Metal Artifact Reduction Techniques Research Articles

Photon-counting CT imaging of a patient with coiled and untreated intracranial saccular aneurysms.

We describe a novel application of photon-counting detector CT (PCD-CT) in neurovascular imaging by harnessing the improved spatial resolution, attenuation of electronic noise, and reduction of metal artifacts. The presented case offers the unique challenge of high-quality imaging for the assessment of treated and untreated intracranial saccular aneurysms, in the setting of metal artifacts from embolization coils. Our goal was to explore optimized reconstruction parameters for ultra-high-resolution imaging (UHR) using a dedicated, sharp neurovascular kernel (Hv72) and the highest strength of quantum iterative reconstruction (QIR-4) for detailed characterization of the vasculature. Virtual monoenergetic images (VMIs) and iterative metal artifact reduction (IMAR) were employed to investigate metal artifact reduction techniques. PCD-CT has the promising potential to enhance patient care in the follow-up of patients with treated aneurysms requiring more complex imaging parameters and image post-processing due to intracranial artifacts.

The Clinical Value of the MAR+ Metal Artifact Reduction Algorithm for Postoperative Assessment of Lumbar Internal Fixation.

With the widespread use of lumbar pedicle screws for internal fixation, the morphology of the screws and the surrounding tissues should be evaluated. The metal artifact reduction (MAR) technique can reduce the artifacts caused by pedicle screws, improve the quality of computed tomography (CT) images after pedicle fixation, and provide more imaging information to the clinic. To explore whether the MAR+ method, a projection-based algorithm for correcting metal artifacts through multiple iterative operations, can reduce metal artifacts and have an impact on the structure of the surrounding metal. A total of 57 patients who underwent lumbar spine CT examination after lumbar internal fixation from January to December 2023 in our hospital were retrospectively enrolled. The CT images were reconstructed using MAR+ and non-MAR+ techniques and were subdivided into MAR+ and non-MAR+ groups. The CT number (in Hounsfield units) and the SD noise values of the spinal canal, vertebral body, psoas major muscle, and adjacent fat were measured in the 2 groups of CT images, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The subjective score was evaluated by two diagnostic radiologists using a double-blind method for image quality evaluation of the MAR+ group and the non-MAR+ group, and the image quality was classified on a 5-point scale. The rank-sum test was utilized to compare the subjective and objective scores of the 2 groups. The SD values of the spinal canal (Z=-4.12, P<0.01), vertebral body (Z=-3.81, P<0.01), and psoas major muscle (Z=-3.87, P<0.01) in the MAR+ group were significantly lower than those in the non-MAR+ group (P<0.05). However, the SD values of the adjacent fat (Z=-2.03, P=0.42) in the MAR+ group, although smaller than those in the non-MAR+ group, were not statistically significant. The CNR values of vertebral canal (Z=-2.67, P=0.008) and fat (Z=-2.60, P=0.009) were higher in the MAR+ group than in the non-MAR+ group, whereas the CNR values of the vertebral body (Z=-6.74, P<0.01) in the MAR+ group were smaller than those in the non-MAR+ group, and the difference of all of them was statistically significant (P<0.05). Furthermore, for both CT and SNR values, the MAR group's values were all less than those of the non-MAR group and were statistically significant (P<0.05). The subjective scores of the measurement points were all higher in the MAR+ group than in the non-MAR+ group. The MAR+ technique has a noise reduction effect on different tissues and artifacts are significantly reduced. Although the artifacts caused by metal screws were not completely eliminated, the MAR+ technique was able to reduce the interference of artifacts in the diagnosis of CT images, thus improving their diagnostic quality.

A comparative study of the role of carbon fibre reinforced polyetheretherketone and titanium intramedullary nails in patients with metastatic bone disease.

Carbon fibre reinforced polyetheretherketone (CFR-PEEK) implants have gained interest because of reported biomechanical advantages and radio-lucent properties. The aim of this study was to evaluate the role of CFR-PEEK nails in patients with metastatic bone disease (MBD). We performed a retrospective cohort study evaluating patients with MBD undergoing intramedullary (IM) nailing for prophylaxis or fixation of pathological fractures using CFR- PEEK or titanium implants. Patient survival, implant failure rates, ability to visualise disease progression on post- operative CT/MRI, and post-operative radiotherapy dose were reported. Fifty patients underwent 56 IM nails (26 CFR-PEEK and 30 titanium). Median survival was 8 months for the entire cohort, 6 months for patients with CFR- PEEK nails and 8 months for those with conventional nails (p=0.691). No implant failures were recorded in either group. There was no correlation between implant type and post-operative radiotherapy dose given (χ 2 = 0.139, p=0.710). Artefact on MRI was less evident with CFR-PEEK nails when hybrid imaging and metal artefact reduction techniques were used. The advantages of CFR-PEEK nails might not be realised in clinical practice for most patients with MBD requiring IM nailing except for in those likely to require prolonged disease surveillance.

