Development of an organ-specific insert phantom generated using a 3D printer for investigations of cardiac computed tomography protocols

Study of Attenuation Correction Using a Cardiac Dynamic Phantom: Synchronized Time-Phase-Gated Attenuation Correction Method

In cardiac nuclear medicine examinations, absorption in the body is the main factor in the degradation of the image quality. The Chang and external source methods were used to correct for absorption in the body. However, fundamental studies on attenuation correction for electrocardiogram (ECG)-synchronized CT imaging have not been performed. Therefore, we developed and improved an ECG-synchronized cardiac dynamic phantom and investigated the synchronized time-phase-gated attenuation correction (STPGAC) method using ECG-synchronized SPECT and CT images of the same time phase. Methods: As a basic study, SPECT was performed using synchronized time-phase-gated (STPG) SPECT and non-phase-gated (NPG) SPECT. The attenuation-corrected images were, first, CT images with the same time phase as the ECG waveform of the gated SPECT acquisition (with CT images with the ECG waveform of the CT acquisition as the reference); second, CT images with asynchronous ECG; third, CT images of the 75% region; and fourth, CT images of the 40% region. Results: In the analysis of cardiac function in the phantom experiment, left ventricle ejection fraction (heart rate, 11.5%-13.4%; myocardial wall, 49.8%-55.7%) in the CT images was compared with that in the STPGAC method (heart rate, 11.5%-13.3%; myocardial wall, 49.6%-55.5%), which was closer in value to that of the STPGAC method. In the phantom polar map segment analyses, none of the images showed variability (F (10,10) < 0.5, P = 0.05). All images were correlated (r = 0.824-1.00). Conclusion: In this study, we investigated the STPGAC method using a SPECT/CT system. The STPGAC method showed similar values of cardiac function analysis to the CT images, suggesting that the STPGAC method accurately reconstructed the distribution of blood flow in the myocardial region. However, the target area for attenuation correction of the heart region was smaller than that of the whole body, and changing the gated SPECT conditions and attenuation-corrected images did not affect myocardial blood flow analysis.

Cardiovascular computed tomography in cardiovascular disease: An overview of its applications from diagnosis to prediction

Cardiovascular computed tomography angiography (CTA) is a widely used imaging modality in the diagnosis of cardiovascular disease. Advancements in CT imaging technology have further advanced its applications from high diagnostic value to minimising radiation exposure to patients. In addition to the standard application of assessing vascular lumen changes, CTA-derived applications including 3D printed personalised models, 3D visualisations such as virtual endoscopy, virtual reality, augmented reality and mixed reality, as well as CT-derived hemodynamic flow analysis and fractional flow reserve (FFRCT) greatly enhance the diagnostic performance of CTA in cardiovascular disease. The widespread application of artificial intelligence in medicine also significantly contributes to the clinical value of CTA in cardiovascular disease. Clinical value of CTA has extended from the initial diagnosis to identification of vulnerable lesions, and prediction of disease extent, hence improving patient care and management. In this review article, as an active researcher in cardiovascular imaging for more than 20 years, I will provide an overview of cardiovascular CTA in cardiovascular disease. It is expected that this review will provide readers with an update of CTA applications, from the initial lumen assessment to recent developments utilising latest novel imaging and visualisation technologies. It will serve as a useful resource for researchers and clinicians to judiciously use the cardiovascular CT in clinical practice.

Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment

Cardiovascular CT is being widely used in the diagnosis of cardiovascular disease due to the rapid technological advancements in CT scanning techniques. These advancements include the development of multi-slice CT, from early generation to the latest models, which has the capability of acquiring images with high spatial and temporal resolution. The recent emergence of photon-counting CT has further enhanced CT performance in clinical applications, providing improved spatial and contrast resolution. CT-derived fractional flow reserve is superior to standard CT-based anatomical assessment for the detection of lesion-specific myocardial ischemia. CT-derived 3D-printed patient-specific models are also superior to standard CT, offering advantages in terms of educational value, surgical planning, and the simulation of cardiovascular disease treatment, as well as enhancing doctor-patient communication. Three-dimensional visualization tools including virtual reality, augmented reality, and mixed reality are further advancing the clinical value of cardiovascular CT in cardiovascular disease. With the widespread use of artificial intelligence, machine learning, and deep learning in cardiovascular disease, the diagnostic performance of cardiovascular CT has significantly improved, with promising results being presented in terms of both disease diagnosis and prediction. This review article provides an overview of the applications of cardiovascular CT, covering its performance from the perspective of its diagnostic value based on traditional lumen assessment to the identification of vulnerable lesions for the prediction of disease outcomes with the use of these advanced technologies. The limitations and future prospects of these technologies are also discussed.

