Explore the vast range of titles available.

Background: Patients with liver pathology benefit from image-guided interventions. Training for interventional procedures is recommended to be performed on liver phantoms until a basic proficiency is reached. In the last 40 years, several attempts have been made to develop materials to mimic the imaging characteristics of the human liver in order to create liver phantoms. There is still a lack of accessible, reproducible and cost-effective soft liver phantoms for image-guided procedure training. Methods: Starting from a CT-scan DICOM file, we created a 3D-printed liver mold using InVesalius (Centro de Tecnologia da informação Renato Archer CTI, InVesalius 3 open-source software, Campinas, Brazil) for segmentation, Autodesk Fusion 360 with Netfabb (Autodesk software company, Fusion 360 2.0.19426 with Autodesk Netfabb Premium 2023.0 64-Bit Edition, San Francisco, CA, USA) for 3D modeling and Stratasys Fortus 380 mc 3D printer (Stratasys 3D printing company, Fortus 380 mc 3D printer, Minneapolis, MN, USA). Using the 3D-printed mold, we created 14 gelatin-based liver phantoms with 14 different recipes, using water, cast sugar and dehydrated gelatin, 32% fat bovine milk cream with intravenous lipid solution and technical alcohol in different amounts. We tested all these phantoms as well as ex vivo pig liver and human normal, fatty and cirrhotic liver by measuring the elasticity, shear wave speed, ultrasound attenuation, CT-scan density, MRI signal intensity and fracture force. We assessed the results of the testing performed, as well as the optical appearance on ultrasound, CT and MRI, in order to find the best recipe for gelatin-based phantoms for image-guided procedure training. Results: After the assessment of all phantom recipes, we selected as the best recipe for transparent phantoms one with 14 g of gelatin/100 mL water and for opaque phantom, the recipes with 25% cream. Conclusions: These liver gelatin-based phantom recipes are an inexpensive, reproducible and accessible alternative for training in image-guided and diagnostic procedures and will meet most requirements for valuable training.

PurposeLearning how to perform percutaneous transhepatic bile duct drainage (PTCD) is challenging for interventional radiology (IR) trainees. Therefore, simulators are crucial for IR training and are being increasingly demanded in the evolving healthcare environment of value-based care. To facilitate interventional training, we tried to evaluate our newly developed liver phantom for further use in IR training. MethodsWe developed a liver phantom with a flexible hollow biliary tree, hydrogel-based liver parenchyma, plastic ribs, and silicone skin. The phantom was evaluated by 20 radiology residents from two hospitals. After an introduction, all participants tried to obtain biliary access by fluoroscopic guidance within 25 min. Puncture time, fluoroscopy time, and kerma area product were measured. After 7 days, the participants repeated the procedure on an altered and more difficult model. Additionally, a survey was handed out to every participant (20 residents, 5 experts, and 5 IR fellows) to evaluate the phantom in terms of accuracy and haptic feedback, as well as general questions regarding simulation. ResultsThe residents performed significantly faster and were more self-confident on Day 7 than on Day 1, significantly decreasing puncture time, fluoroscopy time, and kerma area product (p ≤ 0.0001). The participants were very satisfied with their simulation experience and would trust themselves more in real-life scenarios. ConclusionWe were able to develop a phantom with high anatomical accuracy for fluoroscopy and ultrasound-guided interventions. The phantom successfully helped residents learn and improve their PTCD performance.

Purpose Hepatocellular carcinoma (HCC) is one of the most common types of liver cancer that could potentially be surrounded by healthy arteries or veins that a surgeon would have to avoid during treatment. A realistic 3D liver model is an unmet need for HCC preoperative planning. Methods This paper presents a method to create a soft phantom model of the human liver with the help of a 3D-printed mold, silicone, ballistic gel, and a blender. Results For silicone, the elastic modulus of seven different ratios of base silicone and silicone hardener are tested; while for ballistic gel, a model using 20% gelatin and 10% gelatin is created for the tumor and the rest of the liver, respectively. It is found that the silicone modulus of elasticity matches with the real liver modulus of elasticity. It is also found that the 10% gelatin part of the ballistic gel model is an excellent emulation of a healthy human liver. Conclusion The 3D flexible liver phantom made from a 10% gelatin-to-water mixture demonstrates decent fidelity to real liver tissue in terms of texture and elasticity. It holds significant potential for improving medical training, preoperative planning, and surgical research. We believe that continued development and validation of such models could further enhance their utility and impact in the field of hepatobiliary treatment planning and education.

