after radiotherapy. The 61 female patients who underwent adjuvant radiotherapy following breast cancer surgery for left breast cancer were enrolled. SPECT MPI were performed before radiotherapy for baseline study, and 12 months after for follow-up. Enrolled patients were divided into two groups, new perfusion defect (NPD) and non new perfusion defect found (non-NPD) according to myocardial perfusion scale score. CT simulation data, radiation treatment planning, and SPECT MPI images were fused and registered. The left ventricle was divided into four rings, three territories, and 20 segments according to the AHA's 20-segment model of the LV. The doses between NPD and non-NPD groups were compared by the Mann-Whitney test. The patients were divided into two groups: NPD group (n = 28) and non-NPD group (n = 33). The mean heart dose was 3.14 Gy in the NPD group and 3.08 Gy in the non-NPD group. Mean LV doses were 4.84 Gy and 4.71 Gy, respectively. The radiation dose of the NPD group was higher than the non-NPD group in the 20 segments of LV. There was significant difference in segment 3 (p = 0.03). The study indicated that the radiation doses to 20 segments of LV in NPD were higher than those in non-NPD significantly at segment 3, and higher in other segments in general. In the bull's eye plot combining radiation dose and NPD area, we found that the new cardiac perfusion decline may exist even in the low radiation dose region.Trial registration: FEMH-IRB-101085-F. Registered 01/01/2013, https://clinicaltrials.gov/ct2/show/NCT01758419?cond=NCT01758419&draw=2&rank=1 .

Hazard-based risk grouping effectively stratifying breast cancer patients in post-irradiation long-term heart diseases: a population-based cohort study.

Background: Even though advanced radiotherapy techniques provide a better protective effect on surrounding normal tissues, the late sequelae from radiation exposure to the heart are still considerable in breast cancer patients. The present population-based study explored the role of cox-regression-based hazard risk grouping and intended to stratify patients with post-irradiation long-term heart diseases. Materials and methods: The present study investigated the Taiwan National Health Insurance (TNHI) database. From 2000 to 2017, we identified 158,798 breast cancer patients. Using a propensity score match of 1:1, we included 21,123 patients in each left and right breast irradiation cohort. Heart diseases, including heart failure (HF), ischemic heart disease (IHD), and other heart diseases (OHD), and anticancer agents, including epirubicin, doxorubicin, and trastuzumab, were included for analysis. Results: Patients received left breast irradiation demonstrated increased risks on IHD (aHR, 1.16; 95% CI, 1.06-1.26; p < 0.01) and OHD (aHR, 1.08; 95% CI, 1.01-1.15; p < 0.05), but not HF (aHR, 1.11; 95% CI, 0.96-1.28; p = 0.14), when compared with patients received right breast irradiation. In patients who received left breast irradiation dose of >6,040 cGy, subsequent epirubicin might have a trend to increase the risk of heart failure (aHR, 1.53; 95% CI, 0.98-2.39; p = 0.058), while doxorubicin (aHR, 0.59; 95% CI, 0.26-1.32; p = 0.19) and trastuzumab (aHR, 0.93; 95% CI, 0.33-2.62; p = 0.89) did not. Older age was the highest independent risk factor for post-irradiation long-term heart diseases. Conclusion: Generally, systemic anticancer agents are safe in conjunction with radiotherapy for managing post-operative breast cancer patients. Hazard-based risk grouping may help stratify breast cancer patients associated with post-irradiation long-term heart diseases. Notably, radiotherapy should be performed cautiously for elderly left breast cancer patients who received epirubicin. Limited irradiation dose to the heart should be critically considered. Regular monitoring of potential signs of heart failure may be conducted.

Machine learning combined with radiomics and deep learning features extracted from CT images: a novel AI model to distinguish benign from malignant ovarian tumors.