A customized anthropomorphic 3D-printed phantom to reproducibility assessment in computed tomography: an oncological case study

Introduction

Studies on computed tomography (CT) reproducibility at different acquisition parameters have to take into account radiation dose administered and related ethical issues. 3D-printed phantoms provide the possibility to investigate these features deeply and to foster CT research, also taking advantage by outperforming new generation scanners. The aim of this study is to propose a new anthropomorphic 3D-printed phantom for chest lesions, tailored on a real patient CT scan, to investigate the variability of volume and Hounsfield Unit (HU) measurements at different CT acquisition parameters.

Methods

The chest CT of a 75-year-old patient with a paramediastinal lung lesion was segmented based on an eight-compartment approach related to HU ranges (air lung, lung interstitium, fat, muscle, vascular, skin, bone, and lesion). From each mask produced, the 3D.stl model was exported and linked to a different printing infill value, based on a preliminary test and HU ratios derived from the patient scan. Fused deposition modeling (FDM) technology printing was chosen with filament materials in polylactic acid (PLA). Phantom was acquired at 50 mAs and three different tube voltages of 80, 100, and 120 kVp on two different scanners, namely, Siemens Somatom Force (Siemens Healthineers, Erlangen, Germany; same setting of real patient for 80 kVp acquisition) and GE 750 HD CT (GE Healthcare, Chicago, IL). The same segmentation workflow was then applied on each phantom acquisition after coregistration pipeline, and Dice Similarity Coefficient (DSC) and HU averages were extracted and compared for each compartment.

Results

DSC comparison among real patient versus phantom scans at different kVp, and on both CT scanners, demonstrated a good overlap of different compartments and lesion vascularization with a higher similarity for lung and lesion masks for each setting (about 0.9 and 0.8, respectively). Although mean HU was not comparable with real data, due to the PLA material, the proportion of intensity values for each compartment remains respected.

Discussion

The proposed approach demonstrated the reliability of 3D-printed technology for personalized approaches in CT research, opening to the application of the same workflow to other oncological fields.

Three-Dimensional Bioprinting in Cardiovascular Disease: Current Status and Future Directions

Three-dimensional (3D) printing plays an important role in cardiovascular disease through the use of personalised models that replicate the normal anatomy and its pathology with high accuracy and reliability. While 3D printed heart and vascular models have been shown to improve medical education, preoperative planning and simulation of cardiac procedures, as well as to enhance communication with patients, 3D bioprinting represents a potential advancement of 3D printing technology by allowing the printing of cellular or biological components, functional tissues and organs that can be used in a variety of applications in cardiovascular disease. Recent advances in bioprinting technology have shown the ability to support vascularisation of large-scale constructs with enhanced biocompatibility and structural stability, thus creating opportunities to replace damaged tissues or organs. In this review, we provide an overview of the use of 3D bioprinting in cardiovascular disease with a focus on technologies and applications in cardiac tissues, vascular constructs and grafts, heart valves and myocardium. Limitations and future research directions are highlighted.

Three-dimensional printing of patient-specific computed tomography lung phantoms: a reader study

In modern clinical decision-support algorithms, heterogeneity in image characteristics due to variations in imaging systems and protocols hinders the development of reproducible quantitative measures including for feature extraction pipelines. With the help of a reader study, we investigate the ability to provide consistent ground-truth targets by using patient-specific 3D-printed lung phantoms. PixelPrint was developed for 3D-printing lifelike computed tomography (CT) lung phantoms by directly translating clinical images into printer instructions that control density on a voxel-by-voxel basis. Data sets of three COVID-19 patients served as input for 3D-printing lung phantoms. Five radiologists rated patient and phantom images for imaging characteristics and diagnostic confidence in a blinded reader study. Effect sizes of evaluating phantom as opposed to patient images were assessed using linear mixed models. Finally, PixelPrint's production reproducibility was evaluated. Images of patients and phantoms had little variation in the estimated mean (0.03-0.29, using a 1-5 scale). When comparing phantom images to patient images, effect size analysis revealed that the difference was within one-third of the inter- and intrareader variabilities. High correspondence between the four phantoms created using the same patient images was demonstrated by PixelPrint's production repeatability tests, with greater similarity scores between high-dose acquisitions of the phantoms than between clinical-dose acquisitions of a single phantom. We demonstrated PixelPrint's ability to produce lifelike CT lung phantoms reliably. These phantoms have the potential to provide ground-truth targets for validating the generalizability of inference-based decision-support algorithms between different health centers and imaging protocols and for optimizing examination protocols with realistic patient-based phantoms. Classification: CT lung phantoms, reader study.

