OBJECTIVES:This study aimed (1) to quantify the differential impact of deep learning (DL) reconstruction on brachial plexus (BP) diffusion tensor imaging (DTI) image quality and quantitative metrics compared with conventional single-shot echo-planar imaging (EPI), (2) to clarify the clinical utility and limitations of integrating simultaneous multislice (SMS) acceleration with DL DTI in the challenging BP anatomy, and (3) to determine the optimal, time-efficient DTI protocol for robust BP tractography. MATERIALS AND METHODS:Twenty-seven healthy volunteers were prospectively enrolled (stage 1: n = 14; stage 2: n = 13). All DTI acquisitions used a single-shot EPI sequence. In the first stage, DTI with DL reconstruction was compared with a conventional non-DL DTI. In the second stage, the integration of SMS acceleration into DL DTI protocols was assessed across 5 protocol sets. Fiber tract number, tract length, tract-based DTI metrics, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), image consistency, and interreader agreement were assessed in the BP postganglionic nerve roots and spinal cord. RESULTS:In the first stage, DL DTI demonstrated significantly higher tractography success rates, fiber numbers, and fiber lengths in the BP (P < 0.05). DL substantially improved interreader agreement and image consistency, with the Dice similarity coefficient (DSC) increasing from 0.537 to 0.740 (P = 0.006). DL reconstruction resulted in changes in anatomy-specific fractional anisotropy, with a significant decrease in BP fractional anisotropy but an increase in spinal cord fractional anisotropy. In the second stage, SMS-integrated protocols produced significantly lower tractography success and degraded image quality compared with non-SMS DL protocols (P < 0.05). SMS integration resulted in lower SNR and CNR (P < 0.05), and reduced image consistency (DSC decreased from 0.727 to 0.486, P = 0.015). The DL12-2 protocol (12 diffusion directions and two b800 acquisitions) was identified as the optimal time-efficient solution. CONCLUSIONS:DL reconstruction significantly improves the feasibility and reliability of BP DTI and affects quantitative metrics in an anatomy-specific manner. In contrast, the integration of SMS acceleration with single-shot EPI remains technically challenging in the high-susceptibility BP region. Our findings underscore that anatomy-specific optimization is essential for successful clinical integration of DL-enhanced DTI.
Objectives: This study aimed (1) to quantify the differential impact of deep learning (DL) reconstruction on brachial plexus (BP) diffusion tensor imaging (DTI) image quality and quantitative metrics compared with conventional single-shot echo-planar imaging (EPI), (2) to clarify the clinical utility and limitations of integrating simultaneous multislice (SMS) acceleration with DL DTI in the challenging BP anatomy, and (3) to determine the optimal, time-efficient DTI protocol for robust BP tractography. Materials and Methods: Twenty-seven healthy volunteers were prospectively enrolled (stage 1: n = 14; stage 2: n = 13). All DTI acquisitions used a single-shot EPI sequence. In the first stage, DTI with DL reconstruction was compared with a conventional non-DL DTI. In the second stage, the integration of SMS acceleration into DL DTI protocols was assessed across 5 protocol sets. Fiber tract number, tract length, tract-based DTI metrics, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), image consistency, and interreader agreement were assessed in the BP postganglionic nerve roots and spinal cord. Results: In the first stage, DL DTI demonstrated significantly higher tractography success rates, fiber numbers, and fiber lengths in the BP ( P < 0.05). DL substantially improved interreader agreement and image consistency, with the Dice similarity coefficient (DSC) increasing from 0.537 to 0.740 ( P = 0.006). DL reconstruction resulted in changes in anatomy-specific fractional anisotropy, with a significant decrease in BP fractional anisotropy but an increase in spinal cord fractional anisotropy. In the second stage, SMS-integrated protocols produced significantly lower tractography success and degraded image quality compared with non-SMS DL protocols ( P < 0.05). SMS integration resulted in lower SNR and CNR ( P < 0.05), and reduced image consistency (DSC decreased from 0.727 to 0.486, P = 0.015). The DL12-2 protocol (12 diffusion directions and two b800 acquisitions) was identified as the optimal time-efficient solution. Conclusions: DL reconstruction significantly improves the feasibility and reliability of BP DTI and affects quantitative metrics in an anatomy-specific manner. In contrast, the integration of SMS acceleration with single-shot EPI remains technically challenging in the high-susceptibility BP region. Our findings underscore that anatomy-specific optimization is essential for successful clinical integration of DL-enhanced DTI.
Background: With modern CT technology offering faster acquisition, lower radiation exposure, higher resolution, and advanced detector designs, routine image interpretation still relies largely on gray‑scale windowing, which by design requires frequent manual adjustment. Existing color mappings rely on uniform mathematical gradients and offer no clear advantage over gray‑scale display for tissue or structure perception. Objective: To develop and evaluate a software framework supporting interactive exploration of perception‑based color mapping. Materials and Methods: A custom research DICOM viewer enabling interactive nonuniform color display was developed. Verification included a contrast‑agent dilution series compared with a clinical viewer and liver phantom CT scans with predefined lesions acquired at varying dose levels and reconstruction settings. Differentiation of tissues and structures in the liver phantom was examined by visual rating after application of different color mappings. Results: Quantitative verification using a contrast-agent dilution series confirmed correct mapping of CT values to color. In a phantom-based reader evaluation using liver phantom CT scans, nonuniform color mapping produced stable visual representations and was significantly preferred in subjective visual analysis. Conclusions: Unlike uniform color mappings, the proposed approach uses nonuniform color ranges to better match human perception. In CT, this may facilitate visual separation of tissues and structures and was preferred in phantom‑based visual assessment compared with standard uniform display methods.
