Routine Clinical Imaging Research Articles

Evaluation of MR anatomically-guided PET reconstruction using a convolutional neural network in PSMA patients.

&#xD;Recently, approaches have utilized the superior anatomical information provided by magnetic resonance imaging (MRI) to guide the reconstruction of positron emission tomography (PET). One of those approaches is the Bowsher's prior, which has been accelerated lately with a convolutional neural network (CNN) to reconstruct MR-guided PET in the imaging domain in routine clinical imaging. Two differently trained Bowsher-CNN methods (B-CNN0 and B-CNN) have been trained and tested on brain PET/MR images on non-PSMA tracers, but so far, have not been evaluated in other anatomical regions yet. &#xD;Methods: &#xD;A NEMA phantom with five of its six spheres filled with the same, calibrated concentration of 18F-DCFPyL-PSMA, and thirty-two patients (mean age 64 ± 7 years) with biopsy-confirmed PCa were used in this study. Reconstruction with either of the two available Bowsher-CNN methods were performed on the conventional MR-based attenuation correction (MRAC) and T1-MR images in the imaging domain. Detectable volume of the spheres and tumors, relative contrast recovery (CR), and background variation (BV) were measured for the MRAC and the Bowsher-CNN images, and qualitative assessment was conducted by ranking the image sharpness and quality by two experienced readers.&#xD;Results: &#xD;For the phantom study, the B-CNN produced 12.7% better CR compared to conventional reconstruction. The small sphere volume (<1.8mL) detectability improved from MRAC to B-CNN by nearly 13%, while measured activity was higher than the ground-truth by 8%. The signal-to-noise ratio (SNR), CR, and BV were significantly improved (p<0.05) in B-CNN images of the tumor. The qualitative analysis determined that tumor sharpness was excellent in 76% of the PET images reconstructed with the B-CNN method, compared to conventional reconstruction. &#xD;Conclusions: &#xD;Applying the MR-guided B-CNN in clinical prostate PET/MR imaging improves some quantitative, as well as qualitative imaging measures. The measured improvements in the phantom are also clearly translated into clinical application.

Comprehensive voxel-wise, tract-based, and network lesion mapping reveals unique architectures of right and left visuospatial neglect

Visuospatial neglect is a common, post-stroke cognitive impairment which is widely considered to be a disconnection syndrome. However, the patterns of disconnectivity associated with visuospatial neglect remain unclear. Here, we had 480 acute stroke survivors [age = 72.8 (SD = 13.3), 44.3% female, 7.5 days post-stroke (SD = 11.3)] undertake routine clinical imaging and standardised visuospatial neglect testing. The data were used to conduct voxel-wise, tract-level, and network-level lesion-mapping analyses aimed at localising the neural correlates of left and right egocentric (body-centred) and allocentric (object-centred) visuospatial neglect. Only minimal anatomical homogeneity was present between the correlates of right and left egocentric neglect across all analysis types. This finding challenges previous work suggesting that right and left visuospatial neglect are anatomically homologous, and instead suggests that egocentric neglect may involve damage to a shared, but hemispherically asymmetric attention network. By contrast, egocentric and allocentric neglect was associated with disconnectivity in a distinct but overlapping set of network edges, with both deficits related to damage across the dorsal and ventral attention networks. Critically, this finding suggests that the distinction between egocentric and allocentric neglect is unlikely to reflect a simple dichotomy between dorsal versus ventral networks dysfunction, as is commonly asserted. Taken together, the current findings provide a fresh perspective on the neural circuitry involved in regulating visuospatial attention, and provide important clues to understanding the cognitive and perceptual processes involved in this common and debilitating neuropsychological syndrome.

Hemodynamic imaging parameters in brain metastases patients – Agreement between multi-delay ASL and hypercapnic BOLD

