A joint brain extraction and image quality assessment framework for fetal brain MRI slices.

Brain extraction and image quality assessment are two fundamental steps in fetal brain magnetic resonance imaging (MRI) 3D reconstruction and quantification. However, the randomness of fetal position and orientation, the variability of fetal brain morphology, maternal organs around the fetus, and the scarcity of data samples, all add excessive noise and impose a great challenge to automated brain extraction and quality assessment of fetal MRI slices. Conventionally, brain extraction and quality assessment are typically performed independently. However, both of them focus on the brain image representation, so they can be jointly optimized to ensure the network learns more effective features and avoid overfitting. To this end, we propose a novel two-stage dual-task deep learning framework with a brain localization stage and a dual-task stage for joint brain extraction and quality assessment of fetal MRI slices. Specifically, the dual-task module compactly contains a feature extraction module, a quality assessment head and a segmentation head with feature fusion for simultaneous brain extraction and quality assessment. Besides, a transformer architecture is introduced into the feature extraction module and the segmentation head. We utilize a multi-step training strategy to guarantee a stable and successful training of all modules. Finally, we validate our method by a 5-fold cross-validation and ablation study on a dataset with fetal brain MRI slices in different qualities, and perform a cross-dataset validation in addition. Experiments show that the proposed framework achieves very promising performance.

The effect of head motion on brain age prediction using deep convolutional neural networks.

Deep learning can be used effectively to predict participants' age from brain magnetic resonance imaging (MRI) data, and a growing body of evidence suggests that the difference between predicted and chronological age-referred to as brain-predicted age difference (brain-PAD)-is related to various neurological and neuropsychiatric disease states. A crucial aspect of the applicability of brain-PAD as a biomarker of individual brain health is whether and how brain-predicted age is affected by MR image artifacts commonly encountered in clinical settings. To investigate this issue, we trained and validated two different 3D convolutional neural network architectures (CNNs) from scratch and tested the models on a separate dataset consisting of motion-free and motion-corrupted T1-weighted MRI scans from the same participants, the quality of which were rated by neuroradiologists from a clinical diagnostic point of view. Our results revealed a systematic increase in brain-PAD with worsening image quality for both models. This effect was also observed for images that were deemed usable from a clinical perspective, with brains appearing older in medium than in good quality images. These findings were also supported by significant associations found between the brain-PAD and standard image quality metrics indicating larger brain-PAD for lower-quality images. Our results demonstrate a spurious effect of advanced brain aging as a result of head motion and underline the importance of controlling for image quality when using brain-predicted age based on structural neuroimaging data as a proxy measure for brain health.

The "hidden noise" problem in MR image reconstruction.

PURPOSE: The performance of modern image reconstruction methods is commonly judged using quantitative error metrics like root mean squared-error and the structural similarity index, which are calculated by comparing reconstructed images against fully sampled reference data. In practice, the reference data will contain noise and is not a true gold standard. In this work, we demonstrate that the "hidden noise" present in reference data can substantially confound standard approaches for ranking different image reconstruction results. METHODS: Using both experimental and simulated k-space data and several different image reconstruction techniques, we examined whether there was correlation between performance metrics obtained with typical noisy reference data versus those obtained with higher-quality reference data. RESULTS: For conventional performance metrics, the reconstructions that matched best with the higher-quality reference data were substantially different from the reconstructions that matched best with typical noisy reference data. This leads to suboptimal reconstruction results if the performance with respect to noisy reference data is used to select which reconstruction methods/parameters to employ. These issues were reduced when employing alternative error metrics that better account for noise. CONCLUSION: Reference data containing hidden noise can substantially mislead the ranking of image reconstruction methods when using conventional error metrics, but this issue can be mitigated with alternative error metrics.

Comprehensive assessment of nonuniform image quality: Application to imaging near metal.

PURPOSE: Comprehensive assessment of image quality requires accounting for spatial variations in (i) intensity artifact, (ii) geometric distortion, (iii) signal-to-noise ratio (SNR), and (iv) spatial resolution, among other factors. This work presents an ensemble of methods to meet this need, from phantom design to image analysis, and applies it to the scenario of imaging near metal. METHODS: A modular phantom design employing a gyroid lattice is developed to enable the co-registered volumetric quantitation of image quality near a metallic hip implant. A method for measuring spatial resolution by means of local point spread function (PSF) estimation is presented and the relative fitness of gyroid and cubic lattices is examined. Intensity artifact, geometric distortion, and SNR maps are also computed. Results are demonstrated with 2D-FSE and MAVRIC-SL scan protocols on a 3T MRI scanner. RESULTS: The spatial resolution method demonstrates a worst-case error of 0.17 pixels for measuring in-plane blurring up to 3 pixels (full width at half maximum). The gyroid outperforms a cubic lattice design for the local PSF estimation task. The phantom supports four configurations toggling the presence/absence of both metal and structure with good spatial correspondence for co-registered analysis of the four quality factors. The marginal scan time to evaluate one scan protocol amounts to five repetitions. The phantom design can be fabricated in 2 days at negligible material cost. CONCLUSION: The phantom and associated analysis methods can elucidate complex image quality trade-offs involving intensity artifact, geometric distortion, SNR, and spatial resolution. The ensemble of methods is suitable for benchmarking imaging performance near metal.