Stereotactic Body Radiation Therapy for Clinically Localized Prostate Cancer in Men With Hip Prostheses: A Cautionary Note.

Stereotactic body radiation therapy (SBRT) has been established as a safe and effective treatment for prostate cancer. SBRT requires high accuracy to reduce treatment margins. Metal hip prostheses create artifacts that distort pelvic imaging and potentially decrease the accuracy of target/organ at risk (OAR) identification and radiation dose calculations. Data on the safety and efficacy of SBRT after hip replacement is limited. This single-institution study sought to evaluate the safety and local control following SBRT for prostate cancer in men with hip replacements. 23 patients treated with localized prostate cancer and a history of pre-treatment hip replacement, treated with SBRT from 2007 to 2017 at MedStar Georgetown University Hospital were included in this retrospective analysis. Treatment was administered with the CyberKnife® (Accuray Incorporated, Sunnyvale, CA) at doses of 35 Gy or 36.25 Gy in 5 fractions. The targets and OARs were identified and contoured by a single experienced Radiation Oncologist (SPC).The adequacy of the CT and T2W MRI images for treatment planning was assessed with a three-point scale (good, adequate, or suboptimal).During treatment planning, care was taken to avoid treatment beams that directly traversed the hip prosthesis. Toxicities were recorded and scored using the Common Terminology Criteria for Adverse Events version 4.0 (CTCAE v.4.0). Local recurrence was confirmed by magnetic resonance imaging and/or prostate biopsy. The median follow-up was seven years. The patients were elderly (median age = 71 years) with a high rate of comorbidities (Charlson Comorbidity Index > 2 in 25%). Four patients had bilateral hip replacements. The majority of patients were low to intermediate risk per the D'Amico classification. Around 13% received upfront ADT. In total, 13 patients were treated with 35 Gy, and 10 were treated with 36.25 Gy.The rates of late > Grade 3 GU toxicity and> Grade 2 GI toxicity were 8.6% and 4.3%, respectively. There were no Grade 4 or 5 toxicities.Six patients (26%) developed a local recurrence at a median time of 7.5 years. Of these six patients, four had unilateral hip replacements and two had bilateral.Three underwent salvage cryotherapy and three received salvage ADT. In the general population, high-grade toxicities and local recurrences are uncommon following prostate SBRT.However, in this cohort of patients with prior hip replacements, prostate SBRT had higher than expected rates of late toxicity and local recurrence. In the opinion of the authors, such patients should be counseled regarding an elevated risk of late toxicity and local recurrence with prostate SBRT. With its ultrasound guidance, brachytherapy would have the advantage of circumventing the need for MRI/CT-based imaging and thus may represent a preferable radiation alternative in this patient population. If these patients are treated with SBRT, they should be monitored closely for local recurrence so early salvage can be performed. We hopethat recent advances in metal artifact reduction techniques and dose-calculation algorithms will improve future outcomes.

An image-based metal artifact reduction technique utilizing forward projection in computed tomography.

The projection data generated via the forward projection of a computed tomography (CT) image (FP-data) have useful potentials in cases where only image data are available. However, there is a question of whether the FP-data generated from an image severely corrupted by metal artifacts can be used for the metal artifact reduction (MAR). The aim of this study was to investigate the feasibility of a MAR technique using FP-data by comparing its performance with that of a conventional robust MAR using projection data normalization (NMARconv). The NMARconv was modified to make use of FP-data (FPNMAR). A graphics processing unit was used to reduce the time required to generate FP-data and subsequent processes. The performances of FPNMAR and NMARconv were quantitatively compared using a normalized artifact index (AIn) for two cases each of hip prosthesis and dental fillings. Several clinical CT images with metal artifacts were processed by FPNMAR. The AIn values of FPNMAR and NMARconv were not significantly different from each other, showing almost the same performance between these two techniques. For all the clinical cases tested, FPNMAR significantly reduced the metal artifacts; thereby, the images of the soft tissues and bones obscured by the artifacts were notably recovered. The computation time per image was ~ 56ms. FPNMAR, which can be applied to CT images without accessing the projection data, exhibited almost the same performance as that of NMARconv, while consuming significantly shorter processing time. This capability testifies the potential of FPNMAR for wider use in clinical settings.