Arterial spin labeling (ASL) MRI is a routine clinical imaging technique that provides quantitative cerebral blood flow (CBF) information. A related technique is blood oxygenation level-dependent (BOLD) MRI during hypercapnia, which can assess cerebrovascular reactivity (CVR). ASL is weighted towards arteries, whereas BOLD is weighted towards veins. Their associated parameters in heterogeneous tissue types or under different hemodynamic conditions remains unclear. Baseline multi-delay ASL MRI and BOLD MRI during hypercapnia were performed in fourteen patients with brain metastases. In the ROI analysis, the CBF and CVR values were positively correlated in regions showing sufficient reserve capacity (i.e. non-steal regions, rrm = 0.792). Additionally, longer hemodynamic lag times were related to lower baseline CBF (rrm = −0.822) and longer arterial arrival time (AAT; rrm = 0.712). In contrast, in regions exhibiting vascular steal an inverse relationship was found with higher baseline CBF related to more negative CVR (rrm = −0.273). These associations were confirmed in voxelwise analyses. The relationship between CBF, AAT and CVR measures seems to be dependent on the vascular status of the underlying tissue. Healthy tissue relationships do not hold in tissues experiencing impaired or exhausted autoregulation. CVR metrics can possibly identify at-risk areas before perfusion deficiencies become visible on ASL MRI, specifically within vascular steal regions.

Imaging Spectrum of the Developing Glioblastoma: A Cross-Sectional Observation Study.

Glioblastoma (GBM) has the typical radiological appearance (TRA) of a centrally necrotic, peripherally enhancing tumor with surrounding edema. The objective of this study was to determine whether the developing GBM displays a spectrum of imaging changes detectable on routine clinical imaging prior to TRA GBM. Patients with pre-operative imaging diagnosed with GBM (1 January 2014-31 March 2022) were identified from a neuroscience center. The imaging was reviewed by an experienced neuroradiologist. Imaging patterns preceding TRA GBM were analyzed. A total of 76 out of 555 (14%) patients had imaging preceding TRA GBM, 57 had solitary lesions, and 19 had multiple lesions (total = 84 lesions). Here, 83% of the lesions had cortical or cortical/subcortical locations. The earliest imaging features for 84 lesions were T2 hyperintensity/CT low density (n = 18), CT hyperdensity (n = 51), and T2 iso-intensity (n = 15). Lesions initially showing T2 hyperintensity/CT low density later showed T2 iso-intensity. When CT and MRI were available, all CT hyperdense lesions showed T2 iso-intensity, reduced diffusivity, and the following enhancement patterns: nodular 35%, solid 29%, none 26%, and patchy peripheral 10%. The mean time to develop TRA GBM from T2 hyperintensity was 140 days and from CT hyperdensity was 69 days. This research suggests that the developing GBM shows a spectrum of imaging features, progressing through T2 hyperintensity to CT hyperdensity, T2 iso-intensity, reduced diffusivity, and variable enhancement to TRA GBM. Red flags for non-TRA GBM lesions are cortical/subcortical CT hyperdense/T2 iso-intense/low ADC. Future research correlating this imaging spectrum with pathophysiology may provide insight into GBM growth patterns.

Metal artifact reduction in patients with total hip replacements: evaluation of clinical photon counting CT using virtual monoenergetic images

ObjectivesTo investigate photon-counting CT (PCCT)–derived virtual monoenergetic images (VMI) for artifact reduction in patients with unilateral total hip replacements (THR).MethodsForty-two patients with THR and portal-venous phase PCCT of the abdomen and pelvis were retrospectively included. For the quantitative analysis, region of interest (ROI)–based measurements of hypodense and hyperdense artifacts, as well as of artifact-impaired bone and the urinary bladder, were conducted, and corrected attenuation and image noise were calculated as the difference of attenuation and noise between artifact-impaired and normal tissue. Two radiologists qualitatively evaluated artifact extent, bone assessment, organ assessment, and iliac vessel assessment using 5-point Likert scales.ResultsVMI110keV yielded a significant reduction of hypo- and hyperdense artifacts compared to conventional polyenergetic images (CI) and the corrected attenuation closest to 0, indicating best possible artifact reduction (hypodense artifacts: CI: 237.8 ± 71.4 HU, VMI110keV: 8.5 ± 122.5 HU; p < 0.05; hyperdense artifacts: CI: 240.6 ± 40.8 HU vs. VMI110keV: 13.0 ± 110.4 HU; p < 0.05). VMI110keV concordantly provided best artifact reduction in the bone and bladder as well as the lowest corrected image noise. In the qualitative assessment, VMI110keV received the best ratings for artifact extent (CI: 2 (1–3), VMI110keV: 3 (2–4); p < 0.05) and bone assessment (CI: 3 (1–4), VMI110keV: 4 (2–5); p < 0.05), whereas organ and iliac vessel assessments were rated highest in CI and VMI70keV.ConclusionsPCCT-derived VMI effectively reduce artifacts from THR and thereby improve assessability of circumjacent bone tissue. VMI110keV yielded optimal artifact reduction without overcorrection, yet organ and vessel assessments at that energy level and higher were impaired by loss of contrast.Clinical relevance statementPCCT-enabled artifact reduction is a feasible method for improving assessability of the pelvis in patients with total hip replacements at clinical routine imaging.Key Points• Photon-counting CT-derived virtual monoenergetic images at 110 keV yielded best reduction of hyper- and hypodense artifacts, whereas higher energy levels resulted in artifact overcorrection.• The qualitative artifact extent was reduced best in virtual monoenergetic images at 110 keV, facilitating an improved assessment of the circumjacent bone.• Despite significant artifact reduction, assessment of pelvic organs as well as vessels did not profit from energy levels higher than 70 keV, due to the decline in image contrast.