CT image quality is strongly influenced by the energy of the x-ray beam. The tube voltage (kV) determines a polyenergetic x-ray spectrum, which affects both image contrast and noise in conventional energy-integrating detector CT (EID-CT) imaging. In photon-counting detector CT (PCD-CT), spectral data sets are always available by default, and virtual monoenergetic images (VMI) can be reconstructed at any specific photon energy (keV). This enables radiologists to tailor energy selection to dedicated clinical tasks, achieving an optimal balance between contrast, noise, and radiation dose, and ultimately enhancing diagnostic confidence. This article educates the reader on the differences between polyenergetic and monoenergetic images to provide radiologists with practical insights into optimizing spectral imaging protocols and leveraging keV differences in routine clinical practice. Using an anthropomorphic phantom with iodine rods, differences in image quality, specifically image contrast and noise, are demonstrated between polyenergetic EID-CT and PCD-CT VMIs.
Objective: To evaluate the impact of tin-filtered photon-counting detector (PCD) computed tomography (CT) in combination with high-energy virtual monoenergetic imaging (VMI) and iterative metal artifact reduction (iMAR) on metal artifact reduction, image quality, and assessment of intragraft and extragraft bone fusion, in patients after anterior cervical discectomy and fusion (ACDF). Materials and Methods: Patients who underwent ACDF and postoperative tin-filtered PCD-CT between 2023 and 2026 were retrospectively analyzed. Metal artifacts were quantitatively and qualitatively assessed in standard polychromatic (T3D), iMAR (T3D iMAR ), VMI at 120 keV (VMI 120 ), and combined VMI 120 + iMAR (VMI 120+iMAR ) reconstructions. Quantitative analysis included measurement of hypodense and hyperdense artifact attenuation and corrected noise. Three musculoskeletal radiologists independently scored 5 imaging features on 4-point Likert scales and assessed the presence of secondary artifacts. Subgroup analyses were performed for polyetheretherketone (PEEK)-tantalum versus titanium cages and for 140 versus 100 kVp acquisitions. Results: Forty-four patients (23 with PEEK-tantalum cages, 21 with titanium cages) were included. VMI 120+iMAR achieved the strongest metal artifact reduction with hypodense artifacts from −362.5 Hounsfield Units (HU) to −38 HU and hyperdense artifacts from 218.5 to 83.5 HU, as well as significant noise improvements compared with T3D (all P <0.001); effects were most pronounced near titanium cages. T3D iMAR provided comparable artifact reduction to VMI 120+iMAR in PEEK-tantalum cages ( P =0.55 to 0.83) but inferior artifact reduction in titanium cages ( P <0.001). Bone-metal interface conspicuity improved significantly with VMI 120 and VMI 120+iMAR ( P ≤0.01). Intragraft and extragraft bone fusion visibility was rated highest with standard T3D images (median 3 to 4), whereas the most pronounced impairments were observed for VMI 120+iMAR (median 2 to 3, P ≤0.01). iMAR-based techniques introduced secondary artifacts, including pseudo-osteolysis (20.5% to 38.6%), and white zone artifacts (50% to 56.8%), while dark zone and silhouette artifacts were less common (4.5% to 6.8%). White zone artifacts were significantly more frequent at 140 versus 100 kVp ( P <0.05), while dark zone and silhouette artifacts were exclusively observed at 100 kVp. Inter-reader agreement was substantial to almost perfect (κ=0.62 to 0.94). Conclusions: Tin-filtered PCD-CT with VMI 120+iMAR offers the most effective metal artifact reduction after ACDF and improves bone-metal interface conspicuity, particularly near titanium cages, followed by T3D iMAR . However, these advanced reconstructions may impair diagnostic accuracy for bone fusion assessment due to reconstruction-induced artifacts. iMAR-based reconstructions introduced pseudo-osteolysis that may simulate pseudoarthrosis, as well as white zone artifacts that may mimic false bony bridging in a material-dependent and kVp-dependent manner. Therefore, a reconstruction-specific approach is recommended for the clinical evaluation of ACDF patients, balancing metal artifact reduction against diagnostic reliability for bone fusion.