Impact of different metal artifact reduction techniques in photon-counting computed tomography head and neck scans in patients with dental hardware

ObjectivesMetal artifacts remain a challenge in computed tomography. We investigated the potential of photon-counting computed tomography (PCD-CT) for metal artifact reduction using an iterative metal artifact reduction (iMAR) algorithm alone and in combination with high keV monoenergetic images (140 keV) in patients with dental hardware.Material and methodsConsecutive patients with dental implants were prospectively included in this study and received PCD-CT imaging of the craniofacial area. Four series were reconstructed (standard [PCD-CTstd], monoenergetic at 140 keV [PCD-CT140keV], iMAR corrected [PCD-CTiMAR], combination of iMAR and 140 keV monoenergetic [PCD-CTiMAR+140keV]). All reconstructions were assessed qualitatively by four radiologists (independent and blinded reading on a 5-point Likert scale [5 = excellent; no artifact]) regarding overall image quality, artifact severity, and delineation of adjacent and distant anatomy. To assess signal homogeneity and evaluate the magnitude of artifact reduction, we performed quantitative measures of coefficient of variation (CV) and a region of interest (ROI)–based relative change in artifact reduction [PCD-CT/PCD-CTstd].ResultsWe enrolled 48 patients (mean age 66.5 ± 11.2 years, 50% (n = 24) males; mean BMI 25.2 ± 4.7 kg/m2; mean CTDIvol 6.2 ± 6 mGy). We found improved overall image quality, reduced artifacts and superior delineation of both adjacent and distant anatomy for the iMAR vs. non-iMAR reconstructions (all p < 0.001). No significant effect of the different artifact reduction approaches on CV was observed (p = 0.42). The ROI-based analysis indicated the most effective artifact reduction for the iMAR reconstructions, which was significantly higher compared to PCD-CT140keV (p < 0.001).ConclusionPCD-CT offers highly effective approaches for metal artifact reduction with the potential to overcome current diagnostic challenges in patients with dental implants.Clinical relevance statementMetallic artifacts pose a significant challenge in CT imaging, potentially leading to missed findings. Our study shows that PCD-CT with iMAR post-processing reduces artifacts, improves image quality, and can possibly reveal pathologies previously obscured by artifacts, without additional dose application.Key Points• Photon-counting detector CT (PCD-CT) offers highly effective approaches for metal artifact reduction in patients with dental fillings/implants.• Iterative metal artifact reduction (iMAR) is superior to high keV monoenergetic reconstructions at 140 keV for artifact reduction and provides higher image quality.• Signal homogeneity of the reconstructed images is not affected by the different artifact reduction techniques.

Quality improvement of images with metal artifact reduction using a noise recovery technique in computed tomography.

In metal artifact reduction (MAR) in computed tomography (CT) based on projection data inpainting, X-ray photon noise has not been considered in the inpainting process. This study aims to assess the effectiveness of a MAR technique incorporating noise recovery in such projection data regions, compared with existing MAR techniques based on projection data normalization (NMAR), including one with frequency splitting (FSNMAR). Phantoms simulating hip prostheses and dental fillings were scanned using a 64-row multi slice CT scanner. The projection data was processed by NMAR and NMAR with noise recovery (NRNMAR); the processed data was sent back to the CT system for reconstruction. For the phantoms and clinical cases with hip prostheses and dental fillings, images were reconstructed without MAR, and with NMAR, NRNMAR, and FSNMAR (incorporated in the CT system). To validate the efficacy of noise recovery, noise power spectra (NPSs) were measured from the images of the hip prosthesis phantom with and without metals. The artifact index (AI) was compared between NRNMAR and FSNMAR. The resultant NPSs of NRNMAR were very similar to those of phantom images with no metals, endorsing the efficacy of noise recovery. The NMAR images had unnatural noise textures and FSNMAR caused additional streaks. NRNMAR exhibited some significant improvements in these respects: It reduced the AI by as much as 66.2-88.6% compared to FSNMAR, except for the case of a unilateral prosthesis. In conclusion, NRNMAR, which simply adds white noise to the projection data, would be effective in improving the quality of CT images with metal artifacts reduction.