IE-CycleGAN: improved cycle consistent adversarial network for unpaired PET image enhancement.

PURPOSE: Technological advances in instruments have greatly promoted the development of positron emission tomography (PET) scanners. State-of-the-art PET scanners such as uEXPLORER can collect PET images of significantly higher quality. However, these scanners are not currently available in most local hospitals due to the high cost of manufacturing and maintenance. Our study aims to convert low-quality PET images acquired by common PET scanners into images of comparable quality to those obtained by state-of-the-art scanners without the need for paired low- and high-quality PET images. METHODS: In this paper, we proposed an improved CycleGAN (IE-CycleGAN) model for unpaired PET image enhancement. The proposed method is based on CycleGAN, and the correlation coefficient loss and patient-specific prior loss were added to constrain the structure of the generated images. Furthermore, we defined a normalX-to-advanced training strategy to enhance the generalization ability of the network. The proposed method was validated on unpaired uEXPLORER datasets and Biograph Vision local hospital datasets. RESULTS: For the uEXPLORER dataset, the proposed method achieved better results than non-local mean filtering (NLM), block-matching and 3D filtering (BM3D), and deep image prior (DIP), which are comparable to Unet (supervised) and CycleGAN (supervised). For the Biograph Vision local hospital datasets, the proposed method achieved higher contrast-to-noise ratios (CNR) and tumor-to-background SUVmax ratios (TBR) than NLM, BM3D, and DIP. In addition, the proposed method showed higher contrast, SUVmax, and TBR than Unet (supervised) and CycleGAN (supervised) when applied to images from different scanners. CONCLUSION: The proposed unpaired PET image enhancement method outperforms NLM, BM3D, and DIP. Moreover, it performs better than the Unet (supervised) and CycleGAN (supervised) when implemented on local hospital datasets, which demonstrates its excellent generalization ability.

90Y post-radioembolization clinical assessment with whole-body Biograph Vision Quadra PET/CT: image quality, tumor, liver and lung dosimetry.

PURPOSE: Evaluation of 90Y liver radioembolization post-treatment clinical data using a whole-body Biograph Vision Quadra PET/CT to investigate the potential of protocol optimization in terms of scan time and dosimetry. METHODS: 17 patients with hepatocellular carcinoma with median (IQR) injected activity 2393 (1348-3298) MBq were included. Pre-treatment dosimetry plan was based on 99mTc-MAA SPECT/CT with Simplicit90Y™ and post-treatment validation with Quadra using Simplicit90Y™ and HERMIA independently. Regarding the image analysis, mean and peak SNR, the coefficient of variation (COV) and lesion-to-background ratio (LBR) were evaluated. For the post-treatment dosimetry validation, the mean tumor, whole liver and lung absorbed dose evaluation was performed using Simplicit90Y and HERMES. Images were reconstructed with 20-, 15-, 10-, 5- and 1- min sinograms with 2, 4, 6 and 8 iterations. Wilcoxon signed rank test was used to show statistical significance (p < 0.05). RESULTS: There was no difference of statistical significance between 20- and 5- min reconstructed times for the peak SNR, COV and LBR. In addition, there was no difference of statistical significance between 20- and 1- min reconstructed times for all dosimetry metrics. Lung dosimetry showed consistently lower values than the expected. Tumor absorbed dose based on Simplicit90Y™ was similar to the expected while HERMES consistently underestimated significantly the measured tumor absorbed dose. Finally, there was no difference of statistical significance between expected and measured tumor, whole liver and lung dose for all reconstruction times. CONCLUSION: In this study we evaluated, in terms of image quality and dosimetry, whole-body PET clinical images of patients after having been treated with 90Y microspheres radioembolization for liver cancer. Compared to the 20-min standard scan, the simulated 5-min reconstructed images provided equal image peak SNR and noise behavior, while performing also similarly for post-treatment dosimetry of tumor, whole liver and lung absorbed doses.

FDG imaging with long-axial field-of-view PET/CT in patients with high blood glucose-a matched pair analysis.