BACKGROUND: To develop an artificial intelligence (AI) model with radiomics and deep learning (DL) features extracted from CT images to distinguish benign from malignant ovarian tumors. METHODS: We enrolled 149 patients with pathologically confirmed ovarian tumors. A total of 185 tumors were included and divided into training and testing sets in a 7:3 ratio. All tumors were manually segmented from preoperative contrast-enhanced CT images. CT image features were extracted using radiomics and DL. Five models with different combinations of feature sets were built. Benign and malignant tumors were classified using machine learning (ML) classifiers. The model performance was compared with five radiologists on the testing set. RESULTS:  Among the five models, the best performing model is the ensemble model with a combination of radiomics, DL, and clinical feature sets. The model achieved an accuracy of 82%, specificity of 89% and sensitivity of 68%. Compared with junior radiologists averaged results, the model had a higher accuracy (82% vs 66%) and specificity (89% vs 65%) with comparable sensitivity (68% vs 67%). With the assistance of the model, the junior radiologists achieved a higher average accuracy (81% vs 66%), specificity (80% vs 65%), and sensitivity (82% vs 67%), approaching to the performance of senior radiologists. CONCLUSIONS:  We developed a CT-based AI model that can differentiate benign and malignant ovarian tumors with high accuracy and specificity. This model significantly improved the performance of less-experienced radiologists in ovarian tumor assessment, and may potentially guide gynecologists to provide better therapeutic strategies for these patients.

Fast myocardial perfusion SPECT denoising using an attention-guided generative adversarial network.

Purpose: Deep learning-based denoising is promising for myocardial perfusion (MP) SPECT. However, conventional convolutional neural network (CNN)-based methods use fixed-sized convolutional kernels to convolute one region within the receptive field at a time, which would be ineffective for learning the feature dependencies across large regions. The attention mechanism (Att) is able to learn the relationships between the local receptive field and other voxels in the image. In this study, we propose a 3D attention-guided generative adversarial network (AttGAN) for denoising fast MP-SPECT images. Methods: Fifty patients who underwent 1184 MBq 99mTc-sestamibi stress SPECT/CT scan were retrospectively recruited. Sixty projections were acquired over 180° and the acquisition time was 10 s/view for the full time (FT) mode. Fast MP-SPECT projection images (1 s to 7 s) were generated from the FT list mode data. We further incorporated binary patient defect information (0 = without defect, 1 = with defect) into AttGAN (AttGAN-def). AttGAN, AttGAN-def, cGAN, and Unet were implemented using Tensorflow with the Adam optimizer running up to 400 epochs. FT and fast MP-SPECT projection pairs of 35 patients were used for training the networks for each acquisition time, while 5 and 10 patients were applied for validation and testing. Five-fold cross-validation was performed and data for all 50 patients were tested. Voxel-based error indices, joint histogram, linear regression, and perfusion defect size (PDS) were analyzed. Results: All quantitative indices of AttGAN-based networks are superior to cGAN and Unet on all acquisition time images. AttGAN-def further improves AttGAN performance. The mean absolute error of PDS by AttcGAN-def was 1.60 on acquisition time of 1 s/prj, as compared to 2.36, 2.76, and 3.02 by AttGAN, cGAN, and Unet. Conclusion: Denoising based on AttGAN is superior to conventional CNN-based networks for MP-SPECT.

Lower-extremity muscle wasting in patients with peripheral arterial disease: quantitative measurement and evaluation with CT.

