Scan Time Research Articles

Use of Ultra-Short Echo Time MRI to Improve Temporal Bone Imaging.

The short T2 nature of cortical bone causes it to appear similar to air on MR, forcing clinicians to rely on computed tomography imaging, with its attendant ionizing radiation exposure, to define temporal bone structures. Through the use of novel MR sequences with ultra-short echo times (UTE), short T2 structures are now able to be visualized, allowing for improved understanding of anatomical relationships. Eight patients (50% female) undergoing MR imaging of the skull base for diagnostic purposes (62.5% for vestibular schwannoma surveillance) at a tertiary care center were enrolled to evaluate the safety and efficacy of UTE imaging. CT scans were completed in 37.5% of the patients as part of their workup and used for comparison purposes. The repetition time, short echo time, and long echo time for the UTE sequence were 11, 0.032, and 2.2 msec, respectively. The protocol added 6 min to the total scanning time, and all patients tolerated the sequence without issue. The ossicles, mastoid air cells, antrum, and epitympanum were able to be seen and had a high Dice similarity coefficient when compared to CT (>0.5). UTE allowed for clear delineation of all segments of the facial nerve with a signal-to-noise ratio of 35 (although the BRAVO sequences had a superior ratio of 140). Vestibular schwannomas were able to be distinguished from normal brain parenchyma. UTE is safe and effective for visualizing anatomic structures not normally seen on traditional MRI, potentially allowing for improved surgical planning in patients. 3 Laryngoscope, 134:4691-4696, 2024.

Computed tomography-based radiological gynecomastia in SBMA as an independent differential diagnostic biomarker: a retrospective study.

Spinal bulbar muscular atrophy (SBMA) and amyotrophic lateral sclerosis (ALS) are motor neuron disorders that demonstrate overlapping clinical features, especially in the early stage. Therefore, the aim of this study was to investigate the utility of chest tomography (CT) imaging in distinguishing between SBMA and ALS. This was a retrospective study reviewing CT images from patients with SBMA and sporadic ALS and those in the control group. The CT images were assessed to measure the diameter and morphology of glandular tissue associated with gynecomastia. We compared CT-measured gynecomastia between the SBMA, ALS, and control groups. Additionally, correlation analyses were performed between the quantitative measurements of gynecomastia obtained from CT scans and various clinical/laboratory parameter in the SBMA group. 15 chest CT images were collected from SBMA, 41 from ALS, and 29 from control group. No statistical differences were observed in BMI, functional scales, or age at the time of CT scans between the SBMA and ALS groups. Despite similar functional scales and age in both groups, the mean glandular tissue diameter of breast tissue observed in chest CT imaging differed significantly between SBMA, ALS, and controls: 32.22 ± 12.57mm, 15.91 ± 4.81mm, and 15.76 ± 7.26mm, respectively. This disparity allowed for the differentiation of SBMA from ALS and controls with statistical significance. Clinical gynecomastia was 80%, while radiological gynecomastia was 93.3% in SBMA. A significantly higher prevalence of diffuse glandular morphology pattern in SBMA (50%) was observed, contrasting with the predominance of nodular morphology in ALS and controls (9.1% and 20%). Correlative analysis between glandular tissue diameter and other clinical/laboratory parameters within the SBMA group showed no specific finding. CT-based radiological gynecomastia effectively differentiated SBMA from ALS. These findings support the usefulness of radiological gynecomastia as a potential differential diagnostic marker for SBMA, especially in the early stages.

Predictive coding compressive sensing optical coherence tomography hardware implementation

Compressed sensing (CS) is an approach that enables comprehensive imaging by reducing both imaging time and data density, and is a theory that enables undersampling far below the Nyquist sampling rate and guarantees high-accuracy image recovery. Prior efforts in the literature have focused on demonstrations of synthetic undersampling and reconstructions enabled by compressed sensing. In this paper, we demonstrate the first physical, hardware-based sub-Nyquist sampling with a galvanometer-based OCT system with subsequent reconstruction enabled by compressed sensing. Acquired images of a variety of samples, with volume scanning time reduced by 89% (12.5% compression rate), were successfully reconstructed with relative error (RE) of less than 20% and mean square error (MSE) of around 1%.

Non-contrast-enhanced MR-angiography of the abdominal arteries: intraindividual comparison between relaxation-enhanced angiography without contrast and triggering (REACT) and 4D contrast-enhanced MR-angiography.