SemiMAR: Semi-Supervised Learning for CT Metal Artifact Reduction.

Metal artifacts lead to CT imaging quality degradation. With the success of deep learning (DL) in medical imaging, a number of DL-based supervised methods have been developed for metal artifact reduction (MAR). Nonetheless, fully-supervised MAR methods based on simulated data do not perform well on clinical data due to the domain gap. Although this problem can be avoided in an unsupervised way to a certain degree, severe artifacts cannot be well suppressed in clinical practice. Recently, semi-supervised metal artifact reduction (MAR) methods have gained wide attention due to their ability in narrowing the domain gap and improving MAR performance in clinical data. However, these methods typically require large model sizes, posing challenges for optimization. To address this issue, we propose a novel semi-supervised MAR framework. In our framework, only the artifact-free parts are learned, and the artifacts are inferred by subtracting these clean parts from the metal-corrupted CT images. Our approach leverages a single generator to execute all complex transformations, thereby reducing the model's scale and preventing overlap between clean part and artifacts. To recover more tissue details, we distill the knowledge from the advanced dual-domain MAR network into our model in both image domain and latent feature space. The latent space constraint is achieved via contrastive learning. We also evaluate the impact of different generator architectures by investigating several mainstream deep learning-based MAR backbones. Our experiments demonstrate that the proposed method competes favorably with several state-of-the-art semi-supervised MAR techniques in both qualitative and quantitative aspects.

PDS-MAR: a fine-grained projection-domain segmentation-based metal artifact reduction method for intraoperative CBCT images with guidewires

Objective. Since the invention of modern Computed Tomography (CT) systems, metal artifacts have been a persistent problem. Due to increased scattering, amplified noise, and limited-angle projection data collection, it is more difficult to suppress metal artifacts in cone-beam CT, limiting its use in human- and robot-assisted spine surgeries where metallic guidewires and screws are commonly used. Approach. To solve this problem, we present a fine-grained projection-domain segmentation-based metal artifact reduction (MAR) method termed PDS-MAR, in which metal traces are augmented and segmented in the projection domain before being inpainted using triangular interpolation. In addition, a metal reconstruction phase is proposed to restore metal areas in the image domain. Main results. The proposed method is tested on both digital phantom data and real scanned cone-beam computed tomography (CBCT) data. It achieves much-improved quantitative results in both metal segmentation and artifact reduction in our phantom study. The results on real scanned data also show the superiority of this method. Significance. The concept of projection-domain metal segmentation would advance MAR techniques in CBCT and has the potential to push forward the use of intraoperative CBCT in human-handed and robotic-assisted minimal invasive spine surgeries.

MRI Advancements in Musculoskeletal Clinical and Research Practice.

Over the past decades, MRI has become increasingly important for diagnosing and longitudinally monitoring musculoskeletal disorders, with ongoing hardware and software improvements aiming to optimize image quality and speed. However, surging demand for musculoskeletal MRI and increased interest to provide more personalized care will necessitate a stronger emphasis on efficiency and specificity. Ongoing hardware developments include more powerful gradients, improvements in wide-bore magnet designs to maintain field homogeneity, and high-channel phased-array coils. There is also interest in low-field-strength magnets with inherently lower magnetic footprints and operational costs to accommodate global demand in middle- and low-income countries. Previous approaches to decrease acquisition times by means of conventional acceleration techniques (eg, parallel imaging or compressed sensing) are now largely overshadowed by deep learning reconstruction algorithms. It is expected that greater emphasis will be placed on improving synthetic MRI and MR fingerprinting approaches to shorten overall acquisition times while also addressing the demand of personalized care by simultaneously capturing microstructural information to provide greater detail of disease severity. Authors also anticipate increased research emphasis on metal artifact reduction techniques, bone imaging, and MR neurography to meet clinical needs.