OBJECTIVES: Lower-extremity peripheral arterial disease (PAD) results in limb ischemia and is strongly associated with sarcopenia. This study aimed to retrospectively evaluate the association between the quantity of muscle mass in the lower extremities and the severity of vascular stenosis in PAD patients. METHODS: Between January 2018 and August 2021, 128 patients with PAD and 53 individuals without PAD, diagnosed by computed tomography, were enrolled. The severity of stenosis of lower-extremity arteries was measured using a grading system. The muscle and fat mass areas were calculated in the abdomen at the L3 or L4 level, mid-thigh, and lower leg. Multivariable logistic regression was conducted to clarify the risk associated with low muscle mass. The difference in muscle mass between PAD and non-PAD patients was evaluated by using propensity score matching. RESULTS: A strong positive correlation between the abdomen muscle area and leg muscle area was observed. The muscle area and muscle index of the leg were lower in PAD patients. These changes occurred earlier than in the abdomen muscle area. The group with more severe artery stenosis had more muscle wasting in the lower extremities. Greater age, female, lower BMI, and PAD were associated with low muscle mass. After propensity score matching, the leg muscle area was still lower in PAD patients. CONCLUSIONS: There is a direct association between PAD and regional muscle wasting. This occurs earlier regionally in the lower extremities than in central muscles. Early diagnosis of PAD might prevent progressive muscle loss, improving disease outcome and quality of life. KEY POINTS: • Peripheral arterial disease is strongly associated with sarcopenia. • Muscle wasting in the lower extremities is earlier and more prominent than that in the abdomen. • More severe arterial stenoses are associated with higher muscle wasting in the lower extremities.

Deep learning-based denoising in projection-domain and reconstruction-domain for low-dose myocardial perfusion SPECT.

BACKGROUND: Low-dose (LD) myocardial perfusion (MP) SPECT suffers from high noise level, leading to compromised diagnostic accuracy. Here we investigated the denoising performance for MP-SPECT using a conditional generative adversarial network (cGAN) in projection-domain (cGAN-prj) and reconstruction-domain (cGAN-recon). METHODS: Sixty-four noisy SPECT projections were simulated for a population of 100 XCAT phantoms with different anatomical variations and 99mTc-sestamibi distributions. Series of LD projections were obtained by scaling the full dose (FD) count rate to be 1/20 to 1/2 of the original. Twenty patients with 99mTc-sestamibi stress SPECT/CT scans were retrospectively analyzed. For each patient, LD SPECT images (7/10 to 1/10 of FD) were generated from the FD list mode data. All projections were reconstructed by the quantitative OS-EM method. A 3D cGAN was implemented to predict FD images from their corresponding LD images in the projection- and reconstruction-domain. The denoised projections were reconstructed for analysis in various quantitative indices along with cGAN-recon, Gaussian, and Butterworth-filtered images. RESULTS: cGAN denoising improves image quality as compared to LD and conventional post-reconstruction filtering. cGAN-prj can further reduce the dose level as compared to cGAN-recon without compromising the image quality. CONCLUSIONS: Denoising based on cGAN-prj is superior to cGAN-recon for MP-SPECT.

Integrating 18 F-FDG PET/CT with lung dose-volume for assessing lung inflammatory changes after arc-based radiotherapy for esophageal cancer: A pilot study.

OBJECTIVE: The incidence of radiation pneumonitis (RP) has a highly linear relationship with low-dose lung volume. We previously established a volume-based algorithm (VBA) method to improve low-dose lung volume in radiotherapy (RT). This study assessed lung inflammatory changes by integrating fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18 F-FDG PET/CT) with VBA for esophageal cancer patients undergoing arc-based RT. METHODS: Thirty esophageal cancer patients received 18 F-FDG PET/CT imaging pre-RT and post-RT were included in a retrospective pilot study. We fused lung doses and parameters of PET/CT in RT planning. Based on VBA, we used the 5Gy isodose curve to define high-dose (HD) and low-dose (LD) regions in the lung volume. We divided patients into non-RP (nRP) and RP groups. The maximum, mean standardized uptake value (SUVmax, SUVmean), global lung glycolysis (GLG), mean lung dose (MLD) and V5-30 in lungs were analyzed. Area under the curve values were utilized to identify optimal cut-off values for RP. RESULTS: Eleven patients in the nRP group and 19 patients in the RP group were identified. In 30 RP lungs, post-RT SUVmax, SUVmean and GLG of HD regions showed significant increases compared to values for pre-RT lungs. There were no significant differences in values of 22 nRP lungs. Post-RT SUVmax and SUVmean of HD regions, MLD, and lung V5 and V10 in RP lungs were significantly higher than in nRP lungs. For detecting RP, the optimal cut-off values were post-RT SUVmax > 2.28 and lung V5  > 47.14%. CONCLUSION: This study successfully integrated 18 F-FDG PET/CT with VBA to assess RP in esophageal cancer patients undergoing RT. Post-RT SUVmax > 2.28 and lung V5  > 47.14% might be potential indicators of RP.