To evaluate Relaxation-Enhanced Angiography without Contrast and Triggering (REACT), a novel 3D isotropic flow-independent non-contrast-enhanced magnetic resonance angiography (non-CE-MRA) for imaging of the abdominal arteries, by comparing image quality and assessment of vessel stenosis intraindidually with 4D CE-MRA. Thirty patients (mean age 35.7 ± 16.8years; 20 females) referred for the assessment of the arterial abdominal vasculature at 3T were included in this retrospective, single-centre study. The protocol comprised both 4D CE-MRA and REACT (navigator-triggering, Compressed SENSE factor 10, nominal scan time 02:54min, and reconstructed voxel size 0.78 × 0.78 × 0.85 mm3). Two radiologists independently evaluated 14 abdominal artery segments for stenoses, anatomical variants, and vascular findings (aortic dissection, abdominal aorta aneurysms and its branches). Subjective image quality was assessed using a 4-point Likert scale (1 = non-diagnostic, 4 = excellent). REACT had a total acquisition time of 5:36 ± 00:40min, while 4D CE-MRA showed a total acquisition time (including the native scan and bolus tracking sequence) of 3:45 ± 00:59min (p = 0.001). Considering 4D CE-MRA as the reference standard, REACT achieved a sensitivity of 87.5% and specificity of 100.0% for relevant (≥ 50%) stenosis while detecting 89.5% of all vascular findings other than stenosis. For all vessels combined, subjective vessel quality was slightly higher in 4D CE-MRA (3.0 [IQR: 2.0; 4.0.]; P = 0.040), although comparable to REACT (3.0 [IQR: 2.0; 3.5]). In a short scan time of about 5min, REACT provides good diagnostic performance for detection of relevant stenoses, variants, and vascular findings of the abdominal arteries, while yielding to 4D CE-MRA comparable image quality.

ANALYSIS-ASSOCIATED FACTORS INTERFERING WITH DIFFUSION TENSOR INDICES OF PERIPHERAL NERVES

Diffusion tensor imaging (DTI) enables a non-invasive assessment of tissue architecture based on water diffusion. Advancements in technology have expanded the application of DTI from the central nervous system to the peripheral nervous system. High-resolution magnetic resonance imaging (MRI) systems have further enhanced the visualization of nerve compartments. This study investigates the influence of region of interest (ROI) selection on DTI indices in ex vivoperipheral nerves. Cadaveric median nerves (n=10) were harvested and immersed in fluorinated-carbon liquid, and 9-mm segments were independently scanned with a 9.4-T MRI system (scanning time 40 h). Diffusion-weighted signals were summed, and diffusion tensors were calculated for anatomical compartments using different delineation techniques. Following the initial scan, five samples were scanned for the second time using an identical protocol. The analysis showed that the inclusion of an inert background into the ROI significantly reduces fractional anisotropy (FA). Significant differences in diffusion tensors were observed between the initial and intermediate nerve portions, with FA and mean diffusivity (MD) differing by as much as 25.2% and 25.6%, respectively. Tracing the fascicles without the interfascicular epineurium exhibited an 8.8% lower FA compared to the delineations of the epineurium. Second MRI scans showed significant changes in diffusion tensors with higher eigenvalues D1-D3 and MD. In conclusion, the intermediate portions of the nerve demonstrated greater consistency in DTI indices and are therefore recommended for analysis over the initial portions. Using an inert liquid can minimize background effects, but the inherent diffusion properties of the tissue must be carefully considered. Prolonged scanning times can alter diffusion tensors, likely due to autolytic processes, underscoring the importance of consistent pre-scanning conditions and acquisition protocols. Additionally, maintaining consistency in delineations is paramount, regardless of whether the tracing method includes or excludes the interfascicular epineurium.

High physical activity relates to higher risk of incident carotid plaque components

