Applying the AAPM 293 report to estimate the absorbed dose during head computed tomography: using head circumference for rapid dose estimation.

Background: The American Association of Physicists in Medicine (AAPM) report 293 is more accurate than report 220 in evaluating the absorbed radiation dose during head computed tomography (CT) examination. We aimed to investigate the associations between age, head circumference (HC), the conversion factor (f293), and specific-size dose estimation (SSDE293) during these procedures. The rapid radiation dose was also estimated based on the AAPM report 293. Methods: In this retrospective, cross-sectional study, unenhanced CT images of the head were retrospectively collected from 1,222 participants from Union Hospital and Hubei Cancer Hospital between December 2018 and September 2019. Scan parameters, including age, HC, water-equivalent diameter (DW), and volumetric computed tomography dose index (CTDIvol), were generated automatically using indigenously-developed image processing software. The corresponding f293 and SSDE293 were calculated according to the AAPM report 293. The analyses were performed using linear regression. Results: In the younger group, age and HC were significantly negatively correlated with SSDE293 (r=-0.33 and -0.44, respectively; both P values ≤0.001). No significant correlation was reported between age, HC, and SSDE293 in the older group. Moreover, age was significantly negatively associated with f293 in the younger and older groups (r=-0.80 and -0.13, respectively; both P values ≤0.001). A significantly negative association was seen between f293 and increased HC in both age groups (r=-0.92 and -0.82, respectively; both P values ≤0.001). Conclusions: The HC of patients was associated with head conversion. HC is a feasible indicator for rapidly estimating the radiation dose in head CT examinations based on the AAPM report 293.

Comparison of selected photon shield and organ-based tube current modulation for radiation dose reduction in head computed tomography: A phantom study.

OBJECTIVE: The aim of this study is to investigate the radiation dose and image quality of head CT using SPS and OBTCM techniques. METHODS: Three anthropomorphic head phantoms (1-yr-old, 5-yr-old, and adult) were used. Images were acquired using four modes (Default protocol, OBTCM, SPS, and SPS+OBTCM). Absorbed dose to the lens, anterior brain (brain_A), and posterior brain (brain_P) was measured and compared. Image noise and CNR were assessed in the selected regions of interest (ROIs). RESULTS: Compared with that in the Default protocol, the absorbed dose to the lens reduced by up to 28.33%,71.38%, and 71.12% in OBTCM, SPS, and SPS+OBTCM, respectively. The noise level in OBTCM slightly (≤1.45HU) increased than that in Default protocol, and the SPS or SPS+OBTCM mode resulted in a quantitatively small increase (≤2.58HU) in three phantoms. There was no significant difference in CNR of different phantoms under varies scanning modes (p > 0.05). CONCLUSIONS: During head CT examinations, the SPS mode can reduce the radiation dose while maintaining image quality. SPS+OBTCM couldn't further effectively reduce the absorbed dose to the lens for 1-yr and 5-yr-old phantoms. Thus, SPS mode in pediatric and SPS+OBTCM mode in adult are better than other modes, and should be used in clinical practice.

Physics Informed Neural Networks (PINN) for Low Snr Magnetic Resonance Electrical Properties Tomography (MREPT).