Validation of Virtual Monochromatic Images and Effect of Body Size Obtained Using a Rapid kVp-switching Dual-energy Computed Tomography System: A Phantom Study.

ABSTRACT: The objective of this paper is to validate virtual monochromatic computed tomography (CT) numbers and the effect of the body size of insert materials in phantoms on the findings of a dual-energy CT scanner. The material inserted in the phantom simulates human organs. This study investigated the effect of different body sizes on CT numbers to understand the accuracy of dual-energy CT. The effect of body size on virtual monochromatic CT numbers was investigated using a QRM phantom. The true monochromatic CT numbers of insert materials were calculated from coefficients obtained using NIST XCOM. The true Z eff values were supplied by phantom manufacturers or computed using Mayneord's equation. The virtual monochromatic CT numbers of insert materials in both the phantoms varied with energy. The CT numbers of materials with a Z eff of >7.42 (water Z eff ) and <7.42 decreased and increased with energy, respectively. The CT numbers were affected by phantom size as a function of energy. For water, tissues, and air, the CT numbers in the XL phantom were considerably larger than those in other phantom sizes at 40 keV. Body size affected the CT numbers, particularly for the XL size and at low energies. For all materials, the magnitude of difference between the measured and true CT numbers was related to the Z eff of the materials, potentially because the photoelectric effect is more prominent at low energies for materials with a higher Z eff . The difference in CT numbers appeared to be dependent on position. The true and measured Z eff agreed to within 6% for all the materials except the SR2 brain, for which the discrepancy was 25%.

Pix2Pix generative adversarial network for low dose myocardial perfusion SPECT denoising.

Background: Myocardial perfusion (MP) SPECT is a well-established method for diagnosing cardiac disease, yet its radiation risk poses safety concern. This study aims to apply and evaluate the use of Pix2Pix generative adversarial network (Pix2Pix GAN) in denoising low dose MP SPECT images. Methods: One hundred male and female patients with different 99mTc-sestamibi activity distributions, organ and body sizes were simulated by a population of digital 4D Extended Cardiac Torso (XCAT) phantoms. Realistic noisy SPECT projections of full dose of 987 MBq injection and 16 min acquisition, and low dose ranged from 1/20 to 1/2 of the full dose, were generated by an analytical projector from the right anterior oblique (RAO) to the left posterior oblique (LPO) positions. Additionally, twenty patients underwent ~1,184 MBq 99mTc-sestamibi stress SPECT/CT scan were also retrospectively recruited for the study. For each patient, low dose SPECT images (7/10 to 1/10 of full dose) were generated from the full dose list mode data. Our Pix2Pix GAN model was trained with full dose and low dose reconstructed SPECT image pairs. Normalized mean square error (NMSE), structural similarity index (SSIM), coefficient of variation (CV), full-width-at-half-maximum (FWHM) and relative defect size differences (RSD) of Pix2Pix GAN processed images were evaluated along with a reference convolutional auto encoder (CAE) network and post-reconstruction filters. Results: NMSE values of 0.0233±0.004 vs. 0.0249±0.004 and 0.0313±0.007 vs. 0.0579±0.016 were obtained on 1/2 and 1/20 dose level for Pix2Pix GAN and CAE in the simulation study, while they were 0.0376±0.010 vs. 0.0433±0.010 and 0.0907±0.020 vs. 0.1186±0.025 on 7/10 and 1/10 dose level in the clinical study. Similar results were also obtained from the SSIM, CV, FWHM and RSD values. Overall, the use of Pix2Pix GAN was superior to other denoising methods in all physical indices, particular in the lower dose levels in the simulation and clinical study. Conclusions: The Pix2Pix GAN method is effective to reduce the noise level of low dose MP SPECT. Further studies on clinical performance are warranted to demonstrate its full clinical effectiveness.