Comprehensive evaluation of artifact reduction and tissue recovery effects of metal artifact reduction technique based on full-reference metric

For the comprehensive evaluation of metal artifact reduction (MAR) technique, not only the removal of metal artifacts but also the evaluation of the area restored by MAR is required. We propose a method to comprehensively evaluate the effect by MAR in this study. We have conducted the computed tomography scan to acquire both the evaluation image and the reference image for the full-reference based evaluation. The evaluation image and reference image were reconstructed into 24 image sets according to the tube potentials, image reconstruction method, and use of the MAR technique. Images of two different positions were selected according to the distance from metal and material (bone, tissue) distribution, and bone and tissue were automatically segmented in both evaluation and reference images. The values of full width at half the maximum (FWHM) and centroid were extracted after Gaussian modeling of each segmented region. Then, we computed four evaluation metrics (FWHMNM: non-MAR to non-metal ratio of FWHM, FWHMM: MAR to non-metal ratio of FWHM, CENTNM: non-MAR to non-metal ratio of centroid, CENTM: MAR to non-metal ratio of centroid), and the MAR image and non-MAR image were compared. The overlap ratio automatically segmented from the evaluation image and reference image were position 1 (bone: 99.61%, tissue: 99.23%) with 80 kVp, position 1 (bone: 99.32%, tissue: 99.56%) with 120 kVp, position 2 (bone: 99.20%, tissue: 99.73%) with 80 kVp, and position 2 (bone: 99.23%, tissue: 99.67%) with 120 kVp. The FWHMNM showing the change of image pixel value by metal artifact was calculated as (bone: 1.32–1.46, tissue: 1.08–1.16) at 80 kVp and (bone: 1.19–1.27, tissue: 1.02–1.05) at 120 kVp. More metal artifacts occurred at 80 kVp tube potential. Regardless of the tube potential and image reconstruction method, the MAR showed an overall artifact reduction effect (1 < FWHMM < FWHMNM). However, distortion of pixel values occurred due to the MAR in regions where metal artifacts were high in proximity to metal (1 < FWHMNM < FWHMM). Overall, the average value of the medium was maintained (CENTM: 0.98–1.03) after MAR application, but there was a change of image value in region around the metal (CENTM: 0.97–1.11). In this study, we propose a new method to evaluate the effect of metal artifacts and MAR technique using full-reference based method. Metal artifacts, effect of MAR technique, and side-effect caused by MAR technique were quantitatively analyzed through proposed method. There are some limitations in applying it to clinical imaging since our method is a reference-based evaluation. However, our experimental results were important for understanding the effects of the MAR technique and its functional properties.

Is AI the way forward for reducing metal artifacts in CT? Development of a generic deep learning-based method and initial evaluation in patients with sacroiliac joint implants

PurposeTo develop a deep learning-based metal artifact reduction technique (dl-MAR) and quantitatively compare metal artifacts on dl-MAR-corrected CT-images, orthopedic metal artifact reduction (O-MAR)-corrected CT-images and uncorrected CT-images after sacroiliac (SI) joint fusion. Methodsdl-MAR was trained on CT-images with simulated metal artifacts. Pre-surgery CT-images and uncorrected, O-MAR-corrected and dl-MAR-corrected post-surgery CT-images of twenty-five patients undergoing SI joint fusion were retrospectively obtained. Image registration was applied to align pre-surgery with post-surgery CT-images within each patient, allowing placement of regions of interest (ROIs) on the same anatomical locations. Six ROIs were placed on the metal implant and the contralateral side in bone lateral of the SI joint, the gluteus medius muscle and the iliacus muscle. Metal artifacts were quantified as the difference in Hounsfield units (HU) between pre- and post-surgery CT-values within the ROIs on the uncorrected, O-MAR-corrected and dl-MAR-corrected images. Noise was quantified as standard deviation in HU within the ROIs. Metal artifacts and noise in the post-surgery CT-images were compared using linear multilevel regression models. ResultsMetal artifacts were significantly reduced by O-MAR and dl-MAR in bone (p < 0.001), contralateral bone (O-MAR: p = 0.009; dl-MAR: p < 0.001), gluteus medius (p < 0.001), contralateral gluteus medius (p < 0.001), iliacus (p < 0.001) and contralateral iliacus (O-MAR: p = 0.024; dl-MAR: p < 0.001) compared to uncorrected images. Images corrected with dl-MAR resulted in stronger artifact reduction than images corrected with O-MAR in contralateral bone (p < 0.001), gluteus medius (p = 0.006), contralateral gluteus medius (p < 0.001), iliacus (p = 0.017), and contralateral iliacus (p < 0.001). Noise was reduced by O-MAR in bone (p = 0.009) and gluteus medius (p < 0.001) while noise was reduced by dl-MAR in all ROIs (p < 0.001) in comparison to uncorrected images. Conclusiondl-MAR showed superior metal artifact reduction compared to O-MAR in CT-images with SI joint fusion implants.