PURPOSE: High blood glucose (hBG) in patients undergoing [18F]FDG PET/CT scans often results in rescheduling the examination, which may lead to clinical delay for the patient and decrease productivity for the department. The aim of this study was to evaluate whether long-axial field-of-view (LAFOV) PET/CT can minimize the effect of altered bio-distribution in hBG patients and is able to provide diagnostic image quality in hBG situations. MATERIALS AND METHODS: Oncologic patients with elevated blood glucose (≥ 8.0 mmol/l) and normal blood glucose (< 8.0 mmol/l, nBG) levels were matched for tumor entity, gender, age, and BMI. hBG patients were further subdivided into two groups (BG 8-11 mmol/l and BG > 11 mmol/l). Tracer uptake in the liver, muscle, and tumor was evaluated. Furthermore, image quality was compared between long acquisitions (ultra-high sensitivity mode, 360 s) on a LAFOV PET/CT and routine acquisitions equivalent to a short-axial field-of-view scanner (simulated (sSAFOV), obtained with high sensitivity mode, 120 s). Tumor-to-background ratio (TBR) and contrast-to-noise ratio (CNR) were used as the main image quality criteria. RESULTS: Thirty-one hBG patients met the inclusion criteria and were matched with 31 nBG patients. Overall, liver uptake was significantly higher in hBG patients (SUVmean, 3.07 ± 0.41 vs. 2.37 ± 0.33; p = 0.03), and brain uptake was significantly lower (SUVmax, 7.58 ± 0.74 vs. 13.38 ± 3.94; p < 0.001), whereas muscle (shoulder/gluteal) uptake showed no statistically significant difference. Tumor uptake was lower in hBG patients, resulting in a significantly lower TBR in the hBG cohort (3.48 ± 0.74 vs. 5.29 ± 1.48, p < 0.001). CNR was higher in nBG compared to hBG patients (12.17 ± 4.86 vs. 23.31 ± 12.22, p < 0.001). However, subgroup analysis of nBG 8-11 mmol/l on sSAFOV PET/CT compared to hBG (> 11 mmol/l) patients examined with LAFOV PET/CT showed no statistical significant difference in CNR (19.84 ± 8.40 vs. 17.79 ± 9.3, p = 0.08). CONCLUSION: While elevated blood glucose (> 11 mmol) negatively affected TBR and CNR in our cohort, the images from a LAFOV PET-scanner had comparable CNR to PET-images acquired from nBG patients using sSAFOV PET/CT. Therefore, we argue that oncologic patients with increased blood sugar levels might be imaged safely with LAFOV PET/CT when rescheduling is not feasible.

Comparison of Reduced and Full Field of View in Diffusion-Weighted MRI on Image Quality: A Meta-Analysis.

BACKGROUND: Reduced field of view (rFOV) diffusion-weighted imaging (DWI) in MRI shows potential for enhanced image quality compared with traditional full field of view (fFOV) DWI. Evaluating rFOV DWI's impact on image quality is important for clinical adoption. OBJECTIVE: To assess the efficacy of rFOV DWI in improving image quality, focusing on artifact reduction, signal-to-noise ratio (SNR) improvement, and lesion detectability. STUDY TYPE: Meta-analysis. POPULATION: Systematic literature search was conducted in PubMed, Embase, the Cochrane Library, and Web of Science ending in January 2024. Thirteen studies with 765 participants focusing on DWI quality using rFOV was analyzed. FIELD STRENGTH/SEQUENCE: SS-EPI, Rtr-SS-EPI, 2D-SS-EPI at 3.0 T. ASSESSMENT: Two investigators performed the data extraction. QUADAS-2 assessed bias. The image quality assessment of rFOV and fFOV DWI were compared. STATISTICAL TESTS: Standardized mean difference (SMD) was utilized to evaluate and standardize MRI image quality. Heterogeneity was assessed using the I2 statistic and publication bias was evaluated with Egger's test. RESULTS: The QUADAS-2 analysis revealed that most studies exhibited a low risk of bias and minimal concerns regarding applicability. Statistical analysis indicated that rFOV DWI yielded higher subjective image quality scores (SMD = 0.535, 95% CI: 0.339, 0.731, I2 = 45.7%) compared with fFOV DWI and was more effective in reducing artifacts (SMD = 0.44, 95% CI: 0.209, 0.672, I2 = 42.3%) than fFOV DWI. However, a decrease in SNR was noted with rFOV DWI (SMD = -0.670, 95% CI: -1.187 to -0.152, I2 = 87.9%). Additionally, rFOV DWI demonstrated enhancements in lesion visibility (SMD = 0.432, 95% CI: -1.187, -0.152, I2 = 53.1%) and anatomical details (SMD = 0.598, 95% CI: 0.121, 1.075, I2 = 90.8%). DATA CONCLUSION: rFOV DWI enhances MRI image quality by reducing artifacts and improving lesion visibility with a SNR trade-off. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Motion Robust MR Fingerprinting Scan to Image Neonates With Prenatal Opioid Exposure.