Insights on Distinct Left Atrial Remodeling Between Atrial Fibrillation and Heart Failure With Preserved Ejection Fraction.

Background: Heart failure with preserved ejection fraction (HFpEF) and atrial fibrillation (AF) commonly coexist with overlapping pathophysiology like left atrial (LA) remodeling, which might differ given different underlying mechanisms. Objectives: We sought to investigate the different patterns of LA wall remodeling in AF vs. HFpEF. Methods: We compared LA wall characteristics including wall volume (LAWV), wall thickness (LAWT), and wall thickness heterogeneity (LAWT[SD]) and LA structure, function among the controls (without AF or HFpEF, n = 115), HFpEF alone (n = 59), AF alone (n = 37), and HFpEF+AF (n = 38) groups using multi-detector computed tomography and echocardiography. Results: LA wall remodeling was most predominant and peak atrial longitudinal strain (PALS) was worst in HFpEF+AF patients as compared to the rest. Despite lower E/e' (9.8 ± 3.8 vs. 13.4 ± 6.4) yet comparable LA volume, LAWT and PALS in AF alone vs. HFpEF alone, LAWV [12.6 (11.6-15.3) vs. 12.0 (10.2-13.7); p = 0.01] and LAWT(SD) [0.68 (0.61-0.71) vs. 0.60 (0.56-0.65); p < 0.001] were significantly greater in AF alone vs. HFpEF alone even after multi-variate adjustment and propensity matching. After excluding the HFpEF+AF group, both LAWV and LAWT [SD] provided incremental values when added to PALS or LAVi (all p for net reclassification improvement <0.05) in discriminating AF alone, with LAWT[SD] yielding the largest C-statistic (0.78, 95% CI: 0.70-0.86) among all LA wall indices. Conclusions: Despite a similar extent of LA enlargement and dysfunction in HFpEF vs. AF alone, larger LAWV and LAWT [SD] can distinguish AF from HFpEF alone, suggesting the distinct underlying pathophysiological mechanism of LA remodeling in AF vs. HFpEF.

Planning evaluation of a novel volume-based algorithm for personalized optimization of lung dose in VMAT for esophageal cancer.

Radiotherapy treatment planning (RTP) is time-consuming and labor-intensive since medical physicists must devise treatment plans carefully to reduce damage to tissues and organs for patients. Previously, we proposed the volume-based algorithm (VBA) method, providing optimal partial arcs (OPA) angle to achieve the low-dose volume of lungs in dynamic arc radiotherapy. This study aimed to implement the VBA for esophageal cancer (EC) patients and compare the lung dose and delivery time between full arcs (FA) without using VBA and OPA angle using VBA in volumetric modulated arc therapy (VMAT) plans. We retrospectively included 30 patients diagnosed with EC. RTP of each patient was replanned to 4 VMAT plans, including FA plans without (FA-C) and with (FA + C) dose constraints of OARs and OPA plans without (OPA-C) and with (OPA + C) dose constraints of OARs. The prescribed dose was 45 Gy. The OARs included the lungs, heart, and spinal cord. The dose distribution, dose-volume histogram, monitor units (MUs), delivery time, and gamma passing rates were analyzed. The results showed that the lung V5 and V10 in OPA + C plans were significantly lower than in FA + C plans (p < 0.05). No significant differences were noted in planning target volume (PTV) coverage, lung V15, lung V20, mean lung dose, heart V30, heart V40, mean heart dose, and maximal spinal cord dose between FA + C and OPA + C plans. The delivery time was significantly longer in FA + C plans than in OPA + C plans (237 vs. 192 s, p < 0.05). There were no significant differences between FA + C and OPA + C plans in gamma passing rates. We successfully applied the OPA angle based on the VBA to clinical EC patients and simplified the arc angle selection in RTP. The VBA could provide a personalized OPA angle for each patient and effectively reduce lung V5, V10, and delivery time in VMAT.