Low-cost 3D-printed anthropomorphic cardiac phantom, for computed tomography automatic left ventricle segmentation and volumetry - A pilot study

INTRODUCTION

Accurate cardiac left ventricle (LV) delineation is essential to CT-derived left ventricular ejection fraction (LVEF). To evaluate dose-reduction potential, an anatomically accurate heart phantom, with realistic X-ray attenuation is required. We demonstrated and tested a custom-made phantom using 3D-printing, and examined the influence of image noise on automatically measured LV volumes METHODS: A single coronary CT angiography (CCTA) dataset was segmented and converted to Standard Tessellation Language (STL) mesh, using open-source software. A 3D-printed model, with hollow left heart chambers, was printed and cavities filled with gelatinized contrast media. This was CT-scanned in an anthropomorphic chest phantom, at different exposure conditions. LV and "myocardium" noise and attenuation was measured. LV volume was automatically measured using two different methods. We calculated Spearmans' correlation of LV volume with noise and contrast-noise ratio respectively om 486 scans of the phantom. Source images were compared to one phantom series with similar parameters. This was done using Dice coefficient on LV short-axis segmentations.

RESULTS

Phantom "Myocardium" and LV attenuation was comparable to measurements on source images. Automatic volume measurement succeeded, with mean volume deviation to patient images less than 2 ml. There was a moderate correlation of volume with CNR, and strong correlation of volume with image noise. With papillary muscles included in LV volume, the correlation was positive, but negative when excluded. Variation of volumes was lowest at 90-100 kVp for both methods in the 486 repeat scans. The Dice coefficient was 0.87, indicating high overlap between the single phantom series and source scan. Cost of 3D-printer and materials was 400 and 30 Euro respectively.

CONCLUSION

Both anatomically and radiologically the phantom mimicked the source scans closely. LV volumetry was reliably performed with automatic algorithms.

IMPLICATIONS FOR PRACTICE

Patient-specific cardiac phantoms may be produced at minimal cost and can potentially be used for other anatomies and pathologies. This enables radiographic phantom studies without need for dedicated 3D-labs or expensive commercial phantoms.

3D Printed Models in Cardiovascular Disease: An Exciting Future to Deliver Personalized Medicine

3D printing has shown great promise in medical applications with increased reports in the literature. Patient-specific 3D printed heart and vascular models replicate normal anatomy and pathology with high accuracy and demonstrate superior advantages over the standard image visualizations for improving understanding of complex cardiovascular structures, providing guidance for surgical planning and simulation of interventional procedures, as well as enhancing doctor-to-patient communication. 3D printed models can also be used to optimize CT scanning protocols for radiation dose reduction. This review article provides an overview of the current status of using 3D printing technology in cardiovascular disease. Limitations and barriers to applying 3D printing in clinical practice are emphasized while future directions are highlighted.

3D printed anthropomorphic left ventricular myocardial phantom for nuclear medicine imaging applications

Background

Anthropomorphic torso phantoms, including a cardiac insert, are frequently used to investigate the imaging performance of SPECT and PET systems. These phantom solutions are generally featuring a simple anatomical representation of the heart. 3D printing technology paves the way to create cardiac phantoms with more complex volume definition. This study aimed to describe how a fillable left ventricular myocardium (LVm) phantom can be manufactured using geometry extracted from a patient image.

Methods

The LVm of a healthy subject was segmented from ¹⁸F-FDG attenuation corrected PET image set. Two types of phantoms were created and 3D printed using polyethylene terephthalate glycol (PETG) material: one representing the original healthy LVm, and the other mimicking myocardium with a perfusion defect. The accuracy of the LVm phantom production was investigated by high-resolution CT scanning of 3 identical replicas. ^99mTc SPECT acquisitions using local cardiac protocol were performed, without additional scattering media (“in air” measurements) for both phantom types. Furthermore, the healthy LVm phantom was inserted in the commercially available DataSpectrum Anthropomorphic Torso Phantom (“in torso” measurement) and measured with hot background and hot liver insert.

Results

Phantoms were easy to fill without any air-bubbles or leakage, were found to be reproducible and fully compatible with the torso phantom. Seventeen segments polar map analysis of the "in air” measurements revealed that a significant deficit in the distribution appeared where it was expected. 59% of polar map segments had less than 5% deviation for the "in torso” and "in air” measurement comparison. Excluding the deficit area, neither comparison had more than a 12.4% deviation. All the three polar maps showed similar apex and apical region values for all configurations.

Conclusions

Fillable anthropomorphic 3D printed phantom of LVm can be produced with high precision and reproducibility. The 3D printed LVm phantoms were found to be suitable for SPECT image quality tests during different imaging scenarios. The flexibility of the 3D printing process presented in this study provides scalable and anthropomorphic image quality phantoms in nuclear cardiology imaging.

