Investigative Radiology最新文献

Abstract: Interstitial lung disease (ILD) encompasses a variety of lung disorders with varying degrees of inflammation or fibrosis, requiring a combination of clinical, imaging, and pathologic data for evaluation. Imaging is essential for the noninvasive diagnosis of the disease, as well as for assessing disease severity, monitoring its progression, and evaluating treatment response. However, traditional visual assessments of ILD with computed tomography (CT) suffer from reader variability. Automated quantitative CT offers a more objective approach by using computer-based analysis to consistently evaluate and measure ILD. Advancements in technology have significantly improved the accuracy and reliability of these measurements. Recently, interstitial lung abnormalities (ILAs), which represent potential preclinical ILD incidentally found on CT scans and are characterized by abnormalities in over 5% of any lung zone, have gained attention and clinical importance. The challenge lies in the accurate and consistent identification of ILA, given that its definition relies on a subjective threshold, making quantitative tools crucial for precise ILA evaluation. This review highlights the state of CT quantification of ILD and ILA, addressing clinical and research disparities while emphasizing how machine learning or deep learning in quantitative imaging can improve diagnosis and management by providing more accurate assessments, and finally, suggests the future directions of quantitative CT in this area.

Abstract: Artificial intelligence (AI) has made significant advances in radiology. Nonetheless, challenges in AI development, validation, and reproducibility persist, primarily due to the lack of high-quality, large-scale, standardized data across the world. Addressing these challenges requires comprehensive standardization of medical imaging data and seamless integration with structured medical data.Developed by the Observational Health Data Sciences and Informatics community, the OMOP Common Data Model enables large-scale international collaborations with structured medical data. It ensures syntactic and semantic interoperability, while supporting the privacy-protected distribution of research across borders. The recently proposed Medical Imaging Common Data Model is designed to encompass all DICOM-formatted medical imaging data and integrate imaging-derived features with clinical data, ensuring their provenance.The harmonization of medical imaging data and its seamless integration with structured clinical data at a global scale will pave the way for advanced AI research in radiology. This standardization will enable federated learning, ensuring privacy-preserving collaboration across institutions and promoting equitable AI through the inclusion of diverse patient populations. Moreover, it will facilitate the development of foundation models trained on large-scale, multimodal datasets, serving as powerful starting points for specialized AI applications. Objective and transparent algorithm validation on a standardized data infrastructure will enhance reproducibility and interoperability of AI systems, driving innovation and reliability in clinical applications.

Abstract: Local ablation therapy, encompassing radiofrequency ablation (RFA), microwave ablation, and cryoablation, has emerged as a crucial strategy for managing small hepatocellular carcinomas (HCCs), complementing liver resection and transplantation. This review delves into the clinical significance of tumor size, location, and biology in guiding treatment decisions for HCCs undergoing local ablation therapy, with a focus on tumors smaller than 3 cm. Tumor size significantly influences treatment outcomes, with larger tumors associated with poorer local tumor control due to challenges in creating sufficient ablative margins and the likelihood of microvascular invasion and peritumoral satellite nodules. Advanced ablation techniques such as centripetal or no-touch RFA using multiple electrodes, cryoablation using multiple cryoprobes, and microwave ablation offer diverse options for HCC treatment. Notably, no-touch RFA demonstrates superior local tumor control compared with conventional RFA by achieving sufficient ablative margins, making it particularly promising for hepatic dome lesions or tumors with aggressive biology. Laparoscopic RFA proves beneficial for treating anterior subphrenic HCCs, whereas artificial pleural effusion-assisted RFA is effective for controlling posterior subphrenic HCCs. However, surgical resection generally offers better survival outcomes for periportal HCCs compared with RFA. Cryoablation exhibits a lower incidence of vascular or biliary complications than RFA for HCCs adjacent to perivascular or periductal regions. Additionally, aggressive tumor biology, such as microvascular invasion, can be predicted using magnetic resonance imaging findings and serum tumor markers. Aggressive HCC subtypes frequently exhibit Liver Imaging Reporting and Data System M features on magnetic resonance imaging, aiding in prognosis. A comprehensive understanding of tumor size, location, and biology is imperative for optimizing the benefits of local ablation therapy in managing HCCs.

Objectives: This project aims to model an optimal scanning environment for breast magnetic resonance imaging (MRI) screening based on real-life data to identify to what extent the logistics of breast MRI can be optimized.

Materials and methods: A novel concept for a breast MRI screening facility was developed considering layout of the building, workflow steps, used resources, and MRI protocols. The envisioned screening facility is person centered and aims for an efficient workflow-oriented design. Real-life data, collected from existing breast MRI screening workflows, during 62 scans in 3 different hospitals, were imported into a 3D simulation software for designing and testing new concepts. The model provided several realistic, virtual, logistical pathways for MRI screening and their outcome measures: throughput, waiting times, and other relevant variables.