Evaluation of Abdominal Computed Tomography Scans for Differentiating the Discrepancies in Abdominal Adipose Tissue Between Two Major Subtypes of Primary Aldosteronism.

The aim of this study was to analyze the differences in the distribution of abdominal adipose tissue between the two subtypes of primary aldosteronism (PA) using abdominal computed tomography. We retrospectively analyzed patients diagnosed as having essential hypertension (EH) or PA from the prospectively collected Taiwan Primary Aldosteronism Investigation (TAIPAI) database. Patients with PA were divided into the subgroups of idiopathic hyperaldosteronism (IHA) and unilateral aldosterone-producing adenoma (APA). Patients' basic clinicodemographic data were collected, and a self-developed CT-based software program was used to quantify the abdominal adiposity indexes, including visceral adipose tissue (VAT) area, VAT ratio, waist circumference (WC), subcutaneous adipose tissue (SAT) area, and SAT ratio. We included 190 patients with EH and 436 patients with PA (238 with IHA and 198 with APA). The APA group had significantly lower abdominal adiposity indexes than the other groups. We also found negative correlations of aldosterone-to-renin ratio (ARR) with VAT area, VAT ratio, WC, and body mass index (BMI) in the APA group. After propensity score matching (which left 184 patients each in the IHA and APA groups), patients in the APA group still had significantly lower WC, SAT area, SAT ratio, and VAT ratio than those in the IHA group. Furthermore, logistic regression analysis indicated that lower probability of abdominal obesity was significantly related to patients with APA. Our data revealed that the distribution of abdominal adipose tissue was similar in patients with IHA and those with EH, but the abdominal adiposity indexes were significantly lower in patients with APA than in those with IHA and EH.

Thoracic Aortic Calcification and Pre-Clinical Hypertension by New 2017 ACC/AHA Hypertension Guidelines.

The recently revised 2017 American College of Cardiology/American Heart Association (ACC/AHA) hypertension (HTN) guidelines employ a lower blood pressure threshold to define HTN, aiming for earlier prevention of HTN-related cardiovascular diseases (CVD). Thoracic aortic calcification (TAC), a new surrogate marker of aging and aortic medial layer degeneration, and different stages of HTN, according to the 2017 ACC/AHA HTN guidelines, remain unknown. We classified 3022 consecutive asymptomatic individuals enrolled into four HTN categories using the revised 2017 ACC/AHA guidelines: normal blood pressure (NBP), elevated blood pressure (EBP), and stage 1 (S1) and stage 2 (S2) HTN. The coronary artery calcification score and TAC metrics (total Agaston TAC score, total plaque volume (mm3), and mean density (Hounsfield units, HU)) were measured using multi-detector computed tomography. Compared to NBP, a graded and significant increase in the TAC metrics was observed starting from EBP and S1 and S2 HTN, using the new 2017 ACC/AHA guidelines (NBP as reference; all trends: p < 0.001). These differences remained consistent after being fully adjusted. Older age (>50 years), S1 and S2 HTN, prevalent diabetes, and chronic kidney disease (<60 mL/min/1.73 m2) are all independently contributing factors to higher TAC risk using multivariate stepwise logistic regressions (all p ≤ 0.001). The optimal cutoff values of systolic blood pressure, diastolic blood pressure, and pulse pressure were 121, 74, and 45 mmHg, respectively, for the presence of TAC after excluding subjects with known CVD and ongoing HTN medication treatment. Our data showed that the presence of TAC starts at a stage of elevated blood pressure not categorized as HTN from the updated 2017 ACC/AHA hypertension guidelines.