Efficiency and Accuracy Evaluation of Multiple Diffusion-Weighted MRI Techniques Across Different Scanners.

The choice between different diffusion-weighted imaging (DWI) techniques is difficult as each comes with tradeoffs for efficient clinical routine imaging and apparent diffusion coefficient (ADC) accuracy. To quantify signal-to-noise-ratio (SNR) efficiency, ADC accuracy, artifacts, and distortions for different DWI acquisition techniques, coils, and scanners. Phantom, in vivo intraindividual biomarker accuracy between DWI techniques and independent ratings. NIST diffusion phantom. 51 Patients: 40 with prostate cancer and 11 with head-and-neck cancer at 1.5 T FIELD STRENGTH/SEQUENCE: Echo planar imaging (EPI): 1.5 T and 3 T Siemens; 3 T Philips. Distortion-reducing: RESOLVE (1.5 and 3 T Siemens); Turbo Spin Echo (TSE)-SPLICE (3 T Philips). Small field-of-view (FOV): ZoomitPro (1.5 T Siemens); IRIS (3 T Philips). Head-and-neck and flexible coils. SNR Efficiency, geometrical distortions, and susceptibility artifacts were quantified for different b-values in a phantom. ADC accuracy/agreement was quantified in phantom and for 51 patients. In vivo image quality was independently rated by four experts. QIBA methodology for accuracy: trueness, repeatability, reproducibility, Bland-Altman 95% Limits-of-Agreement (LOA) for ADC. Wilcoxon Signed-Rank and student tests on P < 0.05 level. The ZoomitPro small FOV sequence improved b-image efficiency by 8%-14%, reduced artifacts and observer scoring for most raters at the cost of smaller FOV compared to EPI. The TSE-SPLICE technique reduced artifacts almost completely at a 24% efficiency cost compared to EPI for b-values ≤500 sec/mm2 . Phantom ADC 95% LOA trueness were within ±0.03 × 10-3 mm2 /sec except for small FOV IRIS. The in vivo ADC agreement between techniques, however, resulted in 95% LOAs in the order of ±0.3 × 10-3 mm2 /sec with up to 0.2 × 10-3 mm2 /sec of bias. ZoomitPro for Siemens and TSE SPLICE for Philips resulted in a trade-off between efficiency and artifacts. Phantom ADC quality control largely underestimated in vivo accuracy: significant ADC bias and variability was found between techniques in vivo. 3 TECHNICAL EFFICACY STAGE: 2.

A robust radiomic-based machine learning approach to detect cardiac amyloidosis using cardiac computed tomography.