Cranio-caudal respiratory motion and liver activity cause a variety of complex myocardial perfusion (MP) artifacts, especially in the inferior myocardial wall, that may also mask cardiac defects. To assess and characterise such artifacts, an anthropomorphic thorax with moving thoracic phantoms can be utilised in SPECT MP imaging. In this study, a liver phantom was developed and anatomically added into an anthropomorphic phantom that also encloses an ECG beating cardiac phantom and breathing lungs’ phantom. A cranio-caudal respiratory motion was also developed for the liver phantom and it was synchronised with the corresponding ones of the other thoracic phantoms. This continuous motion was further divided into isochronous dynamic respiratory phases, from end-exhalation to end-inspiration, to perform SPECT acquisitions in different respiratory phases. The new motions’ parameters and settings were measured by mechanical means and also validated in a clinical environment by acquiring CT images and by using two imaging software packages. To demonstrate the new imaging capabilities of the phantom assembly, SPECT/CT MP acquisitions were performed and compared to previous phantom and patients studies. All thoracic phantoms can precisely perform physiological motions within the anthropomorphic thorax. The new capabilities of the phantom assembly allow to perform SPECT/CT MP acquisitions for different cardiac-liver activity ratios and cardiac-liver proximities in supine and, for first time, in prone position. Thus, MP artifacts can be characterised and motion correction can be performed due to these new capabilities. The impact of artifacts and motion correction on defect detection can be also investigated.

Purpose The purpose of this study is to evaluate the impact of two methods of reporting planned dose distributions on the Gamma analysis pass rates for comparison with measured 2D film dose and simulated delivered 3D dose for proton pencil beam scanning treatment of the Imaging and Radiation Oncology Core (IROC) proton lung and liver mobile phantoms. Methods and materials Four-dimensional (4D) computed-tomography (CT) image sets were acquired for IROC proton lung and liver mobile phantoms, which include dosimetry inserts that contains targets, thermoluminescent dosimeters and EBT2 films for plan dose verification. 4DCT measured fixed motion magnitudes were 1.3 and 1.0 cm for the lung and liver phantoms, respectively. To study the effects of motion magnitude on the Gamma analysis pass rate, three motion magnitudes for each phantom were simulated by creating virtual 4DCT image sets with motion magnitudes scaled from the scanned phantom motion by 50, 100, and 200%. The internal target volumes were contoured on the maximum intensity projection CTs of the 4DCTs for the lung phantom and on the minimum intensity projection CTs of the 4DCTs for the liver phantom. Treatment plans were optimized on the average intensity projection (AVE) CTs of the 4DCTs using the RayStation treatment planning system. Plan doses were calculated on the AVE CTs, which was defined as the planned AVE dose (method one). Plan doses were also calculated on all 10 phase CTs of the 4DCTs and were registered using target alignment to and equal-weight-summed on the 50% phase (T50) CT, which was defined as the planned 4D dose (method two). The planned AVE doses and 4D doses for phantom treatment were reported to IROC, and the 2D-2D Gamma analysis pass rates for measured film dose relative to the planned AVE and 4D doses were compared. To evaluate motion interplay effects, simulated delivered doses were calculated for each plan by sorting spots into corresponding respiratory phases using spot delivery time recorded in the log files by the beam delivery system to calculate each phase dose and accumulate dose to the T50 CTs. Ten random beam starting phases were used for each beam to obtain the range of the simulated delivered dose distributions. 3D-3D Gamma analyses were performed to compare the planned 4D/AVE doses with simulated delivered doses. Results The planned 4D dose matched better with the measured 2D film dose and simulated delivered 3D dose than the planned AVE dose. Using planned 4D dose as institution reported planned dose to IROC improved IROC film dose 2D-2D Gamma analysis pass rate from 92 to 96% on average for three films for the lung phantom (7% 5 mm), and from 92 to 94% in the sagittal plane for the liver phantom (7% 4 mm), respectively, compared with using the planned AVE dose. The 3D-3D Gamma analysis (3% 3 mm) pass rate showed that the simulated delivered doses for lung and liver phantoms using 10 random beam starting phases for each delivered beam matched the planned 4D dose significantly better than the planned AVE dose for phantom motions larger than 1 cm ( p ≤  0.04). Conclusions It is recommended to use the planned 4D dose as the institution reported planned dose to IROC to compare with the measured film dose for proton mobile phantoms to improve film Gamma analysis pass rate in the IROC credentialing process.

Background Accurate pharmacokinetic modelling in PET necessitates measurements of an input function, which ideally is acquired non-invasively from image data. For hepatic pharmacokinetic modelling two input functions need to be considered, to account for the blood supply from the hepatic artery and portal vein. Image-derived measurements at the portal vein are challenging due to its small size and image artifacts caused by respiratory motion. In this work we seek to demonstrate, using phantom experiments, how a dedicated PET/MR protocol can tackle these challenges and potentially provide input function measurements of the portal vein in a clinical setup. Methods A custom 3D printed PET/MR phantom was constructed to mimic the liver and portal vein. PET/MR acquisitions were made with emulated respiratory motion. The PET/MR imaging protocol consisted of high-resolution anatomical MR imaging of the portal vein, followed by a PET acquisition in parallel to a dedicated motion-tracking MR sequence. Motion tracking and deformation information were extracted from PET data and subsequently used in PET reconstruction to produce dynamic series of motion-free PET images. Anatomical MR images were used post PET reconstruction for partial volume correction of the input function measurements. Results Reconstruction of dynamic PET data with motion-compensation provided nearly motion-free series of PET frame data, suitable for image derived input function measurements of the portal vein. After partial volume correction, the individual input function measurements were within a 16.1% error range from the true activity in the portal vein compartment at the time of PET acquisition. Conclusion The proposed protocol demonstrates clinically feasible PET/MR imaging of the liver for pharmacokinetic studies with accurate quantification of the portal vein input function, including correction for respiratory motion and partial volume effects.