PURPOSE: To explore whether MR fingerprinting (MRF) scans provide motion-robust and quantitative brain tissue measurements for non-sedated infants with prenatal opioid exposure (POE). STUDY TYPE: Prospective. POPULATION: 13 infants with POE (3 male; 12 newborns (age 7-65 days) and 1 infant aged 9-months). FIELD STRENGTH/SEQUENCE: 3T, 3D T1-weighted MPRAGE, 3D T2-weighted TSE and MRF sequences. ASSESSMENT: The image quality of MRF and MRI was assessed in a fully crossed, multiple-reader, multiple-case study. Sixteen image quality features in three types-image artifacts, structure and myelination visualization-were ranked by four neuroradiologists (8, 7, 5, and 8 years of experience respectively), using a 3-point scale. MRF T1 and T2 values in 8 white matter brain regions were compared between babies younger than 1 month and babies between 1 and 2 months. STATISTICAL TESTS: Generalized estimating equations model to test the significance of differences of regional T1 and T2 values of babies under 1 month and those older. MRI and MRF image quality was assessed using Gwet's second order auto-correlation coefficient (AC2) with confidence levels. The Cochran-Mantel-Haenszel test was used to assess the difference in proportions between MRF and MRI for all features and stratified by the type of features. A P value <0.05 was considered statistically significant. RESULTS: The MRF of two infants were excluded in T1 and T2 value analysis due to severe motion artifact but were included in the image quality assessment. In infants under 1 month of age (N = 6), the T1 and T2 values were significantly higher compared to those between 1 and 2 months of age (N = 4). MRF images showed significantly higher image quality ratings in all three feature types compared to MRI images. CONCLUSIONS: MR Fingerprinting scans have potential to be a motion-robust and efficient method for nonsedated infants. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 1.

Second-Order Motion-Compensated Echo-Planar Cardiac Diffusion-Weighted MRI: Usefulness of Compressed Sensitivity Encoding.

BACKGROUND: Cardiac diffusion-weighted imaging (DWI) using second-order motion-compensated spin echo (M2C) can provide noninvasive in-vivo microstructural assessment, but limited by relatively low signal-to-noise ratio (SNR). Echo-planar imaging (EPI) with compressed sensitivity encoding (EPICS) could address these issues. PURPOSE: To combine M2C DWI and EPCIS (M2C EPICS DWI), and compare image quality for M2C DWI. STUDY TYPE: Prospective. POPULATION: Ten ex-vivo hearts, 10 healthy volunteers (females, 5 [50%]; mean ± SD of age, 25 ± 4 years), and 12 patients with diseased hearts (female, 1 [8.3%]; mean ± SD of age, 44 ± 16 years; including coronary artery heart disease, congenital heart disease, dilated cardiomyopathy, amyloidosis, and myocarditis). FIELD STRENGTH/SEQUENCE: 3-T, M2C EPICS DWI, and M2C DWI. ASSESSMENT: The apparent SNR (aSNR) and the rating scores were used to evaluate and compared image quality of all three groups. The aSNR was calculated using aSNR = Mean intensity myocardium / Standard deviation myocardium $$ \mathrm{aSNR}={\mathrm{Mean}\ \mathrm{intensity}}_{\mathrm{myocardium}}/{\mathrm{Standard}\ \mathrm{deviation}}_{\mathrm{myocardium}} $$ , and the myocardium was segmented manually. Three observers independently rated subjective image quality using a 5-point Likert scale. STATISTICAL TESTS: Bland-Altman analysis and paired t-tests. The threshold for statistical significance was set at P < 0.05. RESULTS: In healthy volunteers, the aSNR with a b-value of 450 s/mm2 acquired by M2C EPICS DWI was significantly higher than M2C DWI at in-plane resolutions of 3.0 × 3.0, 2.5 × 2.5, and 2.0 × 2.0 mm2. In patients with diseased hearts, the aSNR ofM2C EPICS DWI was also significantly higher than that for M2C DWI (bias of M2C EPICS-M2C = 1.999, 95% limits of agreement, 0.362 to 3.636; mean ± SD, 7.80 ± 1.37 vs. 5.80 ± 0.81). The ADC values of M2C EPICS was significantly higher than M2C DWI in in-vivo hearts. Over 80% of the images with rating scores for M2C EPICS DWI were higher than M2C DWI in in-vivo hearts. DATA CONCLUSION: Cardiac imaging by M2C EPICS DWI may demonstrate better overall image quality and higher aSNR than M2C DWI. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Computed Diffusion-Weighted Images of Rectal Cancer: Image Quality, Restaging, and Treatment Response after Neoadjuvant Therapy.