Cardiac amyloidosis (CA) shares similar clinical and imaging characteristics (e.g., hypertrophic phenotype) with aortic stenosis (AS), but its prognosis is generally worse than severe AS alone. Recent studies suggest that the presence of CA is frequent (1 out of 8 patients) in patients with severe AS. The coexistence of the two diseases complicates the prognosis and therapeutic management of both conditions. Thus, there is an urgent need to standardize and optimize the diagnostic process of CA and AS. The aim of this study is to develop a robust and reliable radiomics-based pipeline to differentiate the two pathologies. Thirty patients were included in the study, equally divided between CA and AS. For each patient, a cardiac computed tomography (CCT) was analyzed by extracting 107 radiomics features from the LV wall. Feature robustness was evaluated by means of geometrical transformations to the ROIs and intra-class correlation coefficient (ICC) computation. Various correlation thresholds (0.80, 0.85, 0.90, 0.95, 1), feature selection methods [p-value, least absolute shrinkage and selection operator (LASSO), semi-supervised LASSO, principal component analysis (PCA), semi-supervised PCA, sequential forwards selection] and machine learning classifiers (k-nearest neighbors, support vector machine, decision tree, logistic regression and gradient boosting) were assessed using a leave-one-out cross-validation. Data augmentation was performed using the synthetic minority oversampling technique. Finally, explainability analysis was performed by using the SHapley Additive exPlanations (SHAP) method. Ninety-two radiomic features were selected as robust and used in the further steps. Best performances of classification were obtained using a correlation threshold of 0.95, PCA (keeping 95% of the variance, corresponding to 9 PCs) and support vector machine classifier reaching an accuracy, sensitivity and specificity of 0.93. Four PCs were found to be mainly dependent on textural features, two on first-order statistics and three on shape and size features. These preliminary results show that radiomics might be used as non-invasive tool able to differentiate CA from AS using clinical routine available images.

Software compatibility analysis for quantitative measures of [18F]flutemetamol amyloid PET burden in mild cognitive impairment

RationaleAmyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods.MethodsComposite SUVr using the pons as the reference region was generated from [18F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVrpons was applied. Quantitative results from MIM Software’s MIMneuro, Syntermed’s NeuroQ, Hermes Medical Solutions’ BRASS and GE Healthcare’s CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores.ResultsUsing an Aβ positivity threshold of ≥ 0.6 SUVrpons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss’) and individual software pairings (Cohen’s), were ≥ 0.9 signifying “almost perfect” inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957–0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r2 = 0.98).ConclusionUsing an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [18F]flutemetamol amyloid PET with a ≥ 0.6 SUVrpons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.

Accurate gingival segmentation from 3D images with artificial intelligence: an animal pilot study

BackgroundGingival phenotype plays an important role in dental diagnosis and treatment planning. Traditionally, determining the gingival phenotype is done by manual probing of the gingival soft tissues, an invasive and time-consuming procedure. This study aims to evaluate the feasibility and accuracy of an alternatively novel, non-invasive technology based on the precise 3-dimension (3D) soft tissue reconstruction from intraoral scanning and cone beam computed tomography (CBCT) to predict the gingival biotype.MethodsAs a proof-of-concept, Yorkshire pig mandibles were scanned, and the CBCT data were fed into a deep-learning model to reconstruct the teeth and surrounding bone structure in 3D. By overlaying the CBCT scan with the intraoral scans, an accurate superposition was created and used for virtual measurements of the soft tissue thickness. Meanwhile, gingival thicknesses were also measured by a periodontal probe and digital caliper on the buccal and lingual sides at 3 mm apical to the gingival margin of the posterior teeth and compared with the virtual assessment at the same location. The data obtained from virtual and clinical measurements were compared by Wilcoxon matched-pairs signed-rank analysis, while their correlation was determined by Pearson’s r value. The Mann–Whitney U test was used for intergroup comparisons of the amount of difference.ResultsAmong 108 investigated locations, the clinical and virtual measurements are strongly positively correlated (r = 0.9656, P < 0.0001), and only clinically insignificant differences (0.066 ± 0.223 mm) were observed between the two assessments. There is no difference in the agreement between the virtual and clinical measurements on sexually matured samples (0.087 ± 0.240 mm) and pre-pubertal samples (0.033 ± 0.195 mm). Noticeably, there is a greater agreement between the virtual and clinical measurements at the buccal sites (0.019 ± 0.233 mm) than at the lingual sites (0.116 ± 0.215 mm).ConclusionIn summary, the artificial intelligence-based virtual measurement proposed in this work provides an innovative technique potentially for accurately measuring soft tissue thickness using clinical routine 3D imaging systems, which will aid clinicians in generating a more comprehensive diagnosis with less invasive procedures and, in turn, optimize the treatment plans with more predictable outcomes.