Quantitative synthetic MRI (SyMRI) enables simultaneous acquisition of quantitative T1, T2, and proton density maps and retrospective generation of multiple contrast-weighted images from a single acquisition. By moving beyond conventional qualitative MRI, SyMRI may improve workflow efficiency while providing objective tissue biomarkers. Although most extensively studied in neuroimaging, its application to body MRI has expanded rapidly. This narrative review summarizes the technical basis of body SyMRI, focusing on the predominant 2-dimensional QRAPMASTER/multidynamic multiecho (MDME) framework and the newer 3-dimensional quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (QALAS) approach, and discusses current evidence across breast, prostate, gynecologic, rectal, head and neck, and musculoskeletal imaging. Available studies indicate that SyMRI is technically feasible across these applications and shows promise for lesion characterization, tumor grading, prognostic assessment, treatment-response evaluation, and quantitative analysis of normal and diseased tissues. In several settings, SyMRI-derived parameters provide additional value when combined with diffusion-weighted imaging, dynamic contrast-enhanced MRI, clinicopathologic variables, histogram analysis, radiomics, and predictive modeling. However, current evidence remains limited by small, single-center, and methodologically heterogeneous studies, and most body applications still rely on two-dimensional implementations. Future progress will depend on multicenter prospective validation, standardization of quantitative workflows, and broader evaluation of newer three-dimensional methods.
Objectives: The purpose of this phantom study in human plasma was to characterize the signal enhancement properties of gadoquatrane under clinically relevant, highly standardized conditions in comparison to gadobutrol. Gadoquatrane is a novel high-relaxivity, extracellular macrocyclic gadolinium-based contrast agent (GBCA) currently in clinical development at a dose of 0.01 mmol/kg body weight (corresponding to 0.04 mmol Gd/kg). Materials and Methods: Three GBCA-dilution series in human plasma were prepared: 2 series with equimolar Gd concentrations (0-10 mmol Gd/mL) for gadoquatrane (0.4 mol Gd/L) and gadobutrol (1.0 mol Gd/L), and 1 series with 60% lower Gd concentrations for gadoquatrane (12 samples/series). For each series, signal intensity versus Gd concentration profiles were obtained using standard T1-weighted MRI pulse sequences at 1.5 T. In addition, the impact of sequence parameters was investigated (repetition and echo time for spin-echo sequences; flip angle for gradient-echo sequences). Results: The signal enhancement achieved with the 2 GBCAs depended on the Gd concentration and the pulse sequence. For all sequences tested, almost superimposable signal intensity profiles were found for gadobutrol and gadoquatrane, with 60% lower Gd concentrations for gadoquatrane. Sequence parameter variations affected both GBCAs in the same way. The optimal flip angles were equal for gadobutrol and gadoquatrane (60% reduced). Conclusions: The signal intensity profiles obtained in human plasma using standard clinical pulse sequences were almost superimposable for gadobutrol and gadoquatrane at 60% lower Gd concentrations. For clinical use, this means that the same pulse sequence parameters can be used for both GBCAs and that, essentially, the same signal enhancement can be expected from gadoquatrane at a dose of 0.04 mmol Gd/kg body weight as from gadobutrol at a dose of 0.1 mmol Gd/kg.
OBJECTIVE:To evaluate the potential of combined coherent and incoherent undersampling with deep learning (DL) reconstruction for highly accelerated high-resolution three-dimensional (3D) double-echo steady-state (DESS) MRI of the cervical nerves and rootlets at 7T. METHODS:In this prospective study, asymptomatic volunteers underwent 7T MRI of the cervical spine. A high-resolution, 3D DESS sequence (reconstructed voxel size 0.35 mm³ isotropic) with regular 2-fold GRAPPA undersampling served as reference. The sequence was repeated with coherent CAIPIRINHA undersampling alone and combined CAIPIRINHA + incoherent compressed sensing (CS)-based undersampling with DL reconstruction and varying acceleration factors (DL-CAIPIRINHA: R=2 to 12 and DL-CS-CAIPI: R=4 to 16), while all other imaging parameters remained constant. Two fellowship-trained musculoskeletal radiologists assessed image quality, noise, reconstruction and motion artifacts, and edge sharpness of the spinal cord, intradural rootlets/roots, and exiting spinal nerves, including dorsal root ganglia (DRGs), using 5-point Likert scales, with higher scores indicating better image quality or fewer artifacts. Statistics included Friedman and post hoc Wilcoxon signed-rank tests (Benjamini-Hochberg corrected) and κ statistics. RESULTS:Thirty-two volunteers (mean age 30.9±7.2 y; mean BMI 23.4±2.8 kg/m²; 16 females) were included. Image quality significantly improved with 2- and 4-fold DL-CAIPIRINHA (means 4.4 to 4.6) and 4- and 8-fold DL-CS-CAIPI (3.8 to 3.9) compared with GRAPPA (3.2; all P<0.001), and remained comparable with 12-fold DL-CS-CAIPI (P=0.42) despite more than 6-fold reduction in scan time. All DL-based reconstructions reduced noise (P<0.001). Reconstruction artifacts were more pronounced for 12-fold DL-CAIPIRINHA (1.6) than for 12- and 16-fold DL-CS-CAIPI (3.1 to 3.3; P<0.001). Motion artifacts decreased with acceleration factors ≥4 (P<0.001). Sharpness of the spinal cord, intraspinal rootlets/roots, and DRGs was highest with 4-fold DL-CAIPIRINHA (4.2 to 4.7) vs. GRAPPA (2.9 to 3.2; P<0.001). Inter-reader agreement was almost perfect across all imaging features (κ=0.85 to 0.95). CONCLUSIONS:Coherent CAIPIRINHA undersampling with DL reconstruction improves image quality over conventional GRAPPA while enabling 50% faster imaging in 7T cervical spine MRI. Adding incoherent CS undersampling permits substantially higher acceleration with preserved image quality and fewer reconstruction artifacts. The novel integration of coherent and incoherent undersampling via combined CAIPIRINHA and CS with DL reconstruction provides a robust framework for preserving image quality at acceleration factors beyond 8, enabling efficient high-resolution cervical spine MRI with scan time reductions exceeding 6-fold.