Abstract Background The rupture of carotid atherosclerotic plaque, primarily driven by plaque components, is among the leading causes of ischemic stroke. Although physical activity (PA) stands as a major modifiable target for prevention of atherosclerotic diseases, recent studies suggested a potential adverse impact of high-volume PA on atherosclerotic plaque burden in athletes. Data remains scarce from the community-dwelling population regarding to the impact of PA on the longitudinal change of carotid plaque components. Objectives To assess the association between PA and the incidence of carotid plaque components and explore whether the association of PA with stroke and all-cause mortality differs by the presence of plaque components. Methods Between 2007 and 2012, in a community- dwelling cohort in Netherlands, 1327 stroke-free persons (mean ± standard deviation age 72 ± 9 years, 45% women) with carotid atherosclerosis (carotid intima-media thickness > 2.5 mm) were invited for magnetic resonance imaging (MRI) to assess carotid plaque components. From these, 696 persons (1267 carotid arteries) underwent a follow-up MRI between 2014 and 2017 (median between-scan interval 6 years). Carotid plaque components included calcification, intraplaque hemorrhage (IPH), and lipid-rich necrotic core (LRNC). The volume of moderate, vigorous and total PA (unit: metabolic equivalent task hour, MET-h) was assessed using LASA Physical Activity Questionnaires around the time of the first MRI scan. Participants were followed for the occurrence of stroke or all-cause mortality until December 31, 2019. Generalized estimation equation and Cox regression models were used in the analyses, with adjustments for plaque size and other cardiovascular risk factors. Results Compared to lowest quintile PA group, participants in the highest quintile total PA group had a higher risk of new onset of plaque components, odds ratio (95%CI) 2.69 (1.21; 5.94) for calcification, 1.35 (0.82; 2.24) for LRNC and 1.93 (1.12; 3.34) for IPH (Figure 1). Similar associations were observed for vigorous PA but not for moderate PA. Over a median follow-up of 9.5 years, 118 persons suffered a stroke and 298 died. As shown in table 1, baseline IPH, rather than LRNC or calcification, modulated the associations of PA with stroke and all-cause mortality (P-interaction <0.05): higher total PA was associated with a lower risk of stroke among IPH-free persons, with the hazard ratio (95% CI) of 0.929 (0.867; 0.996) per 10 MET-h/week increase; no associations between PA and stroke were found among those with IPH. Similar associations were found between vigorous PA and all-cause mortality. Conclusions Among the middle-aged and elderly with subclinical atherosclerosis, high level PA, especially high vigorous PA, may lead to an unstable carotid plaque. The beneficial effect of PA on stroke and all-cause mortality is only among persons with a stable carotid plaque profile, especially without IPH.

High prevalence of coronary artery calcium and aortic calcification in adults with repaired coarctation of the aorta and interrupted aortic arch

Abstract Background There is a high rate of late cardiovascular mortality in patients with repaired coarctation of the aorta (CoA) and interrupted aortic arch (IAA). Coronary artery calcium (CAC) is a marker of cardiovascular disease and there is growing evidence for aortic calcification as a predictor. Recent research in the general population suggests any CAC in males <35 years old and females ≤45 years places them at ≥90th percentile. Aims We aimed (1) to determine the prevalence of CAC, thoracic aorta calcification (TAC), and abdominal aorta calcification (AAC) in patients with CoA or IAA repair, and (2) to compare patients to a control group of Tetralogy of Fallot (TOF) patients, a condition with no known increased risk of atherosclerotic cardiovascular disease. Methods Retrospective cohort study of adult survivors of CoA/IAA repair followed up at an adult congenital heart disease (ACHD) clinic. Patients with at least 1 chest, abdomen, or pelvis computerised tomography (CT) scan for any indication were included. The presence/absence of calcification in the coronary arteries or aorta was assessed qualitatively. Patients on antihypertensive and statin therapy were considered hypertensive and hypercholesterolaemic, respectively. Patients were compared to adult survivors of TOF repair with CT scans for any indication (controls). Results Ninety-three CoA/IAA patients (87% CoA/13% IAA, median age at latest follow-up 34 years) had a total of 169 chest and 37 abdomen/pelvis CTs; 82, 93, and 37 patients had at least 1 CT suitable for CAC, TAC, and AAC review, respectively. CAC was present in 22% (18/82), TAC in 33% (31/93), and AAC in 23% (5/22) of CoA/IAA patients. CAC was present in 12% (18/153) and TAC in 11% (18/158) of TOF patients. CoA/IAA patients were more likely to have CAC and TAC than TOF patients (p=0.04 and p<0.0001; respectively) and be younger at the time of diagnosis (CAC p=0.03, TAC p=0.0001) despite TOF patients being older at time of latest CT scan (p=0.0003) (Table 1). Males aged <35 years and females ≤45 years represented 44% (8/18) of CoA/IAA patients with CAC. CoA/IAA patients with CAC were more likely to be hypertensive and hypercholesterolaemic than those without (78% [14/18] vs 48% [31/64], p=0.03; and 28% [5/18] vs 0% [0/64], p<0.0001; respectively) and was similar for TAC (hypertension p=0.005, hypercholesterolaemia p=0.04) but not AAC. After a mean follow-up of 11±7 years from first ACHD clinic, of the 93 patients, 2 patients died, 5 had coronary artery disease (at least mild stenosis on invasive angiography), 3 had a stroke, and 70% (65/93) were considered hypertensive at latest follow-up. Conclusions There is a high prevalence of CAC, aortic calcification, and hypertension in young adults with repaired CoA/IAA. Coronary and thoracic aortic calcification occurs at a younger age compared to controls. Further studies are warranted to assess the impact of aggressive cardiovascular risk reduction in this high-risk group.

Sodium MRI of the skin using a surface coil to investigate and reduce signal loss and bias.