BACKGROUND: Computed diffusion-weighted images (cDWI) of random b value could be derived from acquired DWI (aDWI) with at least two different b values. However, its comparison between aDWI and cDWI images in locally advanced rectal cancer (LARC) patients after neoadjuvant therapy (NT) is needed. PURPOSE: To compare the cDWI and aDWI in image quality, restaging, and treatment response of LARC after NT. STUDY TYPE: Retrospective. POPULATION: Eighty-seven consecutive patients. FIELD STRENGTH/SEQUENCE: 3.0 T/DWI. ASSESSMENT: All patients underwent two DWI sequences, including conventional acquisition with b = 0 and 1000 s/mm2 (aDWIb1000 ) and another with b = 0 and 700 s/mm2 on a 3.0-T MR scanner. The images of the latter were used to compute the diffusion images with b = 1000 s/mm2 (cDWIb1000 ). Four radiologists with 3, 4, 14, and 25 years of experience evaluated the images to compare the image quality, TN restaging performance, and treatment response between aDWIb1000 and cDWIb1000 . STATISTICAL TESTS: Interclass correlation coefficients, weighted κ coefficient, paired Wilcoxon, and McNemar or Fisher test were used. A significance level of 0.05 was used. RESULTS: The cDWIb1000 images were superior to the aDWIb1000 ones in both subjective and objective image quality. In T restaging, the overall diagnostic accuracy of cDWIb1000 images was higher than that of aDWIb1000 images (57.47% vs. 49.43%, P = 0.289 for the inexperienced radiologist; 77.01% vs. 63.22%, significant for the experienced radiologist), with better sensitivity in determining ypT0-Tis tumors. Additionally, it increased the sensitivity in detecting ypT2 tumors for the inexperienced radiologist and ypT3 tumors for the experienced radiologist. N restaging and treatment response were found to be similar between two sequences for both radiologists. DATA CONCLUSION: Compared to aDWIb1000 images, the computed ones might serve as a wise approach, providing comparable or better image quality, restaging performance, and treatment response assessment for LARC after NT. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Impact of coronary CT image quality on the accuracy of the FFRCT Planner.

OBJECTIVE: To assess the accuracy of a virtual stenting tool based on coronary CT angiography (CCTA) and fractional flow reserve (FFR) derived from CCTA (FFRCT Planner) across different levels of image quality. MATERIALS AND METHODS: Prospective, multicenter, single-arm study of patients with chronic coronary syndromes and lesions with FFR ≤ 0.80. All patients underwent CCTA performed with recent-generation scanners. CCTA image quality was adjudicated using the four-point Likert scale at a per-vessel level by an independent committee blinded to the FFRCT Planner. Patient- and technical-related factors that could affect the FFRCT Planner accuracy were evaluated. The FFRCT Planner was applied mirroring percutaneous coronary intervention (PCI) to determine the agreement with invasively measured post-PCI FFR. RESULTS: Overall, 120 patients (123 vessels) were included. Invasive post-PCI FFR was 0.88 ± 0.06 and Planner FFRCT was 0.86 ± 0.06 (mean difference 0.02 FFR units, the lower limit of agreement (LLA) - 0.12, upper limit of agreement (ULA) 0.15). CCTA image quality was assessed as excellent (Likert score 4) in 48.3%, good (Likert score 3) in 45%, and sufficient (Likert score 2) in 6.7% of patients. The FFRCT Planner was accurate across different levels of image quality with a mean difference between FFRCT Planner and invasive post-PCI FFR of 0.02 ± 0.07 in Likert score 4, 0.02 ± 0.07 in Likert score 3 and 0.03 ± 0.08 in Likert score 2, p = 0.695. Nitrate dose ≥ 0.8mg was the only independent factor associated with the accuracy of the FFRCT Planner (95%CI - 0.06 to - 0.001, p = 0.040). CONCLUSION: The FFRCT Planner was accurate in predicting post-PCI FFR independent of CCTA image quality. CLINICAL RELEVANCE STATEMENT: Being accurate in predicting post-PCI FFR across a wide spectrum of CT image quality, the FFRCT Planner could potentially enhance and guide the invasive treatment. Adequate vasodilation during CT acquisition is relevant to improve the accuracy of the FFRCT Planner. KEY POINTS: • The fractional flow reserve derived from coronary CT angiography (FFRCT) Planner is a novel tool able to accurately predict fractional flow reserve after percutaneous coronary intervention. • The accuracy of the FFRCT Planner was confirmed across a wide spectrum of CT image quality. Nitrates dose at CT acquisition was the only independent predictor of its accuracy. • The FFRCT Planner could potentially enhance and guide the invasive treatment.