A novel method for long‐term preserving of urine microstructure using poly(vinyl chloride)

AbstractFor urinalysis teaching and routine clinical imaging of urine, urine microscopic test needs slides that can be clearly examined for long term, which is still under focus. This study hypothesized, that poly(vinyl chloride) (PVC) and polystyrene (PS) could be able to reserve the urine components for a long time. Therefore, we explored, for the first time upon our knowledge, the potential of PVC and PS polymers to adhere the cover slide. The physical properties, viscosity, average molecular weight, the tensile strength and intrinsic viscosity of the polymers were determined. A normal slide (8 × 3 cm × 1 mm) was used to test a urine sample in the presence of either 3% PVC in tetra hydro‐furan(THF) or 3% PS. The results of imaging the PVC and PS slide indicate a clear and transparent vision. The PVC urine slide maintains normal components of urine up to a year, which did not observe in the PS slide. These results suggest that PVC is an effective polymer to protect urine compositions from hydrolyses or decomposition, which makes this novel urine slide a successful candidate for long‐term teaching of urinalyses.

Clinical, Anatomical, and Demographic features associated with the use of Patient-Specific Advanced Visualization Modeling in Cerebrovascular Disease (P14-5.027)

<h3>Objective:</h3> Characterizing clinical attributes of three-dimensional (3D) advanced visualization (AV) modeling in complex cerebrovascular diseases (CVD). <h3>Background:</h3> Visualizing clinical imaging is traditionally accomplished via two-dimensional planar imaging. The growth of 3D-rendering technologies has created novel opportunities for advanced visualization (AV) in CVD, specifically cerebral aneurysms (CA) and arteriovenous malformation (AVMs). The limitations of 2D imaging in CVD may be mitigated with patient-specific AV models which can be seen using 3D Viewer software (3DV), Mixed Reality (XR), and/or 3D Printing (3DP). There remains a gap in knowledge, however, in understanding how these tools are being used in complex CVD. <h3>Design/Methods:</h3> The AV anatomical models are based on Digital Imaging and Communications in Medicine (DICOM) datasets procured via routine clinical imaging. DICOM datasets are segmented using computer-aided design (CAD) software into 3D files. Clinical, anatomical, and demographic features of CVD patients were analyzed. Descriptive statistics were used to characterize clinical attributes associated with AV models used in CVD. <h3>Results:</h3> Seven neurovascular physicians over 24 months requested 61 CVD cases. CA models accounted for 81.9% (n= 50) and AVMs accounted for 18.1% (n= 11) of AV modeling requests. CA data indicated that 80% of patients who received AV models were female (n= 40). Among the AV CA cases, 94% used rXA (rotational angiography), while the remaining used were CTA (4%) and MRI (2%). 3DP was used in 70% of CA cases (n = 35) to create physical models. <h3>Conclusions:</h3> Preliminarily, AV models are used in both CA and AVM and most frequently based on rXA imaging. CAs are commonly viewed using 3DV as well as 3DP. Future directions will include assessing the utility of AV models in CVD across training levels. Additionally, we will collect and compare clinical outcomes data to assess the efficacy of AV in complex CVD. <b>Disclosure:</b> Mr. Bhimarasetty has nothing to disclose. Dr. Sarkar has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for XRHealth. Dr. Sarkar has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for multiple.

The Gray Zone: LR3, LR-M, and LR-TIV

AbstractThe goal of Liver Imaging Reporting and Data System (LI-RADS) is to standardize the lexicon, imaging techniques, interpretation, and reporting of observations in patients with a potential risk for developing hepatocellular carcinoma (HCC), and, consequently, improve communication between radiologists and physicians. LI-RADS diagnostic algorithms are applied to a population “at risk,” follow a stepwise algorithmic approach which categorize and stratify individual observations as HCC, and also assess the likelihood of non-HCC malignancies and tumor in vein. Risk factors for developing HCC have geographical variations, which significantly impact diagnostic and management strategies; however, these variations are not considered in the LIRADS v2018 version. Further, the diagnostic algorithm includes several major and ancillary features, and, tie-breaking rules, which result in numerous probable combinations by which a plausible observation could be assigned a particular category, inherently increasing its complexity. Heterogeneity of the diagnostic algorithm results in certain imaging pitfalls and poses challenges in the precise characterization of observations, complicating its use in routine clinical practice. This article reviews the gray zones which may be encountered in the evaluation of LR-3, LR-M, and LR-TIV observations during routine clinical imaging with contrast-enhanced computed tomography and magnetic resonance imaging.