The purpose was to improve sodium MRI of human skin using a surface coil and twisted projection imaging with smaller, reshaped voxels. Calf skin sodium images were acquired in 14 healthy adults using twisted projection imaging with short TE ˜ 0.1 ms, first with a volume coil and voxels (1.5 × 1.5 × 15 = 34 mm3) reflecting the widely adopted skin imaging protocol (VolPencil). A 5-cm-diameter surface coil then facilitated 5× smaller (0.8 × 0.8 × 10 = 6.4 mm3) voxels with similar signal to noise ratio (SNR) in the same 12-min scan time (SurfPencil). "Pencil-shaped" voxels were then replaced with "pancake-shaped" (0.4 × 4 × 4 = 6.4 mm3) voxels, matching the anatomy of pressed flat skin (SurfPancake). Surface coil B1 was investigated with the novel use of spin-3/2 simulation. Protocol modifications were tested for signal increase (reduced loss) and correlation with (bias by) skin thickness. Higher resolution SurfPencil yielded 44% ± 16% greater skin sodium image intensity than VolPencil, whereas SurfPancake yielded an additional 20% ± 9% (p < 1e-8), reflecting reduced signal loss. Over the 1.0 to 1.8 mm skin thickness across participants, sodium intensity significantly increased 56% ± 19% and 44% ± 12% for VolPencil and SurfPencil, respectively (p < 0.003), but not for SurfPancake, reflecting reduced bias. Imaging yielded skin sodium concentration of 34 ± 5 mM for SurfPancake. This is greater than the ˜20 mM measures from the widely adopted protocol, but simulation (matching experimental trends) identified a remaining 64% signal loss; compensation yields 95 ± 15 mM. Surface coil imaging and "pancake" voxel reshaping increased skin sodium intensity and reduced bias by skin thickness. Simulated loss compensation yields skin sodium concentration similar to that measured by atomic absorption spectroscopy.

A Multi-Hierarchical Complementary Feature Interaction Network for Accelerated Multi-Modal MR Imaging

Magnetic resonance (MR) imaging is widely used in the clinical field due to its non-invasiveness, but the long scanning time is still a bottleneck for its popularization. Using the complementary information between multi-modal imaging to accelerate imaging provides a novel and effective MR fast imaging solution. However, previous technologies mostly use simple fusion methods and fail to fully utilize their potential sharable knowledge. In this study, we introduced a novel multi-hierarchical complementary feature interaction network (MHCFIN) to realize joint reconstruction of multi-modal MR images with undersampled data and thus accelerate multi-modal imaging. Firstly, multiple attention mechanisms are integrated with a dual-branch encoder–decoder network to represent shared features and complementary features of different modalities. In the decoding stage, the multi-modal feature interaction module (MMFIM) acts as a bridge between the two branches, realizing complementary knowledge transfer between different modalities through cross-level fusion. The single-modal feature fusion module (SMFFM) carries out multi-scale feature representation and optimization of the single modality, preserving better anatomical details. Extensive experiments are conducted under different sampling patterns and acceleration factors. The results show that this proposed method achieves obvious improvement compared with existing state-of-the-art reconstruction methods in both visual quality and quantity.

Association of borderline fetal growth with progression to fetal growth restriction.

To evaluate if an estimated fetal weight (EFW) between the 10-15th percentiles at time of anatomy ultrasound, referred to as borderline fetal growth, is associated with progression to fetal growth restriction (FGR) on subsequent ultrasound, delivery of a SGA neonate or neonatal intensive care (NICU) admission. We performed a secondary analysis using the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be data (NuMom2b). The exposures were normotensive pregnancies with non-anomalous singleton gestations with normal growth, defined as EFW >15th percentile at the anatomy scan compared to borderline fetal growth fetuses defined as those with an EFW in the 10-15th percentile. The primary outcome was FGR at subsequent ultrasound, defined as EFW or AC <10%. The secondary outcomes were NICU admission and small for gestational age (SGA) neonate. Univariable analyses were performed comparing maternal baseline demographic and clinical characteristics. Multivariable analysis was performed for the primary outcome with variables adjusted a priori for body mass index, smoking status, race/ethnicity, insurance status, and drug use. 4883 patients met inclusion criteria with 114 in the borderline fetal growth group and 4769 in the normal growth group. There were no significant differences in maternal demographic or medical characteristics (Table 1). In adjusted multivariable analysis, patients with borderline growth had significantly higher odds of being diagnosed with FGR at their subsequent scan (aOR 6.68, CI 3.98-11.20) compared to those with normal growth. For secondary outcomes, patients with borderline fetal growth were significantly more likely to have SGA neonates (6.14% vs. 2.67%, p= 0.025). There was no difference in admissions to the NICU between groups. Diagnosis of borderline fetal growth at time of anatomy scan was associated with a significantly increased odds of progression to FGR at subsequent scan and delivery of a SGA neonate.