Electrical properties (EPs) of tissues facilitate early detection of cancerous tissues. Magnetic resonance electrical properties tomography (MREPT) is a technique to non-invasively probe the EPs of tissues from MRI measurements. Most MREPT methods rely on numerical differentiation (ND) to solve partial differential Equations (PDEs) to reconstruct the EPs. However, they are not practical for clinical data because ND is noise sensitive and the MRI measurements for MREPT are noisy in nature. Recently, Physics informed neural networks (PINNs) have been introduced to solve PDEs by substituting ND with automatic differentiation (AD). To the best of our knowledge, it has not been applied to MREPT due to the challenges in using PINN on MREPT as (i) a PINN requires part of ground-truth EPs as collocation points to optimize the network's AD, (ii) the noisy input data disrupts the optimization of PINNs despite the noise-filtering nature of NNs and additional denoising processes. In this work, we propose a PINN-MREPT model based on a canonical analytic MREPT model. A reference padding layer with known EPs was added to surround the region of interest for providing additive collocation points. Moreover, an optimizable diffusion coefficient was embedded in the analytic MREPT model used in the PINN-MREPT. The noise robustness of the proposed PINN-MREPT for single-sample reconstruction was tested by using numerical phantoms of human brain with extra tumor-like tissues at different noise levels. The results of numerical experiments show that PINN-MREPT outperforms two typical numerical MREPT methods in terms of reconstruction accuracy, sensitivity to the extra tissues, and the correlations of line profiles in the regions of interest. The advantage of the PINN-MREPT is shown by the results of an experiment on phantom measurement, too. Moreover, it is found that the diffusion term plays an important role to achieve a noise-robust PINN-MREPT. This is an important step moving forward to a clinical application of MREPT.

BOLD signal simulation and fMRI quality control base on an active phantom: a preliminary study.

Blood-oxygen-level-dependent (BOLD) signal has been commonly used in functional magnetic resonance imaging (fMRI) to observe the activity in different areas of the brain or other organs. This signal is difficult to simulate, because its amplitude is nearly 1~3% and it is influenced by multiple factors. This study aimed to design and construct an active BOLD simulation phantom and test its stability and repeatability. The phantom consisted of two perpendicular loops. The BOLD signal was simulated by different stimuli generated by a regular periodic vibration current and transmission loops. Three scanners (Siemens skyra 3.0 T, Siemens verio 3.0 T, and GE signa HD 1.5 T) were used to test the stability and repeatability of the BOLD signal detection of the phantom. The percent signal change (PSC) was calculated for each stimulus. At baseline, the phantom exhibited stability, and the average signal variation was below 1% as revealed by the three scanners. The SNR of ROIs with different sizes were markedly high, being 2326.58 and 2389.24; and the ghosting ratio were 0.39% and 0.38%, and the stimuli detection efficiency for Siemens verio and Siemens skyra was 60% and 75%, respectively. The repeated scans of the same scanner for different stimuli were highly reproducible. In the three scanners, the PSC at the same location varied from nearly 1 to 3%. The areas activated on the phantom revealed by different scanners were comparatively consistent. The phantom designed for fMRI quantitative quality control displays good adaptability to different scanners and is easy to operate. It can reliably collect data by simple data processing. Graphical abstract fMRI phantom testing process.

Characterizing mechanical and medical imaging properties of polyvinyl chloride-based tissue-mimicking materials.

Polyvinyl chloride (PVC) is a commonly used tissue-mimicking material (TMM) for phantom construction using 3D printing technology. PVC-based TMMs consist of a mixture of PVC powder and dioctyl terephthalate as a softener. In order to allow the clinical use of a PVC-based phantom use across CT and magnetic resonance imaging (MRI) imaging platforms, we evaluated the mechanical and physical imaging characteristics of ten PVC samples. The samples were made with different PVC-softener ratios to optimize phantom bioequivalence with physiologic human tissue. Phantom imaging characteristics, including computed tomography (CT) number, MRI relaxation time, and mechanical properties (e.g., Poisson's ratio and elastic modulus) were quantified. CT number varied over a range of approximately -10 to 110 HU. The relaxation times of the T1-weighted and T2-weighted images were 206.81 ± 17.50 and 20.22 ± 5.74 ms, respectively. Tensile testing was performed to evaluate mechanical properties on the three PVC samples that were closest to human tissue. The elastic moduli for these samples ranged 7.000-12.376 MPa, and Poisson's ratios were 0.604-0.644. After physical and imaging characterization of the various PVC-based phantoms, we successfully produced a bioequivalent phantom compatible with multimodal imaging platforms for machine calibration and image optimization/benchmarking. By combining PVC with 3D printing technologies, it is possible to construct imaging phantoms simulating human anatomies with tissue equivalency.