RATIONALE AND OBJECTIVES:Dual-source photon-counting CT (DS-PCCT) combines spectral imaging with ultra-high spatial resolution for whole-body assessment of multiple myeloma (MM). This study assessed axial and appendicular skeletal manifestations at initial diagnosis by exploiting attenuation characteristics of soft tissue and fat in low-keV virtual monoenergetic images (VMI). MATERIALS AND METHODS:In this retrospective study, 84 patients (67.1±10.5 y, 54 men) underwent whole-body DS-PCCT between November 2024 and December 2025. The sample comprised 53 therapy-naïve MM patients and 31 with precursor conditions (monoclonal gammopathy of undetermined significance, smoldering myeloma, solitary plasmacytoma). Three board-certified radiologists measured CT attenuation of osteolytic lesions and femoral bone marrow at 70 and 40 keV. Long bones were evaluated for diffuse high-grade, nodular, pseudonodular, and fatty marrow patterns, as well as endosteal scalloping. RESULTS:Among 53 MM patients, 40 (75.5%) spectral-morphologic analysis identified 3 patient-level imaging phenotypes of osteolytic bone disease: a soft-tissue-attenuation phenotype (n=25, 47.2%), a fat-attenuation phenotype (n=10, 18.9%), and coexistence of both lesion types (n=5, 9.4%). The pseudonodular pattern was the predominant femoral marrow imaging pattern, whereas fatty marrow (30.2%), nodular lesions (18.9%), and diffuse high-grade infiltration (3.8%) occurred less frequently. Endosteal scalloping occurred exclusively in osteolytic MM (18.9%). Precursor conditions mainly showed fatty (58.1%) and pseudonodular (38.7%) patterns. Low-keV VMI demonstrated distinct energy-dependent attenuation across patterns. Inter-reader agreement for Hounsfield unit measurements was good to excellent (ICC >0.82). CONCLUSIONS:DS-PCCT identified a previously undescribed fat-attenuation-predominant imaging phenotype in MM that meets criteria for symptomatic bone disease but is not captured by current International Myeloma Working Group definitions of focal lesions. Spectral-morphologic characterization of marrow involvement may complement existing imaging criteria and aid differentiation between overt MM and nonspecific marrow abnormalities.
OBJECTIVES:Extracellular matrix (ECM) remodeling is a hallmark of tumor progression, yet the longitudinal dynamics of elastin accumulation during prostate cancer (PCa) development remain unknown. This study aimed to longitudinally track elastin remodeling during PCa progression using elastin-specific molecular MRI (ESMA) in an orthotopic mouse model and to characterize the spatial heterogeneity of elastin deposition at the tumor-stroma interface. MATERIALS AND METHODS:Human PC3 prostate cancer cells were orthotopically implanted into the ventral prostate lobe of SCID mice (n=6). Weekly MRIs were performed over 6 weeks at 3.0 Tesla using the gadolinium-based elastin-specific probe ESMA (0.2 mmol/kg intravenous weekly). Signal intensity (SI) was quantified before and after contrast administration. Findings were validated by Elastica-van Gieson staining, immunofluorescence, Western blot analysis, and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) for spatial gadolinium mapping. RESULTS:Postcontrast SI increased progressively from 1517±151 at baseline to 3400±411 at week 6 (2.2-fold increase, P <0.001), with the most pronounced enhancement between weeks 2 and 3. Elastin distribution was spatially heterogeneous: peripheral tumor regions contained significantly more elastin (2.95±1.63%) than central areas (1.00±0.40%, P <0.008), indicating preferential ECM remodeling at the tumor-stroma interface. LA-ICP-MS demonstrated a strong correlation between gadolinium concentration and histologic elastin content ( R2 =0.88, P <0.001), and Western blot detected tropoelastin expression in all tumors. CONCLUSION:ESMA-enhanced molecular MRI captures the longitudinal dynamics of elastin accumulation during PCa progression. Progressive elastin deposition, concentrated at the tumor periphery, is consistent with active ECM remodeling at the invasive front and suggests elastin as a candidate imaging biomarker for monitoring matrix-driven tumor progression.