G.O.O.S.E.: Introducing a novel five‐stage structured framework for the early phases of teaching and learning ultrasound

AbstractThe sonography profession faces a critical global workforce shortage, particularly pronounced in Australia, due to insufficient clinical training opportunities and an ageing workforce. The financial burden and increased scan times associated with training exacerbate this issue. Innovative approaches, such as intensive ultrasound courses and pair scanning protocols, have shown promise in addressing these challenges. The GOOSE framework (Get the window, Optimise the view, Optimise the image, Select the image, Explain the findings) offers a structured, step‐by‐step approach to practical sonography training. This framework deconstructs complex ultrasound skills into manageable tasks, optimises cognitive load management, and provides explicit guidance for novice learners. The GOOSE framework is designed to enhance the efficiency of teaching and learning by simplifying complex skills into clear, actionable steps, supported by checklists that guide both instructors and students through the training process. The GOOSE framework offers a systematisation of knowledge transfer that, combined with deliberate practice and structured feedback, ensures learners progressively build their skills with focused, goal‐directed activities. While this model is yet to be validated, initial implementations have shown promising results in improving trainee performance, reducing supervision workload, and standardising instructional methods. This article outlines the principles of the GOOSE framework, its development, and its application in a specialised training facility, proposing it as a standardised model to enhance practical ultrasound education and improve teaching and learning efficiency.

Are muscle and fat loss predictive of clinical events in pancreatic cancer? The importance of precision metrics

BackgroundMuscle and fat loss from cancer may have prognostic significance. Skeletal muscle and fat areas measured at L3 on a CT scan correlate with body muscle and fat mass. We wished to know if reduced skeletal muscle area or fat on diagnostic CT scans or changes from initial CT scans in patients with pancreatic cancer who died in 2018 and 2019 predicted mortality. MethodeEectronic records of 112 patients with locally advanced or metastatic pancreatic cancer were used to extract stage, age, gender, comorbidities, weight, and height at the time of the first CT scan. Survival (in days) was defined from the first CT scan to the death date. Patients had at least one CT scan of the abdomen. I. Two trained medical students read scans independently using TeraRecon software (Durham, NC). Results were averaged, and the differences determined precision. Interclass correlation coefficient (ICC), coefficient of variation, and least significant change determined the precision between readers. Independent prognostic modeling included age and BMI. ResultsAn evaluable sample of 104 with an average age of 67, 56 were male. Nearly half had a TNM Stage of IV (45%). The average Charlson Comorbidity index is 7.2. In those undergoing repeat scans, most were in the timeframe of 60-120 days. Changes in visceral fat in men in the unadjusted Cox proportional hazard model and reduced skeletal muscle area in the age-adjusted model of men predicted mortality. In contrast, myosteatosis in women marginally predicted improved survival. ICC's precision between readers was adequate but by least significant change would have missed subtle, clinically important changes. DiscussionMuscle loss during chemotherapy in men predicted mortality in men but not women. Precision is an important metric when measuring body composition. ConclusionMuscle loss in men during chemotherapy of pancreatic cancer predicts mortality.

Contribution of an Artificial Intelligence Tool in the Detection of Incidental Pulmonary Embolism on Oncology Assessment Scans