Open-ended coaxial probes can be used as tissue characterization devices. However, the technique suffers from a high error rate. To improve this technology, there is a need to decrease the measurement error which is reported to be more than 30% for an in vivo measurement setting. This work investigates the machine learning (ML) algorithms’ ability to decrease the measurement error of open-ended coaxial probe techniques to enable tissue characterization devices. To explore the potential of this technique as a tissue characterization device, performances of multiclass ML algorithms on collected in vivo rat hepatic tissue and phantom dielectric property data were evaluated. Phantoms were used for investigating the potential of proliferating the data set due to difficulty of in vivo data collection from tissues. The dielectric property measurements were collected from 16 rats with hepatic anomalies, 8 rats with healthy hepatic tissues, and in house phantoms. Three ML algorithms, k-nearest neighbors (kNN), logistic regression (LR), and random forests (RF) were used to classify the collected data. The best performance for the classification of hepatic tissues was obtained with 76% accuracy using the LR algorithm. The LR algorithm performed classification with over 98% accuracy within the phantom data and the model generalized to in vivo dielectric property data with 48% accuracy. These findings indicate first, linear models, such as logistic regression, perform better on dielectric property data sets. Second, ML models fitted to the data collected from phantom materials can partly generalize to in vivo dielectric property data due to the discrepancy between dielectric property variability.

Over recent decades, stereotactic body radiotherapy has garnered increasing popularity. Unfortunately, conventional preclinical 2D in vitro models are often insufficient for studying radiotherapy effects. Therefore, in this study, we developed a novel anthropomorphic in vitro liver phantom, which simulates the relevant hepatocellular carcinoma (HCC) tumor microenvironment and spatial organization. The liver phantom was 3D printed, filled with tissue-mimicking agarose mixture, and designed to fit ten microfluidic chips (MCs), in which HepG2 cells were seeded. Airtight MCs induced hypoxic conditions, as verified by Hif1α staining. Irradiation was conducted with 20 Gy in one fraction using a CyberKnife, in either a 2D setup, or by irradiating MCs arranged in the 3D-printed liver model using an individually calculated treatment plan. Post-irradiation cellular damage was determined via γH2AX staining. Here, we demonstrate a new physiologically relevant approach to model HCC pathology following radiotherapy. Comparing γH2AX staining in normoxic conditions to cells grown in MCs (hypoxic conditions) revealed a reduction in cellular damage of 30.24% (p = 0.0001) in the hypoxic environment. Moreover, we compared the scattering effect of radiation on a conventional 2D in vitro model to our new 3D anthropomorphic liver phantom and observed a significant γH2AX intensity reduction of 9.6% (p = 0.0294) in HepG2 cells irradiated in the phantom. Our approach of utilizing a liver phantom takes into account the hypoxic tumor microenvironment and 3D scattering effects of tissue irradiation, thereby modeling both physical and biological parameters of HCC tumors. The use of tissue phantoms lays the groundwork for future examination of other hypoxic tumors and offers a more comprehensive approach for screening and analysis of novel cancer therapeutics.

This paper presents a projection-based augmented-reality system (MARVIS) that supports the visualization of internal structures on the surface of a liver phantom. MARVIS is endowed with three key features: tracking of spatial relationship between the phantom and the operator’s head in real time, monoscopic projection of internal liver structures onto the phantom surface for 3D perception without additional head-mounted devices, and phantom internal electronic circuit to assess the accuracy of a syringe guidance system. An initial validation was carried out by 25 medical students (12 males and 13 females; mean age, 23.12 years; SD, 1.27 years) and 3 male surgeons (mean age, 43.66 years; SD, 7.57 years). The validation results show that the ratio of failed syringe insertions was reduced from 50% to 30% by adopting the MARVIS projection. The proposed system suitably enhances a surgeon’s spatial perception of a phantom internal structure.

Image-guided liver surgery aims to enhance the precision of resection and ablation by providing fast localisation of tumours and adjacent complex vasculature to improve oncologic outcome. This Letter presents a novel end-to-end solution for fast stereo reconstruction and motion estimation that demonstrates high accuracy with phantom and clinical data. The authors’ computationally efficient coarse-to-fine (CTF) stereo approach facilitates liver imaging by accounting for low texture regions, enabling precise three-dimensional (3D) boundary recovery through the use of adaptive windows and utilising a robust 3D motion estimator to reject spurious data. To the best of their knowledge, theirs is the only adaptive CTF matching approach to reconstruction and motion estimation that registers time series of reconstructions to a single key frame for registration to a volumetric computed tomography scan. The system is evaluated empirically in controlled laboratory experiments with a liver phantom and motorised stages for precise quantitative evaluation. Additional evaluation is provided through testing with patient data during liver resection.