Advances in Bone Joint Imaging-Metal Artifact Reduction.

Numerous types of metal implants have been introduced in orthopedic surgery and are used in everyday practice. To precisely evaluate the postoperative condition of arthroplasty or trauma surgery, periprosthetic infection, and the loosening of implants, it is important to reduce artifacts induced by metal implants. In this review, we focused on technical advances in metal artifact reduction using digital tomosynthesis, computed tomography, and magnetic resonance imaging. We discussed new developments in diagnostic imaging methods and the continuous introduction of novel technologies to reduce metal artifacts; however, these innovations have not yet completely removed metal artifacts. Different algorithms need to be selected depending on the size, shape, material and implanted body parts of an implant. Future advances in metal artifact reduction algorithms and techniques and the development of new sequences may enable further reductions in metal artifacts even on original images taken previously. Moreover, the combination of different imaging modalities may contribute to further reductions in metal artifacts. Clinicians must constantly update their knowledge and work closely with radiologists to select the best diagnostic imaging method for each metal implant.

The Impact of View- Angle Tilting and Slice Encoding for Metal Artifact Correction Methods on the Metal Artifact Reduction in Magnetic Resonance Imaging of the Knee Prosthesis

Purpose: At Magnetic Resonance Imaging (MRI), artifacts arising from metal implants are an obstacle to obtaining optimal images. This study aimed to evaluate the impact of View-Angle Tilting (VAT) and Slice Encoding for Metal Artifact Correction (SEMAC) techniques for the artifact reduction of patients during knee MRI with metal implants.&#x0D; Materials and Methods: The MR images without any intervention of the knee from 20 patients with knee prostheses were used. The VAT and SEMAC metal artifact reduction techniques were applied to all the MR images. Volume and mass of the metal prosthesis were quantified using the MATLAB program and compared with the real measurements using nonparametric Wilcoxon tests in SPSS software. The qualitative analysis was performed by two blinded observers regarding the score of artifact size, distortions, image quality, and visualization of bone marrow and soft tissues adjacent to metal implants. In addition, Cohen’s kappa values were used for inter-observer agreement.&#x0D; Results: The average volume of the platinum based on the conventional, VAT, and SEMAC methods was estimated at 14.22 ± 0.43, 14.05 ± 0.4, and 13.3 ± 0.45 cm3, respectively. The statistical analysis showed no significant difference (P &gt; 0.05) between the mean value of the platinum volume for the SEMAC method and the real measurement (13.6 ± 0.33 cm3). Furthermore, regarding the conventional, VAT, and SEMAC sequences, the mean mass of the platinum was obtained at 305.02 ± 9.22, 301.37 ± 8.58, and 285.28 ± 9.65 g, respectively, with the P-Value of 0.005, 0.009, and 0.268, compared to the real measurements (286.81±8.75 g). Notably, the blinded readers demonstrated that the SEMAC method was remarkably superior quality compared with VAT and conventional acquisitions (P-Value&lt; 0.05).&#x0D; Conclusion: The knee prosthesis metal artifact was reduced using the VAT and SEMAC techniques, in a way that, the reduction was significant by the SEMAC method. In addition, concerning the qualitative observer analysis, the application of the SEMAC technique provides improved visualization of tissue structures adjacent to metal implants.

Brachial Plexus Magnetic Resonance Neurography: Technical Challenges and Solutions.

Magnetic resonance neurography of the brachial plexus (BP) is challenging owing to its complex anatomy and technical obstacles around this anatomic region. Magnetic resonance techniques to improve image quality center around increasing nerve-to-background contrast ratio and mitigating imaging artifacts. General considerations include unilateral imaging of the BP at 3.0 T, appropriate selection and placement of surface coils, and optimization of pulse sequences. Technical considerations to improve nerve conspicuity include fat, vascular, and respiratory artifact suppression techniques; metal artifact reduction techniques; and 3-dimensional sequences. Specific optimization of these techniques for BP magnetic resonance neurography greatly improves image quality and diagnostic confidence to help guide nonoperative and operative management.

Intraoperative cone-beam CT with metal artifact reduction for assessment of the electrode position and the intracranial structures during deep brain stimulation procedure.