PixelPrint: Three-dimensional printing of realistic patient-specific lung phantoms for CT imaging

Phantoms are essential tools for assessing and verifying performance in computed tomography (CT). Realistic patient-based lung phantoms that accurately represent textures and densities are essential in developing and evaluating novel CT hardware and software. This study introduces PixelPrint, a 3D-printing solution to create patient-specific lung phantoms with accurate contrast and textures. PixelPrint converts patient images directly into printer instructions, where density is modeled as the ratio of filament to voxel volume to emulate local attenuation values. For evaluation of PixelPrint, phantoms based on four COVID-19 pneumonia patients were manufactured and scanned with the original (clinical) CT scanners and protocols. Density and geometrical accuracies between phantom and patient images were evaluated for various anatomical features in the lung, and a radiomic feature comparison was performed for mild, moderate, and severe COVID-19 pneumonia patient-based phantoms. Qualitatively, CT images of the patient-based phantoms closely resemble the original CT images, both in texture and contrast levels, with clearly visible vascular and parenchymal structures. Regions-of-interest (ROIs) comparing attenuation demonstrated differences below 15 HU. Manual size measurements performed by an experienced thoracic radiologist revealed a high degree of geometrical correlation between identical patient and phantom features, with differences smaller than the intrinsic spatial resolution of the images. Radiomic feature analysis revealed high correspondence, with correlations of 0.95-0.99 between patient and phantom images. Our study demonstrates the feasibility of 3D-printed patient-based lung phantoms with accurate geometry, texture, and contrast that will enable protocol optimization, CT research and development advancements, and generation of ground-truth datasets for radiomic evaluations.

Three-dimensional printing of patient-specific lung phantoms for CT imaging: Emulating lung tissue with accurate attenuation profiles and textures

PURPOSE

Phantoms are a basic tool for assessing and verifying performance in CT research and clinical practice. Patient-based realistic lung phantoms accurately representing textures and densities are essential in developing and evaluating novel CT hardware and software. This study introduces PixelPrint, a 3D printing solution to create patient-based lung phantoms with accurate attenuation profiles and textures.

METHODS

PixelPrint, a software tool, was developed to convert patient digital imaging and communications in medicine (DICOM) images directly into FDM printer instructions (G-code). Density was modeled as the ratio of filament to voxel volume to emulate attenuation profiles for each voxel, with the filament ratio controlled through continuous modification of the printing speed. A calibration phantom was designed to determine the mapping between filament line width and Hounsfield units (HU) within the range of human lungs. For evaluation of PixelPrint, a phantom based on a single human lung slice was manufactured and scanned with the same CT scanner and protocol used for the patient scan. Density and geometrical accuracy between phantom and patient CT data were evaluated for various anatomical features in the lung.

RESULTS

For the calibration phantom, measured mean HU show a very high level of linear correlation with respect to the utilized filament line widths, (r > 0.999). Qualitatively, the CT image of the patient-based phantom closely resembles the original CT image both in texture and contrast levels (from -800 to 0 HU), with clearly visible vascular and parenchymal structures. Regions of interest comparing attenuation illustrated differences below 15 HU. Manual size measurements performed by an experienced thoracic radiologist reveal a high degree of geometrical correlation of details between identical patient and phantom features, with differences smaller than the intrinsic spatial resolution of the scans.

CONCLUSION

The present study demonstrates the feasibility of 3D-printed patient-based lung phantoms with accurate organ geometry, image texture, and attenuation profiles. PixelPrint will enable applications in the research and development of CT technology, including further development in radiomics.

Design of a 3D printed coronary artery model for CT optimization

INTRODUCTION

To design a custom phantom of the coronary arteries to optimize CT coronary angiography (CCTA) protocols.

METHODS

Characteristics of the left and right coronary arteries (mean Hounsfield Unit (HU) values and diameters) were collected from consecutive CCTA examinations (n = 43). Four different materials (two mixtures of glycerine, gelatine and water, pig hearts, Ecoflex™ silicone) were scanned inside a Lungman phantom using the CCTA protocol to find the closest model to in vivo data. A 3D printed model of the coronary artery tree was created using CCTA data by exporting a CT volume rendering into Autodesk Meshmixer™ software. The model was placed in an acid bath for 5 h, then covered in Ecoflex™, which was removed after drying. Both the Ecoflex™ and pig heart were later filled with a mixture of contrast (Visipaque 320 mg I/ml), NaCl and gelatin and scanned with different levels of tube current and iterative reconstruction (ASiR-V). Objective (HU, noise and size (vessel diameter) and subjective analysis were performed on all scans.

RESULTS

The gelatine mixtures had HU values of 130 and 129, Ecoflex™ 65 and the pig heart 56. At the different mA/ASiR-V levels the contrast filled Ecoflex™ had a mean HU 318 ± 4, noise 47±7HU and diameter of 4.4 mm. The pig heart had a mean HU of 209 ± 5, noise 38±4HU and a diameter of 4.4 mm. With increasing iterative reconstruction level the visualisation of the pig heart arteries decreased so no measurements could be performed.

CONCLUSION

The use of a 3D printed model of the arteries and casting with the Ecoflex™ silicone is the most suitable solution for a custom-designed phantom.

IMPLICATIONS FOR PRACTICE

Custom designed phantoms using 3D printing technology enable cost effective optimisation of CT protocols.