OBJECTIVES:To evaluate an AI tool for opportunistic osteoporosis screening using chest radiographs (CXRs), focusing on its diagnostic accuracy against dual-energy x-ray absorptiometry (DXA) and associations with long-term risks of fracture and mortality. MATERIALS AND METHODS:This retrospective, external validation study included a health checkup cohort with same-day CXR-DXA pairs and a chronic obstructive pulmonary disease (COPD) cohort with available CXRs. We evaluated a commercialized AI tool (InceptionV3 backbone, trained with 55,600 CXR-DXA pairs) designed to identify osteoporosis from a single frontal CXR. Diagnostic performance was assessed against DXA using the area under the receiver operating characteristic curve (AUC). Associations between AI results and subsequent fractures or all-cause mortality were investigated using multivariable Cox proportional-hazard regression, adjusted for sex, age, low body mass index, and COPD stage. Mediation analyses were conducted to examine whether these associations were mediated by a diagnosis of osteoporosis. RESULTS:In total, 8618 (male-to-female ratio, 2882:5736; mean age, 58 y; median follow-up, 2868 d) and 4941 (male-to-female ratio, 4110:831; mean age, 69 y; median follow-up, 2656 d) patients were included in the health checkup and COPD cohorts, respectively. The AI achieved AUCs of 0.94 (95% CI: 0.93-0.95) and 0.81 (95% CI: 0.76-0.87) for osteoporosis identification in the health checkup and COPD cohorts, respectively. Higher AI-predicted osteoporosis probability was associated with subsequent fracture and mortality in both cohorts ( Ps <0.05). Mediation analyses showed that indirect effects of AI scores on fracture or mortality mediated through DXA-defined or clinically diagnosed osteoporosis were not significant ( P s>0.05), suggesting that AI may identify fracture risk in individuals not yet clinically diagnosed with osteoporosis. CONCLUSIONS:AI could identify osteoporosis from chest radiographs, and AI results were associated with subsequent fracture and mortality.
Objectives: To evaluate an AI tool for opportunistic osteoporosis screening using chest radiographs (CXRs), focusing on its diagnostic accuracy against dual-energy x-ray absorptiometry (DXA) and associations with long-term risks of fracture and mortality. Materials and Methods: This retrospective, external validation study included a health checkup cohort with same-day CXR-DXA pairs and a chronic obstructive pulmonary disease (COPD) cohort with available CXRs. We evaluated a commercialized AI tool (InceptionV3 backbone, trained with 55,600 CXR-DXA pairs) designed to identify osteoporosis from a single frontal CXR. Diagnostic performance was assessed against DXA using the area under the receiver operating characteristic curve (AUC). Associations between AI results and subsequent fractures or all-cause mortality were investigated using multivariable Cox proportional-hazard regression, adjusted for sex, age, low body mass index, and COPD stage. Mediation analyses were conducted to examine whether these associations were mediated by a diagnosis of osteoporosis. Results: In total, 8618 (male-to-female ratio, 2882:5736; mean age, 58 y; median follow-up, 2868 d) and 4941 (male-to-female ratio, 4110:831; mean age, 69 y; median follow-up, 2656 d) patients were included in the health checkup and COPD cohorts, respectively. The AI achieved AUCs of 0.94 (95% CI: 0.93-0.95) and 0.81 (95% CI: 0.76-0.87) for osteoporosis identification in the health checkup and COPD cohorts, respectively. Higher AI-predicted osteoporosis probability was associated with subsequent fracture and mortality in both cohorts ( Ps <0.05). Mediation analyses showed that indirect effects of AI scores on fracture or mortality mediated through DXA-defined or clinically diagnosed osteoporosis were not significant ( P s>0.05), suggesting that AI may identify fracture risk in individuals not yet clinically diagnosed with osteoporosis. Conclusions: AI could identify osteoporosis from chest radiographs, and AI results were associated with subsequent fracture and mortality.
OBJECTIVES:Deep-learning (DL)-accelerated MRI can significantly reduce acquisition times. Studies evaluating interchangeability with conventional 3D data sets, particularly for monitoring disease activity in multiple sclerosis (MS), are lacking. This study investigated interchangeability and comparability between conventional fluid-attenuated 3D-T2-SPACE dark-fluid (c-3D-T2) and accelerated DL-based fluid-attenuated 3D-T2-SPACE dark-fluid (DL-3D-T2) in detecting new white matter lesions lesions on brain MRIs. MATERIALS AND METHODS:In this prospective study, 94 patients with confirmed MS (n=77) or suspected chronic inflammatory CNS disease (n=17), underwent clinically indicated brain MRI at 1.5T. Each participant underwent both c-3D-T2 (5:01 min) and DL-3D-T2 (2:48 min) imaging. Primary endpoint was interchangeability of both sequences for detecting new white matter lesions defined according to the 2024 revised McDonald criteria. Furthermore, comparability regarding total lesion count and image quality was evaluated. Lesions were assessed in 3 anatomic regions (periventricular, cortical/juxtacortical, and infratentorial) by 3 independent readers and 1 experienced neuroradiologist using an established, certified lesion-detection software. Equivalence margin for interchangeability was predefined at 5%. Gwet's AC1 and AC2 determined inter-reader reliability. RESULTS:The study comprised of 70 women and 24 men, with a mean age of 44.9 years (range: 24 to 72 y). In 73 patients, a comparable prior examination was available and met the technical requirements for AI-based lesion-detection software. In 13 patients new lesions were confirmed. Interchangeability for the primary endpoint was demonstrated for all readers and the experienced neuroradiologist, using certified lesion-detection software. Individual equivalence indices remained within the 5% margin. Detection of new white matter lesions demonstrated almost perfect inter-method agreement with overall Gwet's AC2 values between 0.85 [0.74; 0.96] and 0.98 [0.95; 1.00], and excellent inter-reader reliability, with overall new lesions of 0.85 [0.76; 0.94]. Total number of infratentorial and periventricular lesions demonstrated almost perfect agreement [(≥0.93 (0.91; 0.96)] and good agreement for cortical/juxtacortical lesions [0.71 (0.65; 0.77)]. Subjective analysis revealed that 2 readers rated c-3D-T2 as significantly superior in image quality (P<0.001) and 1 reader rated c-3D-T2 as significantly superior in diagnostic confidence (P=0.003). CONCLUSIONS:DL-accelerated 3D-T2-weighted imaging is interchangeable with conventional 3D imaging for detecting new white matter lesions, while reducing acquisition time by nearly 50%. This acceleration supports more efficient MRI protocols for routine MS surveillance, enabling inclusion of additional advanced sequences. However, as subjective image evaluation was slightly inferior in DL-accelerated data sets, and given the substantial time savings, it may be reasonable to slightly reduce the acceleration factor to enhance image quality.