Introduction: The incidence of venous thromboembolism is estimated to be around 3% of cancer patients. However, a majority of incidental pulmonary embolism (iPE) can be overlooked by radiologists in asymptomatic patients, performing CT scans for disease surveillance, which may significantly impact the patient’s health and management. Routine imaging in oncology is usually reviewed with delayed hours after the acquisition of images. Nevertheless, the advent of AI in radiology could reduce the risk of the diagnostic delay of iPE by an optimal triage immediately at the acquisition console. This study aimed to determine the accuracy rate of an AI algorithm (CINA-iPE) in detecting iPE and the duration until the management of cancer patients in our center, in addition to describing the characteristics of patients with a confirmed pulmonary embolism (PE). Materials and Methods: This is a retrospective analysis of the role of Avicenna’s CE-certified and FDA-cleared CINA-iPE algorithm in oncology patients treated at Gustave Roussy Cancer Campus. The results obtained from the AI algorithm were compared with the attending radiologist’s report and were analyzed by both a radiology resident and a senior radiologist. In case of any discordant results, the reason for this discrepancy was further investigated. The duration between the exact time of the CT scan and analysis was assessed, as well as the duration from the result’s report and the start of active management. Results: Out of 3047 patients, 104 alerts were detected for iPE (prevalence of 1.3%), while 2942 had negative findings. In total, 36 of the 104 patients had confirmed PE, while 68 alerts were false positives. Only one patient reported as negative by the AI tool was deemed to have a PE by the radiologist. The sensitivity and specificity of the AI model were 97.3% and 97.74%, while the PPV and NPV were 34.62% and 99.97%, respectively. Most causes of FP were artifacts (22 cases, 32.3%) and lymph nodes (11 cases, 16.2%). Seven patients experienced delayed diagnosis, requiring them to return to the ER for treatment after being sent home following their scan. The remaining patients received prompt care immediately after their testing, with a mean delay time of 8.13 h. Conclusions: The addition of an AI system for the detection of unsuspected PEs on chest CT scans in routine oncology care demonstrated a promising efficacy in comparison to human performance. Despite a low prevalence, the sensitivity and specificity of the AI tool reached 97.3% and 97.7%, respectively, with detection of all the reported clinical PEs, except one single case. This study describes the potential synergy between AI and radiologists for an optimal diagnosis of iPE in routine clinical cancer care. Clinical relevance statement: In the oncology field, iPEs are common, with an increased risk of morbidity when missed with a delayed diagnosis. With the assistance of a reliable AI tool, the radiologist can focus on the challenging analysis of oncology results while dealing with urgent diagnosis such as PE by sending the patient straight to the ER (Emergency Room) for prompt treatment.

Functional Localization of the Human Auditory and Visual Thalamus Using a Thalamic Localizer Functional Magnetic Resonance Imaging Task

Abstract Functional magnetic resonance imaging (fMRI) of the auditory and visual sensory systems of the human brain is an active area of investigation in the study of human health and disease. The medial geniculate nucleus (MGN) and lateral geniculate nucleus (LGN) are key thalamic nuclei involved in the processing and relay of auditory and visual information, respectively, and are the subject of blood-oxygen-level-dependent (BOLD) fMRI studies of neural activation and functional connectivity in human participants. However, localization of BOLD fMRI signal originating from neural activity in MGN and LGN remains a technical challenge, due in part to the poor definition of boundaries of these thalamic nuclei in standard T1-weighted and T2-weighted magnetic resonance imaging sequences. Here, we report the development and evaluation of an auditory and visual sensory thalamic localizer (TL) fMRI task that produces participant-specific functionally-defined regions of interest (fROIs) of both MGN and LGN, using 3 Tesla multiband fMRI and a clustered-sparse temporal acquisition sequence, in less than 16 minutes of scan time. We demonstrate the use of MGN and LGN fROIs obtained from the TL fMRI task in standard resting-state functional connectivity (RSFC) fMRI analyses in the same participants. In RSFC analyses, we validated the specificity of MGN and LGN fROIs for signals obtained from primary auditory and visual cortex, respectively, and benchmark their performance against alternative atlas- and segmentation-based localization methods. The TL fMRI task and analysis code (written in Presentation and MATLAB, respectively) have been made freely available to the wider research community.

Dynamic sequential cross-sectional scanning increases detection rate of congenital heart disease in sonographers: a prenatal ultrasound training program

BackgroundPrenatal ultrasound is the preferred modality for diagnosing fetal congenital heart disease. Given issues of physician proficiency and hospital distribution, we propose a dynamic sequential cross-sectional scanning (SCS) to explore the feasibility of cardiac screening by sonographers with less than 5 years of experience in ultrasound.Materials and methodsTwenty residents were randomly divided into two groups, receiving training in the American Institute of Ultrasound in Medicine (AIUM) fetal echocardiography and the SCS method. According to the needs of training, the professional staff developed the theoretical knowledge question bank, the CHD ultrasonic video disease bank, and the assessment scale. Trainees completed the pre-training examination, theory and skill operation training, and post-training assessment. For the two groups, the theoretical knowledge, skill operation and disease diagnosis were analyzed statistically before and after training.ResultsAfter training, the trainees in both groups had significantly improved knowledge and diagnostic abilities, their diagnostic thinking about CHD was clear, and they could identify major or even all structural abnormalities and make a definite diagnosis. In terms of skill operation, both groups could complete all required scanning within the specified time. The scanning time of the SCS group was significantly lower than that of the AIUM group, and the effect of the receptor site in the AIUM group was significantly higher than that in the SCS group.ConclusionSCS can be used as a new rapid fetal cardiac scanning method and try to popularize among echocardiographer.

Routine Transvaginal Ultrasound at the Time of the Anatomy Scan: To Do or Not To Do?