The Value of Various Post-Processing Modalities of Diffusion Weighted Imaging in the Detection of Multiple Sclerosis

Diffusion tensor imaging (DTI) showed its adequacy in evaluating the normal-appearing white matter (NAWM) and lesions in the brain that are difficult to evaluate with routine clinical magnetic resonance imaging (MRI) in multiple sclerosis (MS). Recently, MRI systems have been developed with regard to software and hardware, leading to different proposed diffusion analysis methods such as diffusion tensor imaging, q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, and axonal diameter measurement. These methods have the ability to better detect in vivo microstructural changes in the brain than DTI. These different analysis modalities could provide supplementary inputs for MS disease characterization and help in monitoring the disease's progression as well as treatment efficacy. This paper reviews some of the recent diffusion MRI methods used for the assessment of MS in vivo.

Abstract 252: A single-tube approach for detection of circulating tumor DNA using customized panels

Abstract Circulating tumor DNA (ctDNA) is a promising biomarker for cancer. Applications of ctDNA analysis include screening, diagnosis, treatment selection, minimal residual disease (MRD) detection and recurrence monitoring. While some applications are best served by tumor-agnostic panels covering large regions of the genome, such large panels are not universally appropriate due to limitations in sensitivity, user-friendliness, turn-around time (TAT), and sequencing cost. One application where customized, tumor-informed panels can be preferable is detection of MRD and cancer recurrence, and multiple studies have shown that ctDNA can detect residual/recurrent disease several months earlier than routine clinical imaging. This application requires high sensitivity and in most cases will involve repeat testing of longitudinal samples collected over several months or years. In this scenario, the ideal assay characteristics include tumor-informed, personalized assay panels, with a simple, rapid workflow, and with minimal cost per assay. We have developed the Fluent LBx assay to meet these requirements. Fluent LBx analysis can be performed on-site in any appropriately equipped research or clinical laboratory, avoiding the extra cost and delay associated with external testing. Fluent LBx is a variation on SiMSen-Seq (PMID 27060140) that uses modified target and adapter primer sequences to facilitate barcoding and uniform amplification of multiple targets in a single-tube library construction protocol. Library preparation can be completed in under 1.5 hours with approximately 20 minutes of hands-on time. Using this approach, target DNA molecules are first barcoded and then amplified with indexed adaptors compatible with Illumina sequencers, in a single PCR reaction. After clean-up and sequencing, barcode information is used to compile reads from individual DNA molecules and minimize base calling errors introduced during PCR and sequencing. Here we present data demonstrating uniformity, sensitivity and specificity of Fluent LBx assays using LGC SeraCare quality control standards. Additionally, we present longitudinal clinical demonstration of residual disease detection from ctDNA collected from multiple head and neck and gastrointestinal cancer patients through longitudinal monitoring post therapeutic intervention. The Fluent LBx workflow allows rapid, inexpensive, patient-specific monitoring of MRD and recurrence in multiple cancer indications. Citation Format: Robert Meltzer, Jessalyn Kaur, Ekaterina Kintsurashvili, Christopher D'Amato, Tony Godfrey. A single-tube approach for detection of circulating tumor DNA using customized panels [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 252.

Comparison of optimization parametrizations for regional lung compliance estimation using personalized pulmonary poromechanical modeling.

Interstitial lung diseases, such as idiopathic pulmonary fibrosis (IPF) or post-COVID-19 pulmonary fibrosis, are progressive and severe diseases characterized by an irreversible scarring of interstitial tissues that affects lung function. Despite many efforts, these diseases remain poorly understood and poorly treated. In this paper, we propose an automated method for the estimation of personalized regional lung compliances based on a poromechanical model of the lung. The model is personalized by integrating routine clinical imaging data - namely computed tomography images taken at two breathing levels in order to reproduce the breathing kinematic-notably through an inverse problem with fully personalized boundary conditions that is solved to estimate patient-specific regional lung compliances. A new parametrization of the inverse problem is introduced in this paper, based on the combined estimation of a personalized breathing pressure in addition to material parameters, improving the robustness and consistency of estimation results. The method is applied to three IPF patients and one post-COVID-19 patient. This personalized model could help better understand the role of mechanics in pulmonary remodeling due to fibrosis; moreover, patient-specific regional lung compliances could be used as an objective and quantitative biomarker for improved diagnosis and treatment follow up for various interstitial lung diseases.