Feasibility and image quality of bright-blood and black-blood phase-sensitive inversion recovery (BOOST) sequence in clinical practice using for left atrial visualization in patients with atrial fibrillation.

OBJECTIVES: Visualizing left atrial anatomy including the pulmonary veins (PVs) is important for planning the procedure of pulmonary vein isolation with ablation in patients with atrial fibrillation (AF). The aims of our study are to investigate the feasibility of the 3D whole-heart bright-blood and black-blood phase-sensitive (BOOST) inversion recovery sequence in patients with AF scheduled for ablation or electro-cardioversion, and to analyze the correlation between image quality and heart rate and rhythm of patients. METHODS: BOOST was performed for assessing PVs both with T2 preparation pre-pulse (T2prep) and magnetization transfer preparation (MTC) in 45 patients with paroxysmal or permanent AF scheduled for ablation or electro-cardioversion. Image quality analyses were performed by two independent observers. Qualitative assessment was made using the Likert scale; for quantitative analysis, signal to noise ratios (SNR) and contrast to noise ratios (CNR) were calculated for each PV. Heart rate and rhythm were analyzed based on standard 12-lead ECGs. RESULTS: All MTC-BOOST acquisitions achieved diagnostic quality in the PVs, while a significant proportion of T2prep-BOOST images were not suitable for assessing PVs. SNR and CNR values of the MTC-BOOST bright-blood images were higher if patients had sinus rhythm. We found a significant or nearly significant negative correlation between heart rate and the SNR and CNR values of MTC-BOOST bright-blood images. CONCLUSION: 3D whole-heart MTC-BOOST bright-blood imaging is suitable for visualizing the PVs in patients with AF, producing diagnostic image quality in 100% of cases. However, image quality was influenced by heart rate and rhythm. CLINICAL RELEVANCE STATEMENT: The novel 3D whole-heart BOOST CMR sequence needs no contrast administration and is performed during free-breathing; therefore, it is easy to use for a wide range of patients and is suitable for visualizing the PVs in patients with AF. KEY POINTS: • The applicability of the novel 3D whole-heart bright-blood and black-blood phase-sensitive sequence to pulmonary vein imaging in clinical practice is unknown. • Magnetization transfer-bright-blood and black-blood phase-sensitive imaging is suitable for visualizing the pulmonary veins in patients with atrial fibrillation with excellent or good image quality. • Bright-blood and black-blood phase-sensitive cardiac magnetic resonance sequence is easy to use for a wide range of patients as it needs no contrast administration and is performed during free-breathing.

Prioritising quality: investigating the influence of image quality on forensic facial comparison.

Morphological analysis in forensic facial comparison was recently validated for judicial use. However, no image quality assurance systems exist for this purpose, despite image triage being considered the best practice approach. Hence, this study aimed at testing a semi-quantitative scoring method to assess image quality and investigated facial image resolution and lighting quality quantitatively in a context of forensic facial comparison. For this purpose, 400 facial comparison photographic and CCTV image pools developed from the Wits Face Database were used. These facial images were analysed in prior studies that investigated the validity of morphological analysis. A semi-quantitative image quality scoring system was adapted and tested on the above sample and compared across correct and incorrect matches obtained as part of previous studies using a logistic regression model. In addition, facial images were cropped to the closest pixel comprising the face, head and neck areas; then, a face-to-image pixel proportion was calculated as an estimator of resolution quality; and pixel exposure qualities were obtained to be compared to facial comparison outcomes. Ideal and high image quality scores were related to correctness of matches, while low-quality scores were related to incorrect matches. High pixel proportions were related to true matches and low exposure was related to false positives, while high exposure was related to false negatives. These results suggest that an easy method for image triage could be employed by scoring image quality. Quantitative measures should be investigated further for thresholding quality suitability for confidence of facial comparisons.

Imaging of intracranial hemorrhage in photon counting computed tomography using virtual monoenergetic images.