In deep brain stimulation (DBS) for Parkinson's disease (PD), the clinical outcome largely depends on the appropriate position of the electrode implanted in the targeted structure. In intraoperative cone-beam computed tomography (CT) performed for the evaluation of the electrode position, the metal artifact induced by the implanted electrode can prevent the precise localization of the electrode. Metal artifact reduction (MAR) techniques have been recently developed that can dramatically improve the visualization of objects by reducing metal artifacts after performing cone-beam CT. Hence, in this case series, we attempted to clarify the usefulness and accuracy of intraoperative cone-beam CT with MAR (intraCBCTwM) by comparing with both intraoperative cone-beam CT without MAR (intraCBCTwoM) and conventional postoperative CT (post-CT) for the assessment of the implanted electrode position and the intracranial structures during DBS procedures. Between November 2019 and December 2020, 10 patients with PD who underwent DBS at our institution were recruited, and the images of 9 patients (bilateral: n = 8, unilateral: n = 1) were analyzed. The artifact index (AI) in intraCBCTwM or intraCBCTwoM, and conventional post-CT were retrospectively assessed using the standard deviation of the region-of-interest around the implanted electrodes and background noise. Additionally, the Euclidean distances gap of electrode tip based on post-CT in each fusion image was compared between intraCBCTwM and intraCBCTwoM. The AI was significantly lower in intraCBCTwM than in intraCBCTwoM (P < 0.01). The mean Euclidean distance between the tip of the electrode in intraCBCTwM and in post-CT was significantly shorter compared to that in intraCBCTwoM (P < 0.05). The results reported here suggest that intraCBCTwM is a more useful and accurate method than intraCBCTwoM to assess the implanted electrode position and intracranial structures during DBS.

State-of-the-Art Imaging Techniques in Metastatic Spinal Cord Compression.

Simple SummaryMetastatic Spinal Cord Compression (MSCC) is a feared complication in oncology patients due to its potential for severe pain, permanent neurological disability and mechanical instability of the spine. This narrative review, conducted by keyword searches in PubMed and Google Scholar databases, aims to describe the important role of imaging in MSCC diagnosis and treatment. Diagnosis is typically achieved via Magnetic Resonance Imaging (MRI), although Computed Tomography (CT) Myelogram and conventional CT imaging can be performed in certain clinical situations. Metal artifact reduction techniques for MRI and CT are continually being researched to facilitate imaging in MSCC patients with spinal implants. Imaging also has an important role in pre-treatment planning, in-room image-guidance, and post-treatment follow-up for MSCC patients treated with stereotactic body radiotherapy. Recent advances in deep learning tools for image analysis can reduce the time to MSCC diagnosis, enabling earlier treatment for superior functional outcomes.Metastatic Spinal Cord Compression (MSCC) is a debilitating complication in oncology patients. This narrative review discusses the strengths and limitations of various imaging modalities in diagnosing MSCC, the role of imaging in stereotactic body radiotherapy (SBRT) for MSCC treatment, and recent advances in deep learning (DL) tools for MSCC diagnosis. PubMed and Google Scholar databases were searched using targeted keywords. Studies were reviewed in consensus among the co-authors for their suitability before inclusion. MRI is the gold standard of imaging to diagnose MSCC with reported sensitivity and specificity of 93% and 97% respectively. CT Myelogram appears to have comparable sensitivity and specificity to contrast-enhanced MRI. Conventional CT has a lower diagnostic accuracy than MRI in MSCC diagnosis, but is helpful in emergent situations with limited access to MRI. Metal artifact reduction techniques for MRI and CT are continually being researched for patients with spinal implants. Imaging is crucial for SBRT treatment planning and three-dimensional positional verification of the treatment isocentre prior to SBRT delivery. Structural and functional MRI may be helpful in post-treatment surveillance. DL tools may improve detection of vertebral metastasis and reduce time to MSCC diagnosis. This enables earlier institution of definitive therapy for better outcomes.

Impact of computed tomography metal artifact reduction protocol on periprosthetic tissue characterization after total hip arthroplasty:A cadaveric study.