There are no universal guidelines for transvaginal ultrasound (TVUS) at the time of the anatomy scan. TVUS can provide information on placental location and cervical length (CL) but may lead to more interventions. As a quality assurance initiative, a universal TVUS (UTVUS) protocol at the time of the anatomy scan was started at our institution. This study was conducted to assess whether there was a decrease in preterm birth (PTB), postpartum hemorrhage (PPH), and neonatal intensive care unit (NICU) admission once UTVUS was implemented. This was a retrospective cohort study performed on singleton gestations from February 2021 to January 2022. In the first 6 months of the study period, patients only had TVUS based on risk factors (pre group). In the second half of the study period, UTVUS was implemented at the time of the anatomy scan (post group). A total of 2,118 patients were included in the study. There were 1,037 patients in the pre group, of which 161 underwent TVUS based on high-risk factors (history of the cervical procedure, history of prior PTB, and placenta appearing low lying or cervix appearing short on abdominal ultrasound). The post group/UTVUS included 1,081 patients. Patients in the pre group had statistically significantly earlier gestational age at first TVUS (p < 0.0001), were less likely to have had a prior PTB <36 weeks (p = 0.03), and were more likely to have a history of cervical procedure (p = 0.0006) than patients in the post group. There was an increased use of vaginal progesterone in the UTVUS with 33 patients (as opposed to 10 patients in the pre group; p = 0.0007). The proportion of patients with PTB, PPH, or NICU admission did not significantly differ between the two groups even after adjusting for cofounders (p > 0.05). Our data show that UTVUS did not decrease the adverse pregnancy outcomes. In addition, the implementation of UTVUS adds more discomfort for a patient, more time to the patient's scan, and is an additional cost. Therefore, surveillance by abdominal ultrasound and adding TVUS based on risk factors may be a reasonable alternative. · UTVUS showed no difference between CLs.. · There is not sufficient evidence to conclude a difference between PTB or PPH in the two groups.. · There was significantly more placenta previa diagnosed in the post group, yet most resolved..

Comprehensive assessment of imaging quality of artificial intelligence-assisted compressed sensing-based MR images in routine clinical settings

BackgroundConventional MR acceleration techniques, such as compressed sensing, parallel imaging, and half Fourier often face limitations, including noise amplification, reduced signal-to-noise ratio (SNR) and increased susceptibility to artifacts, which can compromise image quality, especially in high-speed acquisitions. Artificial intelligence (AI)-assisted compressed sensing (ACS) has emerged as a novel approach that combines the conventional techniques with advanced AI algorithms. The objective of this study was to examine the imaging quality of the ACS approach by qualitative and quantitative analysis for brain, spine, kidney, liver, and knee MR imaging, as well as compare the performance of this method with conventional (non-ACS) MR imaging.MethodsThis study included 50 subjects. Three radiologists independently assessed the quality of MR images based on artefacts, image sharpness, overall image quality and diagnostic efficacy. SNR, contrast-to-noise ratio (CNR), edge content (EC), enhancement measure (EME), scanning time were used for quantitative evaluation. The Cohen’s kappa correlation coefficient (k) was employed to measure radiologists’ inter-observer agreement, and the Mann Whitney U-test used for comparison between non-ACS and ACS.ResultsThe qualitative analysis of three radiologists demonstrated that ACS images showed superior clinical information than non-ACS images with a mean k of ~ 0.70. The images acquired with ACS approach showed statistically higher values (p < 0.05) for SNR, CNR, EC, and EME compared to the non-ACS images. Furthermore, the study’s findings indicated that ACS-enabled images reduced scan time by more than 50% while maintaining high imaging quality.ConclusionIntegrating ACS technology into routine clinical settings has the potential to speed up image acquisition, improve image quality, and enhance diagnostic procedures and patient throughput.

Accelerated cardiac cine with spatio-coil regularized deep learning reconstruction.