0° vs. 180° CT localiser: The effect of vertical off-centring, phantom positioning and tube voltage on dose optimisation in multidetector computed tomography

Introduction

Patient positioning is an essential consideration for the optimisation of radiation dose during CT examinations. The study objectives seek to explore the effects of vertical off‐centring, localiser direction (0° and 180°), and phantom positioning (supine and prone) on radiation dose, using three different tube voltages in multidetector computed tomography (MDCT) imaging.

Methods

The trunk of a PBU‐60 anthropomorphic phantom was imaged using a Discovery CT750 HD – 128 slice (GE Healthcare). Images employing 0° and 180° localisers were acquired in supine and prone orientation for each combination of vertical off‐centring (±100, ±60 and ±30 mm) and different tube voltages (80, 120 and 140 kVp), using the system’s automatic tube current modulation (ATCM) function. The displayed volume CT dose index (CTDI_vol) and dose length product (DLP) were recorded.

Results

With incremental table off‐centring of ±100 mm, the dose at 120 kVp in the supine position ranged from 63% to 196% (0° localiser) and from 66% to 191% (180° localiser) as compared to iso‐centre. While in the prone position, the dose ranged from 62% to 195% (0° localiser); and 62% to 193% (180° localiser), with a notable dose increase at higher tube voltages. Dose variation and vertical off‐centring showed a significant relationship for both 0° and 180° localisers (r = 0.94 and 0.96, respectively, P < 0.001). The CTDI_vol variation between supine and prone phantom positions at ±100 mm off‐centring was 0.22 mGy (2.9%), and 0.19 mGy (2.3%) when the 0° and 180 ° localisers were utilised, respectively.

Conclusions

Phantom off‐centring and localiser direction evidenced large dose variation. It is recommended that the 0° localiser is employed during CT examinations, in order to minimise the potential additional radiation dose which may result from off‐centring and the use of lower tube voltages where clinically appropriate.

Use of Three-Dimensional Printing in Modelling an Anatomical Structure with a High Computed Tomography Attenuation Value: A Feasibility Study

Introduction: Three-dimensional (3D) printing provides an opportunity to develop anthropomorphic computed tomography (CT) phantoms with anatomical and radiological features mimicking a range of patients’ conditions, thus allowing development of individualised, low dose scanning protocols. However, previous studies of 3D printing in CT phantom development could only create anatomical structures using potassium iodide with attenuation values up to 1200 HU which is insufficient to mimic the radiological features of some high attenuation structures such as cortical bone. This study aimed at investigating the feasibility of using 3D printing in modelling cortical bone with a non-iodinated material. Methods: This study had 2 stages. Stage 1 involved a vat photopolymerisation 3D printer to directly print cube phantoms with different percentage compositions of calcium phosphate (CP) and resin (approach 1), and approach 2 using a material extrusion 3D printer to develop a cube mould for infilling of the CP with hardener as the phantom. The approach able to create the cube phantom with the CT attenuation value close to that of a tibial mid-diaphysis cortex of a real patient, 1475±205 HU was employed to develop a tibial mid-diaphysis phantom. The mean CT numbers of the cube and tibia phantoms were measured and compared with that of the original CT dataset through unpaired t-test. Results: All phantoms were scanned by CT using a lower extremity scanning protocol. The moulding approach was selected to develop the tibia middiaphysis phantom with CT attenuation value, 1434±184 HU which was not statistically significantly different from the one of the original dataset (p = 0.721). Conclusion: This study demonstrates the feasibility to use the material extrusion 3D printer to create a tibial mid-diaphysis mould for infilling of the CP as an anthropomorphic CT phantom and the attenuation value of its cortex matches the real patient’s one.

A Comparison of the Distortion in the Same Field MRI and MR-Linac System With a 3D Printed Phantom

PURPOSE

A 3D printed geometric phantom was developed that can be scanned with computed tomography (CT) and magnetic resonance imaging (MRI) to measure the geometric distortion and determine the relevant dose changes.

MATERIALS AND METHODS

A self-designed 3D printed photosensitive resin phantom was used, which adopts grid-like structures and has 822 1 cm2 squares. The scanning plan was delivered by three MRI scanners: the Elekta Unity MR-Linac 1.5T, GE Signa HDe 1.5T, and GE Discovery-sim 750 3.0T. The geometric distortion comparison was concentrated on two 1.5T MRI systems, whereas the 3.0T MRI was used as a supplemental experiment. The most central transverse images in each dataset were selected to demonstrate the plane distortion. Some mark points were selected to analyze the distortion in the 3D direction based on the plane geometric distortion. A treatment plan was created with the off-line Monaco system.