Results: The total average appointment time in the baseline scenario was 25:54 minutes, with 19:06 minutes of MRI room occupation. Simulated improvements consisted of optimizing processes and resources, facility layout, and scanning protocol. In the simulation, time spent in the MRI room was reduced by introducing an optimized facility layout, dockable tables, and adoption of an abbreviated MRI scanning protocol. The total average appointment time was reduced to 19:36 minutes, and in this scenario, the MRI room was occupied for 06:21 minutes. In the most promising scenario, screening of about 68 people per day (10 hours) on a single MRI scanner could be feasible, compared with 36 people per day in the baseline scenario.

Conclusions: This study suggests that by optimizing workflow MRI for breast screening total appointment duration and MRI occupation can be reduced. A throughput of up to 6 people per hour may be achieved, compared with 3 people per hour in the current setup.

Objectives: The aim of this study was to introduce and evaluate a new metal artifact reduction framework (iMARv2) that addresses the drawbacks (residual artifacts after correction and user preferences for image quality) associated with the current clinically applied iMAR.

Materials and methods: A new iMARv2 has been introduced, combining the current iMAR with new modular components to remove residual metal artifacts after image correction. The postcorrection image impression is adjustable with user-selectable strength settings. Phantom scans from an energy-integrating and a photon-counting detector CT were used to assess image quality, including a Gammex phantom and anthropomorphic phantoms. In addition, 36 clinical cases (with metallic implants such as dental fillings, hip replacements, and spinal screws) were reconstructed and evaluated in a blinded and randomized reader study.

Results: The Gammex phantom showed lower HU errors compared with the uncorrected image at almost all iMAR and iMARv2 settings evaluated, with only minor differences between iMAR and the different iMARv2 settings. In addition, the anthropomorphic phantoms showed a trend toward lower errors with higher iMARv2 strength settings. On average, the iMARv2 strength 3 performed best of all the clinical reconstructions evaluated, with a significant increase in diagnostic confidence and decrease in artifacts. All hip and dental cases showed a significant increase in diagnostic confidence and decrease in artifact strength, and the improvements from iMARv2 in the dental cases were significant compared with iMAR. There were no significant improvements in the spine.

Conclusions: This work has introduced and evaluated a new method for metal artifact reduction and demonstrated its utility in routine clinical datasets. The greatest improvements were seen in dental fillings, where iMARv2 significantly improved image quality compared with conventional iMAR.

Objectives: Administration of gadolinium-based contrast agents (GBCA) in magnetic resonance imaging results in the long-term retention of gadolinium (Gd) in tissues and organs, including the bone, and may affect their function and metabolism. This study aims to investigate the effects of Gd and GBCA on the proliferation/survival, differentiation, and function of bone cell lineages.

Materials and methods: Primary murine osteoblasts (OB) and osteoclast progenitor cells (OPC) isolated from C57BL/6J mice were used to test the effects of Gd 3+ (12.5-100 μM) and GBCA (100-2000 μM). Cultures were supplemented with the nonionic linear Gd-DTPA-BMA (gadodiamide), ionic linear Gd-DTPA (gadopentetic acid), and macrocyclic Gd-DOTA (gadoteric acid). Cell viability and differentiation were analyzed on days 4-6 of the culture. To assess the resorptive activity of osteoclasts, the cells were grown in OPC cultures and were seeded onto layers of amorphous calcium phosphate with incorporated Gd.

Results: Gd 3+ did not affect OB viability, but differentiation was reduced dose-dependently up to 72.4% ± 6.2%-73.0% ± 13.2% (average ± SD) at 100 μM Gd 3+ on days 4-6 of culture as compared with unexposed controls ( P < 0.001). Exposure to GBCA had minor effects on OB viability with a dose-dependent reduction up to 23.3% ± 10.2% for Gd-DTPA-BMA at 2000 μM on day 5 ( P < 0.001). In contrast, all 3 GBCA caused a dose-dependent reduction of differentiation up to 88.3% ± 5.2% for Gd-DTPA-BMA, 49.8% ± 16.0% for Gd-DTPA, and 23.1% ± 8.7% for Gd-DOTA at 2000 μM on day 5 ( P < 0.001). In cultures of OPC, cell viability was not affected by Gd 3+ , whereas differentiation was decreased by 45.3% ± 9.8%-48.5% ± 15.8% at 100 μM Gd 3+ on days 4-6 ( P < 0.05). Exposure of OPC to GBCA resulted in a dose-dependent increase in cell viability of up to 34.1% ± 11.4% at 2000 μM on day 5 of culture ( P < 0.001). However, differentiation of OPC cultures was reduced on day 5 by 24.2% ± 9.4% for Gd-DTPA-BMA, 47.1% ± 14.0% for Gd-DTPA, and 38.2% ± 10.0% for Gd-DOTA ( P < 0.001). The dissolution of amorphous calcium phosphate by mature osteoclasts was reduced by 36.3% ± 5.3% upon incorporation of 4.3% Gd/Ca wt/wt ( P < 0.001).

