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Personalized administration of contrast medium with high delivery rate in low tube voltage coronary computed tomography angiography

Tan SK, Ng KH, Yeong CH, Raja Aman RRA, Mohamed Sani F, Abdul Aziz YF, et al.

Quant Imaging Med Surg, 2019 Apr;9(4):552-564.
PMID: 31143647 DOI: 10.21037/qims.2019.03.13

Background: High delivery rate is an important factor in optimizing contrast medium administration in coronary computed tomography angiography (CCTA). A personalized contrast volume calculation algorithm incorporating high iodine delivery rate (IDR) can reduce total iodine dose (TID) and produce optimal vessel contrast enhancement (VCE) in low tube voltage CCTA. In this study, we developed and validated an algorithm for calculating the volume of contrast medium delivered at a high rate for patients undergoing retrospectively ECG-gated CCTA with low tube voltage protocol.
Methods: The algorithm for an IDR of 2.22 gI·s-1 was developed based on the relationship between VCE and contrast volume in 141 patients; test bolus parameters and characteristics in 75 patients; and, tube voltage in a phantom study. The algorithm was retrospectively tested in 45 patients who underwent retrospectively ECG-gated CCTA with a 100 kVp protocol. Image quality, TID and radiation dose exposure were compared with those produced using the 120 kVp and routine contrast protocols.
Results: Age, sex, body surface area (BSA) and peak contrast enhancement (PCE) were significant predictors for VCE (P<0.05). A strong linear correlation was observed between VCE and contrast volume (r=0.97, P<0.05). The 100-to-120 kVp contrast enhancement conversion factor (Ec) was calculated at 0.81. Optimal VCE (250 to 450 HU) and diagnostic image quality were obtained with significant reductions in TID (32.1%) and radiation dose (38.5%) when using 100 kVp and personalized contrast volume calculation algorithm compared with 120 kVp and routine contrast protocols (P<0.05).
Conclusions: The proposed algorithm could significantly reduce TID and radiation exposure while maintaining optimal VCE and image quality in CCTA with 100 kVp protocol.
Fulltext Low tube voltage prospectively ECG-triggered coronary CT angiography: a systematic review of image quality and radiation dose

Tan SK, Yeong CH, Raja Aman RRA, Ng KH, Abdul Aziz YF, Chee KH, et al.

Br J Radiol, 2018 Jul;91(1088):20170874.
PMID: 29493261 DOI: 10.1259/bjr.20170874

OBJECTIVE: This study aimed (1) to perform a systematic review on scanning parameters and contrast medium (CM) reduction methods used in prospectively electrocardiography (ECG-triggered low tube voltage coronary CT angiography (CCTA), (2) to compare the achievable dose reduction and image quality and (3) to propose appropriate scanning techniques and CM administration methods.
METHODS: A systematic search was performed in PubMed, the Cochrane library, CINAHL, Web of Science, ScienceDirect and Scopus, where 20 studies were selected for analysis of scanning parameters and CM reduction methods.
RESULTS: The mean effective dose (HE) ranged from 0.31 to 2.75 mSv at 80 kVp, 0.69 to 6.29 mSv at 100 kVp and 1.53 to 10.7 mSv at 120 kVp. Radiation dose reductions of 38 to 83% at 80 kVp and 3 to 80% at 100 kVp could be achieved with preserved image quality. Similar vessel contrast enhancement to 120 kVp could be obtained by applying iodine delivery rate (IDR) of 1.35 to 1.45 g s-1 with total iodine dose (TID) of between 10.9 and 16.2 g at 80 kVp and IDR of 1.08 to 1.70 g s-1 with TID of between 18.9 and 20.9 g at 100 kVp.
CONCLUSION: This systematic review found that radiation doses could be reduced to a rate of 38 to 83% at 80 kVp, and 3 to 80% at 100 kVp without compromising the image quality. Advances in knowledge: The suggested appropriate scanning parameters and CM reduction methods can be used to help users in achieving diagnostic image quality with reduced radiation dose.
Generation of fluoroscopy-alike radiographs as alternative datasets for deep learning in interventional radiology

Fum WKS, Md Shah MN, Raja Aman RRA, Abd Kadir KA, Wen DW, Leong S, et al.

Phys Eng Sci Med, 2023 Dec;46(4):1535-1552.
PMID: 37695509 DOI: 10.1007/s13246-023-01317-5