RESULTS

The distortion increases gradually from the center to the outside. The distortion range is 0.79 ± 0.40 mm for the Unity, 1.31 ± 0.56 mm for the GE Signa HDe, and 2.82 ± 1.48 mm for the GE Discovery-sim 750. Additionally, the geometric distortion slightly affects the actual planning dose of the radiotherapy.

CONCLUSION

Geometric distortion increases gradually from the center to the outside. The distortion values of the Unity were smaller than those of the GE Signa HDe, and the Unity has the smallest geometric distortion. Finally, the Unity's dose variation best matched with the standard treatment plan.

Clinical Applications of Patient-Specific 3D Printed Models in Cardiovascular Disease: Current Status and Future Directions

Three-dimensional (3D) printing has been increasingly used in medicine with applications in many different fields ranging from orthopaedics and tumours to cardiovascular disease. Realistic 3D models can be printed with different materials to replicate anatomical structures and pathologies with high accuracy. 3D printed models generated from medical imaging data acquired with computed tomography, magnetic resonance imaging or ultrasound augment the understanding of complex anatomy and pathology, assist preoperative planning and simulate surgical or interventional procedures to achieve precision medicine for improvement of treatment outcomes, train young or junior doctors to gain their confidence in patient management and provide medical education to medical students or healthcare professionals as an effective training tool. This article provides an overview of patient-specific 3D printed models with a focus on the applications in cardiovascular disease including: 3D printed models in congenital heart disease, coronary artery disease, pulmonary embolism, aortic aneurysm and aortic dissection, and aortic valvular disease. Clinical value of the patient-specific 3D printed models in these areas is presented based on the current literature, while limitations and future research in 3D printing including bioprinting of cardiovascular disease are highlighted.

Increasing iterative reconstruction strength at low tube voltage in coronary CT angiography protocols using 3D-printed and Catphan® 500 phantoms

Purpose

The purpose of this study was to investigate the effect of increasing iterative reconstruction (IR) algorithm strength at different tube voltages in coronary computed tomography angiography (CCTA) protocols using a three‐dimensional (3D)‐printed and Catphan^® 500 phantoms.

Methods

A 3D‐printed cardiac insert and Catphan 500 phantoms were scanned using CCTA protocols at 120 and 100 kVp tube voltages. All CT acquisitions were reconstructed using filtered back projection (FBP) and Adaptive Statistical Iterative Reconstruction (ASIR) algorithm at 40% and 60% strengths. Image quality characteristics such as image noise, signal–noise ratio (SNR), contrast–noise ratio (CNR), high spatial resolution, and low contrast resolution were analyzed.

Results

There was no significant difference (P > 0.05) between 120 and 100 kVp measures for image noise for FBP vs ASIR 60% (16.6 ± 3.8 vs 16.7 ± 4.8), SNR of ASIR 40% vs ASIR 60% (27.3 ± 5.4 vs 26.4 ± 4.8), and CNR of FBP vs ASIR 40% (31.3 ± 3.9 vs 30.1 ± 4.3), respectively. Based on the Modulation Transfer Function (MTF) analysis, there was a minimal change of image quality for each tube voltage but increases when higher strengths of ASIR were used. The best measure of low contrast detectability was observed at ASIR 60% at 120 kVp.

Conclusions

Changing the IR strength has yielded different image quality noise characteristics. In this study, the use of 100 kVp and ASIR 60% yielded comparable image quality noise characteristics to the standard CCTA protocols using 120 kVp of ASIR 40%. A combination of 3D‐printed and Catphan^® 500 phantoms could be used to perform CT dose optimization protocols.

Evaluation of an integrated 3D-printed phantom for coronary CT angiography using iterative reconstruction algorithm

INTRODUCTION

3D-printed imaging phantoms are now increasingly available and used for computed tomography (CT) dose optimisation study and image quality analysis. The aim of this study was to evaluate the integrated 3D-printed cardiac insert phantom when evaluating iterative reconstruction (IR) algorithm in coronary CT angiography (CCTA) protocols.

METHODS

The 3D-printed cardiac insert phantom was positioned into a chest phantom and scanned with a 16-slice CT scanner. Acquisitions were performed with CCTA protocols using 120 kVp at four different tube currents, 300, 200, 100 and 50 mA (protocols A, B, C and D, respectively). The image data sets were reconstructed with a filtered back projection (FBP) and three different IR algorithm strengths. The image quality metrics of image noise, signal-noise ratio (SNR) and contrast-noise ratio (CNR) were calculated for each protocol.

RESULTS

Decrease in dose levels has significantly increased the image noise, compared to FBP of protocol A (P < 0.001). As a result, the SNR and CNR were significantly decreased (P < 0.001). For FBP, the highest noise with poor SNR and CNR was protocol D with 19.0 ± 1.6 HU, 18.9 ± 2.5 and 25.1 ± 3.6, respectively. For IR algorithm, the highest strength (AIDR3Dstrong ) yielded the lowest noise with excellent SNR and CNR.