A review of radiological definitions of sarcopenia in cancer

AbstractBackgroundSarcopenia in cancer impacts overall survival, surgical complications, and side effects of oncological treatments. Cancer patients frequently receive cross‐sectional imaging, allowing incidental capture of radiological sarcopenia biomarkers. These biomarkers vary by imaging modality, tumour group, patient demographics, and anatomy but lack a consensus with regard to clinical application. In this article, we provide an overview of radiology‐based sarcopenia biomarkers by anatomy and their prevalence in the literature.MethodsIn accordance with previously published scoping review protocol, we searched PubMed/MEDLINE, Embase, Scopus, and Cochrane between 2007 and June 2021. Studies were independently reviewed by two authors with Cohen's kappa 0.81 and reported using descriptive statistics.ResultsThere were 5649 titles and abstracts reviewed, including 459 full‐text articles. There were 23 additions found through references, resulting in 482 total studies. There is a consistent year‐on‐year increase of new radiological sarcopenia landmarks since 2015, with 49.8% studies reporting novel definitions of sarcopenia. The majority of studies ranged between 50 and 300 participants and featured an abdominal sarcopenia marker (94.4%), of which 75.2% used the skeletal muscle index at L3 (L3SMI). Sarcopenia prevalence ranged from 8.33% to 89.66%. Biomarkers are often applied across genders and ethnicities, regardless of the original population the definition originated from, despite the emergence and availability of ethnic‐specific alternatives.ConclusionThere remains a need to incorporate demographics and age into predictive models derived from sarcopenia biomarkers obtained through routine clinical imaging. Use of individual biomarkers needs to be made with careful consideration of the population in which the biomarkers were generated.

Orofacial Pain and Temporomandibular Joint Disorder: Chair-Side Routine Diagnostics (Radiography, Ultrasonography) and Mihalyi Ultrasonography Measured Splint Therapy, A Case Report

Aim: An increased prevalence of temporomandibular disorders (TMD) has been seen over the last few decades. It is a common issue worldwide considering that a significant part of orofacial pain of non-dental origin is caused by TMD [1]. The present study aims to explain which chair-side examinations can be useful for the diagnostics of the TMD caused pain and thereby an appropriate treatment can be chosen to eliminate the complaints. Methods: In addition to routine clinical examination, radiography and ultrasound imaging provides short examination time, low cost, non-invasive compared with the magnetic resonance imaging (MRI). By radiograph diagnostics can anatomical deviations and serious bilateral differences be recognized. Sonography provides dynamic visualization of the soft-tissue structures of the temporomandibular joint (TMJ). This asymmetric splint therapy is aimed to reduce pain and stress on the joint structure and to protect the associated structures, thereby increasing the quality of life. Results: We compare the distances of the joint spaces according the ulrasonography and with the difference of these we modify the splint. After 8 weeks of individual ultrasonography measured splint therapy treatment the patient has experienced a relief of her TMD signs and symptoms. After the treatment the patiens’s symptoms decreased. Conclusion: Using ultrasonography combined with TMJ x-ray can be a good diagnostic tool. Hence, by using the Mihályi Ultrasonography Measured Splint therapy we provide an individual, non-invasive treatment for patients with temporomandibular disorders.

Orofacial Pain and Temporomandibular Joint Disorder: Chair-Side Routine Diagnostics (Radiography, Ultrasonography) and Mihalyi Ultrasonography Measured Splint Therapy, A Case Report

Aim: An increased prevalence of temporomandibular disorders (TMD) has been seen over the last few decades. It is a common issue worldwide considering that a significant part of orofacial pain of non-dental origin is caused by TMD [1]. The present study aims to explain which chair-side examinations can be useful for the diagnostics of the TMD caused pain and thereby an appropriate treatment can be chosen to eliminate the complaints. Methods: In addition to routine clinical examination, radiography and ultrasound imaging provides short examination time, low cost, non-invasive compared with the magnetic resonance imaging (MRI). By radiograph diagnostics can anatomical deviations and serious bilateral differences be recognized. Sonography provides dynamic visualization of the soft-tissue structures of the temporomandibular joint (TMJ). This asymmetric splint therapy is aimed to reduce pain and stress on the joint structure and to protect the associated structures, thereby increasing the quality of life. Results: We compare the distances of the joint spaces according the ulrasonography and with the difference of these we modify the splint. After 8 weeks of individual ultrasonography measured splint therapy treatment the patient has experienced a relief of her TMD signs and symptoms. After the treatment the patiens’s symptoms decreased. Conclusion: Using ultrasonography combined with TMJ x-ray can be a good diagnostic tool. Hence, by using the Mihályi Ultrasonography Measured Splint therapy we provide an individual, non-invasive treatment for patients with temporomandibular disorders.