Metal artifact reduction (MAR) has improved computed tomography (CT) imaging of total hip arthroplasty (THA) but the assessment of osteolysis and implant to bone contact relies on the accurate depiction of bone defects, cancellous bone, and cement. This study evaluates the impact of available single and dual-energy protocols on periprosthetic tissue characterization in a cadaveric phantom. Bilateral THA was performed on a fresh frozen cadaveric pelvis with simulated osteolytic cavities. CT acquisitions with projection-basedMAR and noise equivalence were performed using single energy 140 kVp, single energy 150 kVp with 0.6 mm tin filtration, and dual-energy at 100/150 kVp with 0.6 mm tin filtration, from which simulated energies were extracted. Image subtraction, segmentation, region of interest histograms, and line profiles were used to characterize tissue density and separation. Tissue densities were heavily dependent on the energy profile of the protocol. Cancellous bone ranged from 182to 45 HU and cement from 1012to 131 HU using 140 kVp compared to dual-energy with weighted high energy tube, respectively. Spectral separation between cancellous bone, osteolytic defect, and cement was reduced for all protocols compared with 140 kVp. Spectral overlap was most severe using dual-energy with heavily weighted high-energy tubes. Dual-energy algorithms reduced trabecular contrast within the cancellous bone and cortical edge response. Althoughthe dual-energy acquisition has been proposed as an additive to projection-based MAR techniques in THA, reduced density and contrast in clinically relevant periprosthetic tissue compared to 140 kVp single energy may limit its use in characterizing periprosthetic tissues.

Practical Aspects of novel MRI Techniques in Neuroradiology: Part 1–3D Acquisitions, Dixon Techniques and Artefact Reduction

Recently introduced MRI techniques offer improved image quality and facilitate examinations of patients even when artefacts are expected. They pave the way for novel diagnostic imaging strategies in neuroradiology. These methods include improved 3D imaging, movement and metal artefact reduction techniques as well as Dixon techniques. Narrative review with an educational focus based on current literature research and practical experiences of different professions involved (physicians, MRI technologists/radiographers, physics/biomedical engineering). Different hardware manufacturers are considered. 3D FLAIR is an example of a versatile 3D Turbo Spin Echo sequence with broad applicability in routine brain protocols. It facilitates detection of smaller lesions and more precise measurements for follow-up imaging. It also offers high sensitivity for extracerebral lesions. 3D techniques are increasingly adopted for imaging arterial vessel walls, cerebrospinal fluid spaces and peripheral nerves. Improved hybrid-radial acquisitions are available for movement artefact reduction in a broad application spectrum. Novel susceptibility artefact reduction techniques for targeted application supplement previously established metal artefact reduction sequences. Most of these techniques can be further adapted to achieve the desired diagnostic performances. Dixon techniques allow for homogeneous fat suppression in transition areas and calculation of different image contrasts based on a single acquisition. · 3D FLAIR can replace 2 D FLAIR for most brain imaging applications and can be a cornerstone of more precise and more widely applicable protocols.. · Further 3D TSE sequences are increasingly replacing 2D TSE sequences for specific applications.. · Improvement of artefact reduction techniques increase the potential for effective diagnostic MRI exams despite movement or near metal implants.. · Dixon techniques facilitate homogeneous fat suppression and simultaneous acquisition of multiple contrasts.. · Sundermann B, Billebaut B, Bauer J et al. Practical Aspects of novel MRI Techniques in Neuroradiology: Part 1-3D Acquisitions, Dixon Techniques and Artefact Reduction. Fortschr Röntgenstr 2022; 194: 1100 - 1108.

DICDNet: Deep Interpretable Convolutional Dictionary Network for Metal Artifact Reduction in CT Images.

Computed tomography (CT) images are often impaired by unfavorable artifacts caused by metallic implants within patients, which would adversely affect the subsequent clinical diagnosis and treatment. Although the existing deep-learning-based approaches have achieved promising success on metal artifact reduction (MAR) for CT images, most of them treated the task as a general image restoration problem and utilized off-the-shelf network modules for image quality enhancement. Hence, such frameworks always suffer from lack of sufficient model interpretability for the specific task. Besides, the existing MAR techniques largely neglect the intrinsic prior knowledge underlying metal-corrupted CT images which is beneficial for the MAR performance improvement. In this paper, we specifically propose a deep interpretable convolutional dictionary network (DICDNet) for the MAR task. Particularly, we first explore that the metal artifacts always present non-local streaking and star-shape patterns in CT images. Based on such observations, a convolutional dictionary model is deployed to encode the metal artifacts. To solve the model, we propose a novel optimization algorithm based on the proximal gradient technique. With only simple operators, the iterative steps of the proposed algorithm can be easily unfolded into corresponding network modules with specific physical meanings. Comprehensive experiments on synthesized and clinical datasets substantiate the effectiveness of the proposed DICDNet as well as its superior interpretability, compared to current state-of-the-art MAR methods. Code is available at https://github.com/hongwang01/DICDNet.