OBJECTIVES:The optic nerve sheath expands with elevated intracranial pressure, and its diameter is a sensitive proxy measure. While 2D transorbital ultrasound is well-established for detecting elevated intracranial pressure (>20 mm Hg), it shows limited sensitivity to modest or gradual changes, potentially due to geometric assumptions and imaging misalignment. This study introduces freehand 3D ultrasound imaging of the optic nerve sheath to reduce measurement ambiguity and enhance the fidelity of optic nerve sheath assessment as a noninvasive marker of intracranial pressure. MATERIALS AND METHODS:Twelve healthy participants (28.7 ± 8.2 y; 6 females) underwent freehand 3D optic nerve sheath imaging during 24 hours of normobaric hypoxia in an environmental chamber (FiO2 = 13.1%). Scans were acquired in a head-raised (30 degrees) position at baseline, 6, 12, and 24 hours. Cardiorespiratory parameters, cerebral blood flow, and end-tidal gases were recorded. In 6 participants, postural effects were also assessed at baseline. Nutrition and hydration were standardized to 75% of daily requirements. RESULTS:The optic nerve sheath's curved, noncircular shape makes the 2D diameter measurement of the sheath a geometric mismatch and an inadequate descriptor. Probe misalignments of 1.2 mm or 15 degrees led to 2D diameter errors (9%/18.7%) exceeding observer variability (2.6%/3.4%). Freehand 3D imaging was reproducible and yielded more informative metrics, including sheath area and thickness. Internal sheath thickness was more responsive to posture and hypoxia than internal 2D diameter (+31.5%, P = 0.01 vs +2.4%, P = 0.9; +8.2%, P = 0.04 vs +1.8%, P = 0.9). A time effect was observed for internal sheath thickness (P = 0.04), and both area and thickness correlated with internal carotid artery velocity (area: r = 0.9, P = 0.05; thickness: r = 0.8, P = 0.07), consistent with physiological expectations. CONCLUSION:By eliminating geometric assumptions and misalignment, freehand 3D ultrasound improves the fidelity and sensitivity of optic nerve sheath measurements at the bedside.
Metallic implants can cause relevant artifacts in computed tomography (CT) imaging, affecting the quality and diagnostic utility of scans. Previous advancements in metal artifact reduction techniques have shown promise but still exhibit limitations in artifact reduction, particularly close to metal implants. To evaluate a novel, advanced iterative metal artifact reduction (iMAR) algorithm for photon-counting detector CT in an experimental study focused on visualizing the vicinity of a fixation nail implant. Three bovine femur bones with titanium-based trochanteric fixation nail implants were scanned on a clinical photon-counting detector CT scanner. Images were reconstructed (1) without iMAR, (2) with the current iMAR algorithm, and (3) with a new prototype iMAR algorithm. The new iMAR prototype algorithm advances state-of-the-art iMAR for photon-counting detector CT by utilizing intrinsically available spectral information. Attenuation and artifact severity (SD of attenuation) were quantified by placing regions-of-interest on each reconstruction across 3 different axial slices: One in the bone marrow immediately adjacent to the metal implant and one in the water adjacent to the femur with the implant. Qualitative image quality, newly introduced artifacts, and diagnostic confidence were rated by 3 radiologists using 5-point Likert scales. Differences between reconstructions were tested using the Friedman test with Wilcoxon post hoc tests; interreader agreement was assessed using Krippendorff alpha. Artifact severity in the bone adjacent to the implant significantly decreased from 226 HU (no iMAR) to 174 HU (current iMAR) and to 159 HU with the new iMAR ( P < 0.001). Adjacent to the femur, artifact severity decreased from 63 HU to 48 HU and to 29 HU, respectively ( P < 0.05). Qualitative scores differed significantly between reconstructions ( P < 0.05), with highest ratings for new iMAR across all categories. Current iMAR introduced new artifacts near the implant, which did not occur with new iMAR ( P < 0.05). Experimental evidence from a bovine femur implant model suggests that a new, advanced iterative metal artifact reduction algorithm leveraging intrinsic spectral information from photon-counting detector CT effectively reduces metal artifacts and further improves the visualization of the metal-bone interface. Thus, this technique has the potential to enhance the assessment of implant-related complications such as aseptic loosening.