Estimation of differential renal function on routine abdominal imaging employing compressed-sensed contrast-enhanced MR: a feasibility study referenced against dynamic renal scintigraphy in patients with deteriorating renal retention parameters

PurposeTo assess whether high temporal/spatial resolution GRASP MRI acquired during routine clinical imaging can identify several degrees of renal function impairment referenced against renal dynamic scintigraphy.MethodsThis retrospective study consists of method development and method verification parts. During method development, patients subject to renal imaging using gadoterate meglumine and GRASP post-contrast MRI technique (TR/TE 3.3/1.6 ms; FoV320 × 320 mm; FA12°; Voxel1.1 × 1.1x2.5 mm) were matched into four equally-sized renal function groups (no-mild-moderate-severe impairment) according to their laboratory-determined estimated glomerular filtration rates (eGFR); 60|120 patients|kidneys were included. Regions-of-interest (ROIs) were placed on cortices, medullary pyramids and collecting systems of bilateral kidneys. Cortical perfusion, tubular concentration and collecting system excretion were determined as TimeCortex=Pyramid(sec), SlopeTubuli (sec−1), and TimeCollecting System (sec), respectively, and were measured by a combination of extraction of time intensity curves and respective quantitative parameters. For method verification, patients subject to GRASP MRI and renal dynamic scintigraphy (99mTc-MAG3, 100 MBq/patient) were matched into three renal function groups (no-mild/moderate-severe impairment). Split renal function parameters post 1.5–2.5 min as well as MAG3 TER were correlated with time intensity parameters retrieved using GRASP technique; 15|30 patients|kidneys were included.ResultsMethod development showed differing values for TimeCortex=Pyramid(71|75|93|122 s), SlopeTubuli(2.6|2.1|1.3|0.5 s−1) and TimeCollecting System(90|111|129|139 s) for the four renal function groups with partial significant tendencies (several p-values < 0.001). In method verification, 29/30 kidneys (96.7%) were assigned to the correct renal function group.ConclusionHigh temporal and spatial resolution GRASP MR imaging allows to identify several degrees of renal function impairment using routine clinical imaging with a high degree of accuracy.

Optimized three-dimensional ultrashort echo time: Magnetic resonance fingerprinting for myelin tissue fraction mapping.

Quantitative assessment of brain myelination has gained attention for both research and diagnosis of neurological diseases. However, conventional pulse sequences cannot directly acquire the myelin-proton signals due to its extremely short T2 and T2* values. To obtain the myelin-proton signals, dedicated short T2 acquisition techniques, such as ultrashort echo time (UTE) imaging, have been introduced. However, it remains challenging to isolate the myelin-proton signals from tissues with longer T2. In this article, we extended our previous two-dimensional ultrashort echo time magnetic resonance fingerprinting (UTE-MRF) with dual-echo acquisition to three dimensional (3D). Given a relatively low proton density (PD) of myelin-proton, we utilized Cramér-Rao Lower Bound to encode myelin-proton with the maximal SNR efficiency for optimizing the MR fingerprinting design, in order to improve the sensitivity of the sequence to myelin-proton. In addition, with a second echo of approximately 3ms, myelin-water component can be also captured. A myelin-tissue (myelin-proton and myelin-water) fraction mapping can be thus calculated. The optimized 3D UTE-MRF with dual-echo acquisition is tested in simulations, physical phantom and in vivo studies of both healthy subjects and multiple sclerosis patients. The results suggest that the rapidly decayed myelin-proton and myelin-water signal can be depicted with UTE signals of our method at clinically relevant resolution (1.8 mm isotropic) in 15 min. With its good sensitivity to myelin loss in multiple sclerosis patients demonstrated, our method for the whole brain myelin-tissue fraction mapping in clinical friendly scan time has the potential for routine clinical imaging.