To develop an iterative deep learning (DL) reconstruction with spatio-coil regularization and multichannel k-space data consistency for accelerated cine imaging. This study proposes a Spatio-Coil Regularized DL (SCR-DL) approach for iterative deep learning reconstruction incorporating multicoil information in data consistency and regularizer. SCR-DL uses shift-invariant convolutional kernels to interpolate missing k-space lines and reconstruct individual coil images, followed by a regularizer that operates simultaneously across spatial and coil dimensions using learned image priors. At 8-fold acceleration, SCR-DL was compared with Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA), sensitivity encoding (SENSE)-based DL and spatio-temporal regularized (STR)-DL reconstruction. In the retrospective undersampled cine, images were quantitatively evaluated using normalized mean square error (NMSE) and structural similarity index measure (SSIM). Additionally, agreement for left-ventricular ejection fraction and left-ventricular mass were assessed using prospectively accelerated cine images at 2-fold and 8-fold accelerations. The SCR-DL algorithm successfully reconstructed highly accelerated cine images. SCR-DL had significant improvements in NMSE (0.03 ± 0.02) and SSIM (91.4% ± 2.7%) compared with GRAPPA (NMSE: 0.09 ± 0.04, SSIM: 69.9% ± 11.1%; p < 0.001), SENSE-DL (NMSE: 0.07 ± 0.04, SSIM: 86.9% ± 3.2%; p < 0.001), and STR-DL (NMSE: 0.04 ± 0.03, SSIM: 90.0% ± 2.5%; p < 0.001) with retrospective undersampled cine. Despite the 3-fold reduction in scan time, there was no difference between left-ventricular ejection fraction (59.8 ± 4.5 vs. 60.8 ± 4.8, p = 0.46) or left-ventricular mass (73.6 ± 19.4 g vs. 73.2 ± 19.7 g, p = 0.95) between R = 2 and R = 8 prospectively accelerated cine images. SCR-DL enabled highly accelerated cardiac cine imaging, significantly reducing breath-hold time. Compared with GRAPPA or SENSE-DL, images reconstructed with SCR-DL showed superior NMSE and SSIM.

Deep learning reconstruction of diffusion-weighted brain MRI for evaluation of patients with acute neurologic symptoms

Purpose: We aimed to evaluate whether the deep-learning (DL) accelerated diffusion weighted image (DWI) is clinically feasible for evaluating patients with acute neurologic symptoms, regarding its shorter study time and acceptable image quality. Materials and methods: In this retrospective study, brain images obtained at DWI with a b-value of 0 s/mm2 and DWI with a b-value of 1000 s/mm2 (DWI 1000) from 321 consecutive patients with acute stroke-like symptom were reconstructed with and without DL algorithm. We compare the diagnostic performance between DL-DWI and conventional DWI for detecting brain lesions, including acute infarction. We assessed the diagnostic accuracy of conventional DWI and DL-DWI and compared the results. Qualitative analysis based on image quality was assessed and compared using a five-point visual scoring system. Apparent diffusion coefficients (ADCs) from DWI with and without DL were also compared. Results: The mean acquisition time for the DL-DWI (49 s) was significantly shorter (P < 0.001) than conventional DWI (165 s). Both DWI with and without DL showed similar performance in diagnosing brain lesions especially sensitivity (98.8% in both DWI and DL-DWI) and specificity (99.5% in both DWI and DL-DWI). Overall image quality, gray-white matter and deep gray matter differentiation of two sequences were similar. DL DWI showed more artifacts than DWI. Lesion conspicuity, especially smaller than 5 mm, was better with DL DWI than conventional DWI (p = 0.03). ADC values of white matter, deep gray matter, and pons with DL were lower than conventional DWI. Conclusions: Compared to conventional DWI, DL-DWI achieved comparable image quality and brain lesion visualization for acute neurological symptoms, with a significantly shorter scan time.

Enhancing amide proton transfer imaging in ischemic stroke using a machine learning approach with partially synthetic data.

Amide proton transfer (APT) imaging, a technique sensitive to tissue pH, holds promise in the diagnosis of ischemic stroke. Achieving accurate and rapid APT imaging is crucial for this application. However, conventional APT quantification methods either lack accuracy or are time-consuming. Machine learning (ML) has recently been recognized as a potential solution to improve APT quantification. In this paper, we applied an ML model trained on a new type of partially synthetic data, along with an optimization approach utilizing recursive feature elimination, to predict APT imaging in an animal stroke model. This partially synthetic datum is not a simple blend of measured and simulated chemical exchange saturation transfer (CEST) signals. Rather, it integrates the underlying components including all CEST, direct water saturation, and magnetization transfer effects partly derived from measurements and simulations to reconstruct the CEST signals using an inverse summation relationship. Training with partially synthetic data requires less in vivo data compared to training entirely with fully synthetic or in vivo data, making it a more practical approach. Since this type of data closely resembles real tissue, it leads to more accurate predictions than ML models trained on fully synthetic data. Results indicate that an ML model trained on this partially synthetic data can successfully predict the APT effect with enhanced accuracy, providing significant contrast between stroke lesions and normal tissues, thus clearly delineating lesions. In contrast, conventional quantification methods such as the asymmetric analysis method, three-point method, and multiple-pool model Lorentzian fit showed inadequate accuracy in quantifying the APT effect. Moreover, ML methods trained using in vivo data and fully synthetic data exhibited poor predictive performance due to insufficient training data and inaccurate simulation pool settings or parameter ranges, respectively. Following optimization, only 13 frequency offsets were selected from the initial 69, resulting in significantly reduced scan time.