Conclusions: Gadolinium and GBCA inhibit differentiation and activity of bone cell lineages in vitro. Thus, Gd retention in bone tissue could potentially impair the physiological regulation of bone turnover on a cellular level, leading to pathological changes in bone metabolism.

Background: Accurate detection of lymph node (LN) metastases in prostate cancer (PCa) is a challenging but crucial step for disease staging. Ultrasmall superparamagnetic iron oxide (USPIO)-enhanced magnetic resonance imaging (MRI) enables distinction between healthy LNs and nodes suspicious for harboring metastases. When combined with MRI at an ultra-high magnetic field, an unprecedented spatial resolution can be exploited to visualize these LNs.

Purpose: The aim of this study was to explore USPIO-enhanced MRI at 7 T in comparison to 3 T for the detection of small suspicious LNs in the same cohort of patients with PCa.

Materials and methods: Twenty PCa patients with high-risk primary or recurrent disease were referred to our hospital for an investigational USPIO-enhanced 3 T MRI examination with ferumoxtran-10. With consent, they underwent a 7 T MRI on the same day. Three-dimensional anatomical and T2*-weighted images of both examinations were evaluated blinded, with an interval, by 2 readers who annotated LNs suspicious for metastases. Number, size, and level of suspicion (LoS) of LNs were paired within patients and compared between field strengths.

Results: At 7 T, both readers annotated significantly more LNs compared with 3 T (474 and 284 vs 344 and 162), with 116 suspicious LNs on 7 T (range, 1-34 per patient) and 79 suspicious LNs on 3 T (range, 1-14 per patient) in 17 patients. For suspicious LNs, the median short axis diameter was 2.6 mm on 7 T (1.3-9.5 mm) and 2.8 mm for 3 T (1.7-10.4 mm, P = 0.05), with large overlap in short axis of annotated LNs between LoS groups. At 7 T, significantly more suspicious LNs had a short axis <2.5 mm compared with 3 T (44% vs 27%). Magnetic resonance imaging at 7 T provided better image quality and structure delineation and a higher LoS score for suspicious nodes.

Conclusions: In the same cohort of patients with PCa, more and more small LNs were detected on 7 T USPIO-enhanced MRI compared with 3 T MRI. Suspicious LNs are generally very small, and increased nodal size was not a good indication of suspicion for the presence of metastases. The high spatial resolution of USPIO-enhanced MRI at 7 T improves structure delineation and the visibility of very small suspicious LNs, potentially expanding the in vivo detection limits of pelvic LN metastases in PCa patients.

Objectives: Detection of infratentorial demyelinating lesions in multiple sclerosis (MS) presents a challenge in magnetic resonance imaging (MRI), a difficulty that is further heightened in 7 T MRI. This study aimed to assess the efficacy of a novel MRI approach, lesion-attenuated magnetization-prepared gradient echo acquisition (LAMA), for detecting demyelinating lesions within the posterior fossa and upper cervical spine on 7 T MRI and contrast its performance with conventional double-inversion recovery (DIR) and T2-weighted turbo spin echo sequences.

Materials and methods: We conducted a retrospective cross-sectional study in 42 patients with a confirmed diagnosis of MS. All patients had 7 T MRI that incorporated LAMA, 3D DIR, and 2D T2-weighted turbo spin echo sequences. Three readers assessed lesion count in the brainstem, cerebellum, and upper cervical spinal cord using both DIR and T2-weighted images in one session. In a separate session, LAMA was analyzed alone. Contrast-to-noise ratio was also compared between LAMA and the conventional sequences. Lesion counts between methods were assessed using nonparametric Wilcoxon signed rank test. Interrater agreement in lesion detection was estimated by intraclass correlation coefficients.

Results: LAMA identified a significantly greater number of lesions than DIR + T2 (mean 6.4 vs 3.0; P < 0.001). LAMA also exhibited better interrater agreement (intraclass correlation coefficient [95% confidence interval], 0.75 [0.41-0.88] vs 0.61 [0.35-0.78]). The contrast-to-noise ratio for LAMA (3.7 ± 0.9) significantly exceeded that of DIR (1.94 ± 0.7) and T2 (1.2 ± 0.7) (all P 's < 0.001). In cases with no lesions detected using DIR + T2, at least 1 lesion was identified in 83.3% with LAMA. Across all analyzed brain regions, LAMA consistently detected more lesions than DIR + T2.

Conclusions: LAMA significantly improves the detection of infratentorial demyelinating lesions in MS patients compared with traditional methods. Integrating LAMA with standard magnetization-prepared 2 rapid acquisition gradient echo acquisition provides a valuable tool for accurately characterizing the extent of MS disease.