3D-printed breast phantom for multi-purpose and multi-modality imaging.

BACKGROUND: Breast imaging technology plays an important role in breast cancer planning and treatment. Recently, three-dimensional (3D) printing technology has become a trending issue in phantom constructions for medical applications, with its advantages of being customizable and cost-efficient. However, there is no current practice in the field of multi-purpose breast phantom for quality control (QC) in multi-modalities imaging. The purpose of this study was to fabricate a multi-purpose breast phantom with tissue-equivalent materials via a 3D printing technique for QC in multi-modalities imaging. METHODS: We used polyvinyl chloride (PVC) based materials and a 3D printing technique to construct a breast phantom. The phantom incorporates structures imaged in the female breast such as microcalcifications, fiber lesions, and tumors with different sizes. Moreover, the phantom was used to assess the sensitivity of lesion detection, depth resolution, and detectability thresholds with different imaging modalities. Phantom tissue equivalent properties were determined using computed tomography (CT) attenuation [Hounsfield unit (HU)] and magnetic resonance imaging (MRI) relaxation times. RESULTS: The 3D-printed breast phantom had an average background value of 36.2 HU, which is close to that of glandular breast tissue (40 HU). T1 and T2 relaxation times had an average relaxation time of 206.81±17.50 and 20.22±5.74 ms, respectively. Mammographic imaging had improved detection of microcalcification compared with ultrasound and MRI with multiple sequences [T1WI, T2WI and short inversion time inversion recovery (STIR)]. Soft-tissue lesion detection and cylindrical tumor contrast were superior with mammography and MRI compared to ultrasound. Hemispherical tumor detection was similar regardless of the imaging modality used. CONCLUSIONS: We developed a multi-purpose breast phantom using a 3D printing technique and determined its value for multi-modal breast imaging studies.

Age-related changes in cortical and subcortical structures of healthy adult brains: A surface-based morphometry study.

BACKGROUND: Cerebral structures in both cortical and subcortical regions change with aging. More specific and comprehensive studies are needed to better elucidate these changes. PURPOSE: To investigate the relationships between age and cerebral structures regarding cortical and subcortical changes. STUDY TYPE: Cross-cohort research. POPULATION: 54 healthy adults (28 females) aged 21-71 years. FIELD STRENGTH/SEQUENCE: T1 -weighted imaging was performed at 1.5T. ASSESSMENT: The cortical thickness, local gyrification index (LGI), and the volumes of total gray matter (GM), white matter (WM), white matter hyperintensity (WMH), deep gray matter nuclei (putamen, pallidum, thalamus, caudate, amygdala, accumbens area, and hippocampus), ventricles, and hippocampal subfields were obtained using FreeSurfer software. STATISTICAL TESTS: Regression analysis was performed to determine the relationships between age and cortical thickness, LGI, and volumes of subcortical structures. Uncorrected P values ≤ 0.001 and R2 > 0.16 were considered significant. RESULTS: The cortical thickness and LGI decreased with age throughout almost all brain regions (R2 > 0.16; P ≤ 0.001). Except for the volumes of the WM and 4th ventricle (R2 < 0.16; P > 0.001), the volumes of the GM, WMH, lateral ventricle, inferior lateral ventricle, and 3rd ventricle showed a nonlinear correlation with aging (R2 > 0.16; P ≤ 0.001). For deep gray matter nuclei, the thalamus volume was significantly decreased with aging (R2 = 0.256; P = 0.001). Additionally, the hippocampus volume was initially increased and then decreased at age of 50, mainly in the granule cell layer of the dentate gyrus (GC-DG), cornus ammonis 2/3 (CA2/3), CA4, and fissure (R2 > 0.16; P ≤ 0.001). The volumes of the putamen, pallidum, accumbens area, amygdala and caudate showed no significance with aging (R2 < 0.16; P > 0.001). DATA CONCLUSION: The results comprehensively show the relationships between age and cerebral structures in multiple brain regions, and these findings may help identify normal aging and other age-related neuroradiological disorders. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:152-163.