Aldosterone-producing adenoma-harbouring KCNJ5 mutations is associated with lower prevalence of metabolic disorders and abdominal obesity.

OBJECTIVE: Aldosterone overproduction and lipid metabolic disturbances between idiopathic hyperaldosteronism (IHA) and unilateral aldosterone-producing adenoma (APA) have been inconsistently linked in patients with primary aldosteronism. Moreover, KCNJ5 mutations are prevalent among APAs and enhance aldosterone synthesis in adrenal cortex. We aimed to investigate the prevalence of metabolic syndrome (MetS) in each primary aldosteronism subtype and observe the role of KCNJ5 mutations among APAs on the distribution of abdominal adipose tissues quantified using computed tomography (CT), including their changes postadrenalectomy. DESIGN AND METHODS: We retrospectively collected 244 and 177 patients with IHA and APA at baseline. Patients with APA had undergone adrenalectomy, and gene sequencing revealed the absence (n = 75) and presence (n = 102) of KCNJ5 mutations. We also recruited 31 patients with APA who had undergone CT-scan 1-year postadrenalectomy. RESULTS: The patients with APA harbouring KCNJ5 mutations had significantly lower prevalence of MetS and smaller distribution in waist circumference, subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) than the other groups. Logistic regression analysis indicated that the VAT area correlated significantly with KCNJ5 mutations among the APAs. Only participants with KCNJ5 mutations had significant increases in triglycerides, cholesterol, SAT, and VAT after 1-year postadrenalectomy. CONCLUSION: This study is the first to demonstrate that MetS and abdominal obesity were less prevalent in the patients with APA harbouring KCNJ5 mutations compared with the IHA group and the non-KCNJ5-mutated APA group. Increasing prevalence of dyslipidaemia and abdominal obesity was observed in patients with KCNJ5 mutations 1-year postadrenalectomy.

Evaluation of different CT maps for attenuation correction and segmentation in static 99m Tc-MAA SPECT/CT for 90 Y radioembolization treatment planning: A simulation study.

PURPOSE: Conventional 99m Tc-macroaggregated albumin (99m Tc-MAA) planar scintigraphy overestimates lung shunt fraction (LSF) compared to SPECT/CT. However, the respiratory motion artifact due to the temporal mismatch between static SPECT and helical CT (HCT) may compromise the SPECT quantitation accuracy by incorrect attenuation correction (AC) and volume-of-interest (VOI) segmentation. This study aims to evaluate AC and VOI segmentation effects systematically and to propose a CT map for LSF and tumor-to-normal liver ratio (TNR) estimation in static 99m Tc-MAA SPECT/CT. METHODS: The 4D XCAT phantom was used to simulate a phantom population of 120 phantoms, modeling 10 different anatomical variations, nine TNRs (2-13.2), nine tumor sizes (2-6.7 cm diameter), eight tumor locations, three axial motion amplitudes of 1, 1.5, and 2 (cm), and four LSFs of 5%, 10%, 15%, and 20%. An analytical projector for low-energy high-resolution parallel-hole collimator was used to simulate 60 noisy projections over 360°, modeling attenuation and geometric collimator-detector response (GCDR). AC and VOI mismatch effects were investigated independently and together, using cine average CT (CACT), HCT at end-inspiration (HCT-IN), mid-respiration (HCT-MID), and end-expiration (HCT-EX) respectively as attenuation and segmentation maps. SPECT images without motion, AC, and VOI errors were also generated as reference. LSF and TNR errors were measured as compared to the ground truth. RESULTS: HCT-MID has slightly better performance for AC effect compared with other CT maps in LSF and TNR estimation, while HCT-EX and HCT-MID perform better for VOI effect. For a respiratory motion amplitude of 1.5 cm and a LSF of 5%, the LSF errors are 19.56 ± 4.58%, -6.79 ± 1.74%, 77.29 ± 14.74%, and 111.25 ± 18.29% corresponding to HCT-MID, HCT-EX, HCT-IN, and CACT in static SPECT. The TNR errors are -12.38 ± 6.42%, -20.55 ± 11.25%, -20.89 ± 9.98%, and -22.89 ± 14.38% respectively. HCT-MID has the best performance for LSF estimation for LSF > 10% and TNR estimation, followed by HCT-EX, HCT-IN, and CACT. CONCLUSIONS: The HCT-MID is recommended for AC and segmentation to alleviate respiratory artifacts and improve quantitation accuracy in 90 Y radioembolization treatment planning. HCT-EX would also be a recommended choice if HCT-MID is not available.