In fluoroscopy-guided interventions (FGIs), obtaining large quantities of labelled data for deep learning (DL) can be difficult. Synthetic labelled data can serve as an alternative, generated via pseudo 2D projections of CT volumetric data. However, contrasted vessels have low visibility in simple 2D projections of contrasted CT data. To overcome this, we propose an alternative method to generate fluoroscopy-like radiographs from contrasted head CT Angiography (CTA) volumetric data. The technique involves segmentation of brain tissue, bone, and contrasted vessels from CTA volumetric data, followed by an algorithm to adjust HU values, and finally, a standard ray-based projection is applied to generate the 2D image. The resulting synthetic images were compared to clinical fluoroscopy images for perceptual similarity and subject contrast measurements. Good perceptual similarity was demonstrated on vessel-enhanced synthetic images as compared to the clinical fluoroscopic images. Statistical tests of equivalence show that enhanced synthetic and clinical images have statistically equivalent mean subject contrast within 25% bounds. Furthermore, validation experiments confirmed that the proposed method for generating synthetic images improved the performance of DL models in certain regression tasks, such as localizing anatomical landmarks in clinical fluoroscopy images. Through enhanced pseudo 2D projection of CTA volume data, synthetic images with similar features to real clinical fluoroscopic images can be generated. The use of synthetic images as an alternative source for DL datasets represents a potential solution to the application of DL in FGIs procedures.
Osteoporosis in Parkinson's Disease: Relevance of Distal Radius Dual-Energy X-Ray Absorptiometry (DXA) and Sarcopenia

Tan YJ, Lim SY, Yong VW, Choo XY, Ng YD, Sugumaran K, et al.

J Clin Densitom, 2020 07 30;24(3):351-361.
PMID: 32888777 DOI: 10.1016/j.jocd.2020.07.001

Osteoporotic fractures are common in Parkinson's disease (PD). Standard dual-energy X-ray absorptiometry (DXA) measuring bone mineral density (BMD) at the femoral neck and lumbar spine (central sites) has suboptimal sensitivity in predicting fracture risk in the general population. An association between sarcopenia and osteoporosis in PD has not been studied. We compared BMD and osteoporosis prevalence in PD patients vs controls; determined the osteoporosis detection rates using central alone vs central plus distal radius DXA; and analyzed factors (in particular, sarcopenia) associated with osteoporosis. One hundred and fifty-six subjects (102 patients with PD, 54 spousal/sibling controls) underwent femoral neck-lumbar spine-distal radius DXA. Seventy-three patients and 46 controls were assessed for sarcopenia using whole-body DXA and handgrip strength. Patients underwent clinical and serum biochemical evaluations. PD patients had significantly lower body mass index compared to controls. After adjustment for possible confounders, distal radius BMD and T-scores were significantly lower in PD patients compared to controls, but not at the femoral neck/lumbar spine. With distal radius DXA, an additional 11.0% of patients were diagnosed with osteoporosis (32.0% to 43.0%), vs 3.7% in controls (33.3% to 37.0%) additionally diagnosed; this increase was largely driven by the markedly higher detection rate in female PD patients. Female gender (adjusted odds ratio [ORadjusted] = 11.3, 95% confidence interval [CI]: 2.6-48.6) and sarcopenia (ORadjusted = 8.4, 95% CI: 1.1-64.9) were independent predictors for osteoporosis in PD. Distal radius DXA increased osteoporosis detection, especially in female PD patients, suggesting that diagnostic protocols for osteoporosis in PD could be optimized. A close association between osteoporosis and sarcopenia was documented for the first time in PD, which has important implications for clinical management and future research.
Progressive and accelerated weight and body fat loss in Parkinson's disease: A three-year prospective longitudinal study

Yong VW, Tan YJ, Ng YD, Choo XY, Sugumaran K, Chinna K, et al.

Parkinsonism Relat Disord, 2020 08;77:28-35.
PMID: 32615497 DOI: 10.1016/j.parkreldis.2020.06.015

INTRODUCTION: Although weight loss is common in Parkinson's disease (PD), longitudinal studies assessing weight and body composition changes are limited.
METHODS: In this three-year longitudinal study, 125 subjects (77 PD patients and 48 spousal/sibling controls) underwent clinical, biochemical and body composition assessments using dual-energy X-ray absorptiometry.
RESULTS: Patients were older than controls (65.6 ± 8.9 vs. 62.6 ± 7.1, P = 0.049), with no significant differences in gender, comorbidities, dietary intake and physical activity. Clinically significant weight loss (≥5% from baseline weight) was recorded in 41.6% of patients, with a doubling of cases (6.5 to 13.0%) classified as underweight at study end. Over three years, patients demonstrated greater reductions in BMI (mean -1.2 kg/m2, 95%CI-2.0 to -0.4), whole-body fat percentage (-2.5% points, 95%CI-3.9 to -1.0), fat mass index (FMI) (-0.9 kg/m2, 95%CI-1.4 to -0.4), visceral fat mass (-0.1 kg, 95%CI-0.2 to 0.0), and subcutaneous fat mass (-1.9 kg, 95%CI-3.4 to -0.5) than in controls, with significant group-by-time interactions after adjusting for age and gender. Notably, 31.2% and 53.3% of patients had FMI<3rd (severe fat deficit) and <10th centiles, respectively. Muscle mass indices decreased over time in both groups, without significant group-by-time interactions. Multiple linear regression models showed that loss of body weight and fat mass in patients were associated with age, dyskinesia, psychosis and constipation.
CONCLUSIONS: We found progressive loss of weight in PD patients, with greater loss of both visceral and subcutaneous fat, but not muscle, compared to controls. Several associated factors (motor and non-motor disease features) were identified for these changes, providing insights on possible mechanisms and therapeutic targets.