PURPOSE: To determine the optimal virtual monoenergetic image (VMI) for detecting and assessing intracranial hemorrhage in unenhanced photon counting CT of the head based on the evaluation of quantitative and qualitative image quality parameters. METHODS: Sixty-three patients with acute intracranial hemorrhage and unenhanced CT of the head were retrospectively included. In these patients, 35 intraparenchymal, 39 intraventricular, 30 subarachnoidal, and 43 subdural hemorrhages were selected. VMIs were reconstructed using all available monoenergetic reconstruction levels (40-190 keV). Multiple regions of interest measurements were used for evaluation of the overall image quality, and signal, noise, signal-to-noise-ratio (SNR), and contrast-to-noise-ratio (CNR) of intracranial hemorrhage. Based on the results of the quantitative analysis, specific VMIs were rated by five radiologists on a 5-point Likert scale. RESULTS: Signal, noise, SNR, and CNR differed significantly between different VMIs (p < 0.001). Maximum CNR for intracranial hemorrhage was reached in VMI with keV levels > 120 keV (intraparenchymal 143 keV, intraventricular 164 keV, subarachnoidal 124 keV, and subdural hemorrhage 133 keV). In reading, no relevant superiority in the detection of hemorrhage could be demonstrated using VMIs above 66 keV. CONCLUSION: For the detection of hemorrhage in unenhanced CT of the head, the quantitative analysis of the present study on photon counting CT is generally consistent with the findings from dual-energy CT, suggesting keV levels just above 120 keV and higher depending on the location of the hemorrhage. However, on the basis of the qualitative analyses, no reliable statement can yet be made as to whether an additional VMI with higher keV is truly beneficial in everyday clinical practice.

On-eye centration of soft contact lenses.

PURPOSE: To evaluate the relative positions of modern soft contact lenses (SCLs) relative to the limbus/cornea and the pupil. METHODS: Sixty images of the anterior eyes of 101 subjects were acquired over 10 s while participants fixated the centre of the camera lens located 33 cm in front of the eye in a well-lit (300 lux) clinic. Custom validated image analysis software was used to locate the boundaries of the contact lenses, pupils and corneas (limbus). Horizontal and vertical relative positions of the contact lens, pupil and limbus were calculated from the fitted boundaries. RESULTS: The mean (standard deviation) pupil and corneal diameters for all subjects were 3.84 mm, (0.83) and 11.97 mm (0.48), respectively. The mean [95% confidence interval] pupil centre was located 0.28 mm [0.26, 0.30] nasally and 0.07 mm [0.05, 0.10] superiorly to the corneal centre. Consistent with clinical observations, the contact lenses centred accurately relative to the corneal centre both nasally 0.04 mm [0.01, 0.07] and inferiorly -0.01 mm [-0.06, 0.03]. However, regardless of the eye, the contact lens was significantly (p < 0.001) decentred relative to the pupil centre both temporally -0.23 mm [-0.26, -0.20] and inferiorly -0.08 mm [-0.12, -0.04]. Decentration magnitudes were significantly correlated between the right and left eyes. CONCLUSIONS: Spherical SCLs centred well on the cornea but temporally and inferiorly from the primary line of sight (pupil centre), due to the differences in the location of the pupil and corneal centres. Contrary to some previous reports, there was no evidence that lens optics or material affected lens centration significantly.

Image quality assessment in low-dose COVID-19 chest CT examinations.

BACKGROUND: Low-dose thoracic protocols were developed massively during the COVID-19 outbreak. PURPOSE: To study the impact on image quality (IQ) and the diagnosis reliability of COVID-19 low-dose chest computed tomography (CT) protocols. MATERIAL AND METHODS: COVID-19 low-dose protocols were implemented on third- and second-generation CT scanners considering two body mass index (BMI) subgroups (<25 kg/m2 and >25 kg/m2). Contrast-to-noise ratios (CNR) were compared with a Catphan phantom. Next, two radiologists retrospectively assessed IQ for 243 CT patients using a 5-point Linkert scale for general IQ and diagnostic criteria. Kappa score and Wilcoxon rank sum tests were used to compare IQ score and CTDIvol between radiologists, protocols, and scanner models. RESULTS: In vitro analysis of Catphan inserts showed in majority significantly decreased CNR for the low dose versus standard acquisition protocols on both CT scanners. However, in vivo, there was no impact on the diagnosis: sensitivity and specificity were ≥0.8 for all protocols and CT scanners. The third-generation scanner involved a significantly lower dose compared to the second-generation scanner (CTDIvol of 1.8 vs. 2.6 mGy for BMI <25 kg/m2 and 3.3 vs. 4.6 mGy for BMI >25 kg/m2). Still, the third-generation scanner showed a significantly higher IQ with the low-dose protocol compared to the second-generation scanner (30.9 vs. 28.1 for BMI <25 kg/m2 and 29.9 vs. 27.8 for BMI >25 kg/m2). Finally, the two radiologists had good global inter-reader agreement (kappa ≥0.6) for general IQ. CONCLUSION: Low-dose protocols provided sufficient IQ independently of BMI subgroups and CT models without any impact on diagnosis reliability.