CONCLUSIONS

The use of IR algorithm and increasing its strengths have reduced noise significantly and thus increased the SNR and CNR when compared to FBP. Therefore, this integrated 3D-printed phantom approach could be used for dose optimisation study and image quality analysis in CCTA protocols.

Use of Three-dimensional Printing in the Development of Optimal Cardiac CT Scanning Protocols

Three-dimensional (3D) printing is increasingly used in medical applications with most of the studies focusing on its applications in medical education and training, pre-surgical planning and simulation, and doctor-patient communication. An emerging area of utilising 3D printed models lies in the development of cardiac computed tomography (CT) protocols for visualisation and detection of cardiovascular disease. Specifically, 3D printed heart and cardiovascular models have shown potential value in the evaluation of coronary plaques and coronary stents, aortic diseases and detection of pulmonary embolism. This review article provides an overview of the clinical value of 3D printed models in these areas with regard to the development of optimal CT scanning protocols for both diagnostic evaluation of cardiovascular disease and reduction of radiation dose. The expected outcomes are to encourage further research towards this direction.

A Systematic Review on 3D-Printed Imaging and Dosimetry Phantoms in Radiation Therapy

INTRODUCTION

Additive manufacturing or 3-dimensional printing has become a widespread technology with many applications in medicine. We have conducted a systematic review of its application in radiation oncology with a particular emphasis on the creation of phantoms for image quality assessment and radiation dosimetry. Traditionally used phantoms for quality assurance in radiotherapy are often constraint by simplified geometry and homogenous nature to perform imaging analysis or pretreatment dosimetric verification. Such phantoms are limited due to their ability in only representing the average human body, not only in proportion and radiation properties but also do not accommodate pathological features. These limiting factors restrict the patient-specific quality assurance process to verify image-guided positioning accuracy and/or dose accuracy in "water-like" condition.

METHODS AND RESULTS

English speaking manuscripts published since 2008 were searched in 5 databases (Google Scholar, Scopus, PubMed, IEEE Xplore, and Web of Science). A significant increase in publications over the 10 years was observed with imaging and dosimetry phantoms about the same total number (52 vs 50). Key features of additive manufacturing are the customization with creation of realistic pathology as well as the ability to vary density and as such contrast. Commonly used printing materials, such as polylactic acid, acrylonitrile butadiene styrene, high-impact polystyrene and many more, are utilized to achieve a wide range of achievable X-ray attenuation values from -1000 HU to 500 HU and higher. Not surprisingly, multimaterial printing using the polymer jetting technology is emerging as an important printing process with its ability to create heterogeneous phantoms for dosimetry in radiotherapy.

CONCLUSION

Given the flexibility and increasing availability and low cost of additive manufacturing, it can be expected that its applications for radiation medicine will continue to increase.

Development of a CT imaging phantom of anthromorphic lung using fused deposition modeling 3D printing

Development of patient-specific CT imaging phantoms with randomly incorporated lesions of various shapes and sizes for calibrating image intensity and validating quantitative measurement software is very challenging. In this investigation, a physical phantom that accurately represents a patient's specific anatomy and the intensity of lung CT images at the voxel level will be fabricated using fused deposition modeling (FDM) 3D printing. Segmentation and modeling of a patient's CT data were performed by an expert and the results were confirmed by a thoracic radiologist with more than 20 years of experience. This facilitated the extraction of the details of the patient's anatomy; various kinds of nodules with different shapes and sizes were randomly added to the modeled lung for evaluating the size-accuracy of the quantification software. To achieve these Hounsfield Units (HU) ranges for the corresponding voxels in acquired CT scans, the infill ratios of FDM 3D printing were controlled. Based on CT scans of the 3D printed phantoms, the measured HU for normal pulmonary parenchyma, ground glass opacity (GGO), and solid nodules were determined to be within target HU ranges. The accuracy of the mean absolute difference and the mean relative difference of nodules were less than 0.55 ± 0.30 mm and 3.72 ± 1.64% (mean difference ± 95 CI), respectively. Patient-specific CT imaging phantoms were designed and manufactured using an FDM printer, which could be applied for the precise calibration of CT intensity and the validation of image quantification software.

Personalized 3D printed coronary models in coronary stenting

Background

3D printing has shown great promise in cardiovascular disease, with reports mainly focusing on pre-surgical planning and medical education. Research on utilization of 3D printed models in simulating coronary stenting has not been reported. In this study, we presented our experience of placing coronary stents into personalized 3D printed coronary models with the aim of determining stent lumen visibility with images reconstructed with different postprocessing views and algorithms.