Volume-based algorithm of lung dose optimization in novel dynamic arc radiotherapy for esophageal cancer.

This study aims to develop a volume-based algorithm (VBA) that can rapidly optimize rotating gantry arc angles and predict the lung V5 preceding the treatment planning. This phantom study was performed in the dynamic arc therapy planning systems for an esophageal cancer model. The angle of rotation of the gantry around the isocenter as defined as arc angle (θA), ranging from 360° to 80° with an interval of 20°, resulting in 15 different θA of treatment plans. The corresponding predicted lung V5 was calculated by the VBA, the mean lung dose, lung V5, lung V20, mean heart dose, heart V30, the spinal cord maximum dose and conformity index were assessed from dose-volume histogram in the treatment plan. Correlations between the predicted lung V5 and the dosimetric indices were evaluated using Pearson's correlation coefficient. The results showed that the predicted lung V5 and the lung V5 in the treatment plan were positively correlated (r = 0.996, p < 0.001). As the θA decreased, lung V5, lung V20, and the mean lung dose decreased while the mean heart dose, V30 and the spinal cord maximum dose increased. The V20 and the mean lung dose also showed high correlations with the predicted lung V5 (r = 0.974, 0.999, p < 0.001). This study successfully developed an efficient VBA to rapidly calculate the θA to predict the lung V5 and reduce the lung dose, with potentials to improve the current clinical practice of dynamic arc radiotherapy.

Cardiac catheterization real-time dynamic radiation dose measurement to estimate lifetime attributable risk of cancer.

Cardiac catheterization procedure is the gold standard to diagnose and treat cardiovascular disease. However, radiation safety and cancer risk remain major concerns. This study aimed to real-time dynamic radiation dose measurement to estimate lifetime attributable risk (LAR) of cancer incidence and mortality in operators. Coronary angiography (CA) with percutaneous coronary intervention (PCI), CA, and others (radiofrequency ablation, pacemaker and defibrillator implantation) procedures with different beam directions, were undertaken on x-ray angiography system. A real-time electronic personal dosimeter (EPD) system was used to measure the radiation dose of staff during all procedures. We followed the Biological Effects of Ionizing Radiation (BEIR) VII report to estimate the LAR of all cancer incidence and mortality. Primary operators received radiation dose in CA with PCI, CA, and others procedures were 59.33 ± 95.03 µSv, 39.81 ± 103.85 µSv, and 21.92 ± 37.04 µSv, respectively. As to the assistant operators were 30.03 ± 55.67 µSv, 14.67 ± 14.88 µSv, and 4 µSv, respectively. LAR of all cancer incidences for staffs aged from 18 to 65 are varied from 0.40% for males to 1.50% for females. LAR of all cancer mortality for staffs aged from 18 to 65 are varied from 0.22% for males to 0.83% for females. Our study provided an easy, real-time and dynamic radiation dose measurement to estimate LAR of cancer for staff during the cardiac catheterization procedures. The LAR for all cancer incidence is about twice that for cancer mortality. Although the radiation doses of staff are lower during each procedure, the increased years of service leads to greater radiation risk to the staff.