Synergizing photon-counting CT with deep learning: potential enhancements in medical imaging.

This review article highlights the potential of integrating photon-counting computed tomography (CT) and deep learning algorithms in medical imaging to enhance diagnostic accuracy, improve image quality, and reduce radiation exposure. The use of photon-counting CT provides superior image quality, reduced radiation dose, and material decomposition capabilities, while deep learning algorithms excel in automating image analysis and improving diagnostic accuracy. The integration of these technologies can lead to enhanced material decomposition and classification, spectral image analysis, predictive modeling for individualized medicine, workflow optimization, and radiation dose management. However, data requirements, computational resources, and regulatory and ethical concerns remain challenges that need to be addressed to fully realize the potential of this technology. The fusion of photon-counting CT and deep learning algorithms is poised to revolutionize medical imaging and transform patient care.

CT angiography of the lower limbs: combining small field of view with large matrix size and iterative reconstruction further improves image quality of below-the-knee arteries.

BACKGROUND: Image quality and diagnostic accuracy in computed tomography angiography (CTA) reach their limits in imaging of below-the-knee vessels. PURPOSE: To evaluate whether image quality in CTA of lower limbs is further improvable by combining side-separate reconstruction with a larger matrix size and whether resulting noise can be compromised with iterative reconstruction (IR). MATERIAL AND METHODS: From CTA of the lower extremities of 26 patients (5 women, 21 men; mean age = 68.5 ± 10.3 years), the lower legs were reconstructed side-separately with different reconstruction algorithms and matrix sizes including filtered back projection (FBP) with a 512 × 512 matrix, FBP with a 1024 × 1024 matrix, IR (SAFIRE) with a 512 × 512 matrix, and IR (SAFIRE) with a 1024 × 1024 matrix. A total of 208 CT series were evaluated. Subjective image quality was assessed by two readers using a 5-point Likert scale. Image noise was assessed by measuring signal-to-noise and contrast-to-noise ratios. RESULTS: Subjective image quality was rated significantly higher when using a 1024 × 1024 matrix (P < 0.001) and could further be increased with IR. Vessel sharpness was rated significantly better with a larger matrix (P < 0.001). Visible and measured image noise was significantly higher with a 1024 × 1024 matrix but could be reduced by using IR (P < 0.001), even to a level below FBP with a 512 × 512 matrix while reconstructing with a larger matrix (P < 0.001). CONCLUSION: Image quality, image noise, and vessel sharpness can be further improved in CTA of the lower extremities with side-separate reconstruction using a 1024 × 1024 matrix size and IR.

Multi-average high-acceleration modified volumetric interpolated breath-hold examination (VIBE) for free-breathing multiphase contrast-enhanced liver MRI: a comparative study with breath-hold VIBE.

BACKGROUND: Breath-hold volumetric interpolated breath-hold examination (BH-VIBE) of multiphase contrast-enhanced liver magnetic resonance imaging (MPCE-LMRI) requires good cooperative individuals to comply with multiple breath-holds. PURPOSE: To develop a free-breathing modified VIBE (FB-mVIBE) as a substitute of BH-VIBE in MPCE-LMRI. MATERIAL AND METHODS: We modified VIBE with a high acceleration factor (2 × 2) and four averages to produce the mVIBE scan. A total of 90 individuals (40 men; mean age = 54.6 ± 10.0 years) who had received MPCE-LMRI as part of a voluntary health check-up for oncology survey were enrolled. Each participant was scanned in four phases (pre-contrast, arterial phase, venous phase, and delay phase), and each phase had two sequential scans. To encounter the timing effect of contrast enhancement, three scan orders were designed: BH-VIBE and FB-mVIBE (group A, n = 30); BH-VIBE and FB-VIBE (group B, n = 30); and FB-mVIBE and BH-VIBE (group C, n = 30). The comparisons included the objective measurements and 25 visual-score by two abdominal radiologists independently. RESULTS: Consistency between raters was observed for all three sequences (intraclass correlation coefficient [ICC] = 0.741-0.829). For rater 1, the mean scores of FB-mVIBE (23.67 ± 1.32) were equal to those of BH-VIBE (23.83 ± 1.98) in groups C and B (P = 0.852). The mean scores of FB-mVIBE (22.07 ± 3.02), but significantly higher than those of FB-VIBE (14.7 ± 3.41) in groups A and B (P <0.001). Similar scores were found for rater 2. The objective measurement of FB-mVIBE were equal to or higher than BH-VIBE and markedly superior to FB-VIBE. CONCLUSION: FB-mVIBE is a practical alternative to BH-VIBE for individuals who cannot cooperate with multiple breath-holds for MPCE-LMRI.