Previous research has highlighted the benefits of reducing contrast media (CM), demonstrating positive impacts on patient safety, environmental sustainability, and health care costs. The 10-to-10 rule, introduced by a single-center study, adjusts CM dose to total body weight and tube voltage. This approach resulted in a reduced overall CM volume, with homogeneous attenuation and consistent diagnostic image quality (IQ) across varying tube voltages. This study aimed to evaluate the effectiveness of the 10-to-10 rule in achieving consistent and homogeneous attenuation in vascular and parenchymal CT in a multicenter clinical practice setting across Europe. A total of 1,037 patients scheduled for CT of the coronary arteries (high-pitch and sequential CCTA), pulmonary arteries (CTPA), aorta (CTA aorta), and abdominal CT in portal venous phase or venous phase scans of the neck were included in this nonrandomized multicenter trial, conducted at 5 centers in the Netherlands, Germany, and Switzerland. Each center followed its standard scan and reconstruction protocol based on the clinical request. CM protocols were based on the 10-to-10 rule: A 10 kV reduction in tube voltage should be accompanied by a 10% decrease in iodine delivery rate for vascular studies or total iodine load in parenchymal studies, and vice versa. Objective image quality (IQ) was assessed by drawing region of interests, measuring attenuation [Hounsfield Unit (HU)], and calculating signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). In vascular studies, a reference line was included, representing the threshold for sufficient diagnostic IQ (CCTA—325 HU, CTPA—200 HU, and CTA Aorta—250 HU). 95% CI of the mean attenuation was calculated, and the lower bound of each 95% CI was used as the reference to assess whether attenuation met these thresholds. Generalized mixed models tested for significant differences in objective IQ across varying tube voltages, presented both unadjusted and multivariate adjusted by age and gender. Results demonstrated no significant differences in attenuation for distal high-pitch CCTA, proximal sequential CCTA, distal CTPA, CTA aorta, abdominal portal venous phase scans, and the thyroid gland and sternocleidomastoid muscle in venous phase scans of the neck after adjusting for age and gender. Proximal high-pitch CCTA, distal sequential CCTA, and proximal CTPA yielded significant results ( P =0.030, P <0.001, and P =0.002, respectively). SNR and CNR showed no significant differences for all scan protocols. The majority of 95% CI lower bounds exceeded the predefined threshold for sufficient diagnostic IQ. Exceptions included high-pitch CCTA scans, where only the 90 kV level met the threshold, as well as in sequential CCTA at 120 kV, and CTPA at 110 and 120 kV, for which the lower bounds remained below the threshold. This study demonstrates the generalizability and effectiveness of the 10-to-10 rule in a multicenter trial setting and a large patient population, showing limited significant deviations in iodine attenuation across varying tube voltages for both vascular and parenchymal CT studies.
Objectives: MR neurography (MRN) is a modern technique for visualizing peripheral nerves and quantifying microstructural pathology, yet its use in pediatric populations remains largely unexplored. This study evaluates the applicability and diagnostic performance of MRN in children and adolescents with genetically confirmed long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (LCHADD) and mitochondrial trifunctional protein deficiency (MTPD), in which peripheral neuropathy is a known long-term complication. Materials and Methods: In a prospective cross-sectional study, 15 patients (LCHADD n = 6; MTPD n = 9) and 14 age-matched controls underwent high-resolution mid-thigh MRN of the sciatic nerve to assess (1) T2-based lesion burden for tibial (SN Tib ) and peroneal (SN Per ) fascicles, (2) functional nerve integrity of the tibial fascicles using diffusion tensor metrics, including fractional anisotropy (FA) and radial diffusivity (RD), and (3) tibial fascicle-based T2 relaxometry parameters. In addition, clinical and electrophysiological data were obtained. Age-adjusted linear regression, ROC analyses, and linear discriminant analyses (LDA) quantified group effects and classification performance. Results: Overall, patients showed higher T2 lesion burden compared with controls (SN Tib : +2.75%, P = 0.001; SN Per : +1.94%, P = 0.001), reduced tibial fascicle FA (Δ: -0.098, P = 0.001), and increased tibial fascicle RD (Δ: +147.4×10 -6 mm 2 /s, P = 0.011). Subgroup comparisons between LCHADD and MTPD revealed no significant differences. Of the 15 patients, 7 exhibited signs of clinical neuropathy. Neuropathic individuals showed pronounced abnormalities (SN Tib : +4.22%, P < 0.001; SN Per : +2.29%, P = 0.002; ΔFA: -0.138, P < 0.001), while even those without clinical neuropathy exhibited elevated SN Per lesion burden (+1.64%; P = 0.018) and reduced tibial fascicle FA (Δ: -0.062, P = 0.03), compared with controls, indicating subclinical involvement. SN Tib lesion burden showed excellent discrimination (AUC: 95.2%), and FA performed well (AUC: 81.2%). Multiparametric LDA achieved 93% apparent in-sample accuracy for patients versus controls, 86% for LCHADD versus MTPD, and 90% for classifying neuropathic, non-neuropathic, and control groups. Conclusions: MRN can be readily applied in children and adolescents and sensitively detects both clinically manifest and subclinical peripheral nerve involvement in long-chain fatty acid oxidation disorders. Extending this capability, exploratory LDA suggests that combining multiple MRN metrics may provide complementary diagnostic and phenotypic information beyond individual parameters.