Methods

A total of six coronary stents with diameter ranging from 2.5 to 4.0 mm were placed into 3 patient-specific 3D printed coronary models for simulation of coronary stenting. The 3D printed models were placed in a plastic container and scanned on a 192-slice third generation dual-source CT scanner with images reconstructed with soft (Bv36) and sharp (Bv59) kernel algorithms. Thick and thin slab maximum-intensity projection (MIP) images were also generated from the original CT data for comparison of stent lumen visibility. Stent lumen diameter was measured on 2D axial and MIP images, while stent diameter was measured on 3D volume rendering images. 3D virtual intravascular endoscopy (VIE) images were generated to provide intraluminal views of the coronary wall and stent appearances.

Results

All of these stents were successfully placed into the right and left coronary arteries but 2 of them did not obtain wall apposition along the complete length. The stent lumen visibility ranged from 54 to 97%, depending on the stent location in the coronary arteries. The mean stent lumen diameters measured on 2D axial, thin and thick slab MIP images were found to be significantly smaller than the actual size (P<0.01). Thick slab MIP images resulted in measured stent lumen diameters smaller than those from thin slab MIP images, with significant differences noticed in most of the measurements (4 out of 6 stents) (P<0.05), and no significant differences in the remaining 2 stents (P=0.19-0.38). In contrast, 3D volume rendering images allowed for more accurate measurements with measured stent diameters close to the actual dimensions in most of these coronary stents, except for the stent placed at the right coronary artery in one of the models due to insufficient expansion of the stent. Images reconstructed with sharp kernel Bv59 significantly improved stent lumen visibility when compared to the smooth Bv36 kernel (P=0.01). 3D VIE was successfully generated in all of the datasets with clear visualization of intraluminal views of the stents in relation to the coronary wall.

Conclusions

This preliminary report shows the feasibility of using 3D printed coronary artery models in coronary stenting for investigation of optimal coronary CT angiography protocols. Future studies should focus on placement of more stents with a range of stent diameters in the quest to reduce the need for invasive angiography for surveillance.

Patient-specific 3D printed pulmonary artery model with simulation of peripheral pulmonary embolism for developing optimal computed tomography pulmonary angiography protocols

BACKGROUND

Computed tomography pulmonary angiography (CTPA) is the preferred imaging modality for diagnosis of patients with suspected pulmonary embolism (PE). Radiation dose associated with CTPA has been significantly reduced due to the use of dose-reduction strategies, however, investigation of low-dose CTPA with use of different kVp and pitch values has not been systematically studied. The aim of this study was to utilize a 3D printed pulmonary model with simulation of small thrombus in the pulmonary arteries for development of optimal CTPA protocols.

METHODS

Animal blood clots were inserted into the pulmonary arteries to simulate peripheral embolism based on a realistic 3D printed pulmonary artery model. The 3D printed model was scanned with 192-slice 3rd generation dual-source CT with 1 mm slice thickness and 0.5 mm reconstruction interval. All images were reconstructed with advanced modelled iterative reconstruction (IR) at a strength level of 3. CTPA scanning parameters were as follows: 70, 80, 100 and 120 kVp, 0.9, 2.2 and 3.2 pitch values. Quantitative assessment of image quality was determined by measuring signal-to-noise ratio (SNR) in both main pulmonary arteries, while qualitative analysis of images was scored by two experienced radiologists (score of 1 indicates poor visualization of thrombus with no confidence, and score of 5 excellent visualization of thrombus with high confidence) to determine the image quality in relation to different scanning protocols for detection of thrombus in the pulmonary arteries.

RESULTS

No significant differences were found in SNR measurements among all CTPA protocols (P>0.05), regardless of kVp or pitch values used, although SNR was higher with 120 kVp and 0.9 and 2.2 pitch protocols than that in other protocols. The thrombi were detected in all images, with 70 kVp and 3.2 pitch protocol scored the lowest with a score of 3 by two observers, and images with other protocols were scored 4 or 5. Lowering kVp from 120 to 70 with use of high-pitch 2.2 or 3.2 protocol resulted in up to 80% dose reduction without significantly affecting image quality.

CONCLUSIONS

Low-dose CT pulmonary angiography protocols comprising 70 kVp and high pitch 2.2 or 3.2 allow for detection of peripheral PE with significant reduction in radiation dose while images are still considered diagnostic.

3D printing in medical imaging and healthcare services

Three-dimensional (3D) printing technology has demonstrated a huge potential for the future of medicine. Since its introduction, it has been used in various areas, for example building anatomical models, personalising medical devices and implants, aiding in precision medical interventions and the latest development, 3D bioprinting. This commentary is provided to outline the current use of 3D printing in medical imaging and its future directions for advancing the healthcare services.

3D printing and medical imaging

Three-dimensional (3D) printing and medical imaging have a complementary association, the benefits and application areas of which are increasingly documented and further illustrated in this journal publication. Medical imaging data can be appropriately processed (i.e. segmented) to provide the geometric information from which accurate and realistic 3D medical models can be generated. The resulting models can be printed in a range of different materials to suit their use as phantoms in medical radiation and imaging studies, for medical imaging education and training or patient communication.