Since the discovery of gadolinium (Gd) in the brain following the administration of gadolinium-based contrast agents (GBCAs), considerable progress has been made in understanding their pharmacokinetics and neurotoxicology. This review summarizes animal studies assessing the presence of Gd after GBCA administration, with a specific focus on functional and behavioral outcomes, rather than providing a comprehensive overview of all aspects of Gd presence in the brain. These findings indicate that Gd accumulation in the brain depends on the chemical structure of GBCAs, with linear agents exhibiting greater retention and slower clearance than macrocyclic agents. Gd distribution is nonhomogeneous, primarily localized in deep gray matter structures, and is influenced by cerebrospinal fluid-mediated transport and perivascular deposition. Although motor and cognitive functions are generally unaffected under normal conditions, prolonged exposure to linear GBCAs or preexisting conditions such as inflammation or metabolic disorders may increase neurotoxic risks, resulting in motor and cognitive deficits. Pain and sensory hypersensitivity are frequently and reproducibly observed, particularly when linear agents are used. We will also discuss the potential mechanisms of neurotoxicity caused by free Gd 3+ ion. However, these mechanistic findings are limited because the studies cannot be extrapolated to clinical practice. Future studies should investigate the potential associations between GBCA exposure and neurodegenerative diseases. These insights are essential for enhancing GBCA safety and informing clinical guidelines.
Objectives: To propose and validate a simplified method for 3D simultaneous post-contrast parametric mapping and synthetic late gadolinium enhancement (LGE) imaging at 0.55T for comprehensive whole-heart myocardial tissue characterization. Materials and Methods: A 3D joint T1/T2 mapping research sequence is adopted from a previous study. Three interleaved volumes with inversion recovery (IR) preparation, no magnetization preparation, and T2 preparation were acquired with image navigators to enable 100% respiratory scan efficiency. Intrinsically co-registered 3D T1, T2, and proton density maps were calculated using a dictionary-matching method, and Bloch equation-based IR and T2 preparation-IR (T2IR) signal models were proposed to generate multi-contrast 3D synthetic LGE images. In vivo evaluation included 10 data sets from a porcine myocardial infarction model to validate the performance of the proposed 3D method in comparison with that of separately scanned 2D reference sequences including post-contrast T1 mapping, pre-contrast T2 mapping, and LGE. Results: For the 10 swine data sets, 2D and 3D T1/T2 maps had consistent findings regarding the changes in T1/T2 values of myocardial infarction, presenting significantly decreased post-contrast T1 (2D: 279±48 vs. 472±44 ms, P <0.01; 3D: 355±32 vs. 597±48 ms, P <0.01) and increased T2 (2D: 102.4±11.5 vs. 66.4±3.1 ms, P <0.01; 3D: 71.0±5.3 vs. 39.4±4.5 ms, P <0.01) in scar compared with remote myocardium. 3D multi-contrast LGE images were successfully generated without additional scan and provided excellent image contrasts. Compared with 2D LGE, 3D synthetic bright-blood IR-LGE had improved scar-to-myocardium contrast ( P <0.01) with comparable image contrasts of scar-to-blood ( P =0.08) and blood-to-myocardium ( P =0.71), synthetic gray-blood IR-LGE had improved scar-to-blood and scar-to-myocardium contrast ( P <0.01) with comparable blood-to-myocardium contrast ( P =0.06), whereas synthetic dark-blood T2IR-LGE demonstrated significant differences regarding all tissue contrasts ( P <0.01). Conclusions: The proposed method provided imaging findings consistent with 2D references and shows promise for comprehensive myocardial tissue characterization in a single simple scan.
Background: Despite the growing number of artificial intelligence (AI)-based applications used in radiology, no structured framework exists to assess their case-level reliability or to document overridden outputs in reports. Purpose: To develop and evaluate the Artificial Intelligence Reporting and Data System (AI-RADS), a structured framework for an objective, case-level assessment of AI output reliability, clinical utility, and recommended actions in radiology. Materials and Methods: The AI-RADS framework was tested in a retrospective, multireader study. Here, 5 board-certified radiologists independently evaluated 350 cases processed by 7 representative AI applications for image-based and generative tasks. Each case was assigned one of 5 AI-RADS categories, applicable modifiers, and an independent correctness rating as a reference. Interreader agreement was quantified using Krippendorff’s α with 95% CIs. Results: Substantial interreader agreement was observed for the core AI-RADS categories in both image-based (Krippendorff’s α=0.87; 95% CI: 0.83-0.91) and generative AI tasks (Krippendorff’s α=0.93; 95% CI: 0.91-0.95). Reader-assigned correctness aligned well with AI-RADS categories 1 to 2, which indicate outputs suitable for integration into clinical workflows. Outputs rated as “incorrect” were predominantly assigned to categories 4 to 5, warranting override or removal from display. Conclusion: AI-RADS provides a structured framework for the case-level evaluation of AI output reliability, clinical utility, and consequences for report communication. This multireader study demonstrated substantial interreader agreement and applicability across various AI applications.
