Publications

Convolutional neural networks (CNN) have demonstrated good accuracy and speed in spatially registering high signal-to-noise ratio (SNR) structural magnetic resonance imaging (sMRI) images. However, some functional magnetic resonance imaging (fMRI) images, e.g., those acquired from arterial spin labeling (ASL) perfusion fMRI, are of intrinsically low SNR and therefore the quality of registering ASL images using CNN is not clear. In this work, we aimed to explore the feasibility of a CNN-based affine registration network (ARN) for registration of low-SNR three-dimensional ASL perfusion image time series and compare its performance with that from the state-of-the-art statistical parametric mapping (SPM) algorithm. The six affine parameters were learned from the ARN using both simulated motion and real acquisitions from ASL perfusion fMRI data and the registered images were generated by applying the transformation derived from the affine parameters. The speed and registration accuracy were compared between ARN and SPM. Several independent datasets, including meditation study (10 subjects × 2), bipolar disorder study (26 controls, 19 bipolar disorder subjects), and aging study (27 young subjects, 33 older subjects), were used to validate the generality of the trained ARN model. The ARN method achieves superior image affine registration accuracy (total translation/total rotation errors of ARN vs. SPM: 1.17 mm/1.23° vs. 6.09 mm/12.90° for simulated images and reduced MSE/L1/DSSIM/Total errors of 18.07% / 19.02% / 0.04% / 29.59% for real ASL test images) and 4.4 times (ARN vs. SPM: 0.50 s vs. 2.21 s) faster speed compared to SPM. The trained ARN can be generalized to align ASL perfusion image time series acquired with different scanners, and from different image resolutions, and from healthy or diseased populations. The results demonstrated that our ARN markedly outperforms the iteration-based SPM both for simulated motion and real acquisitions in terms of registration accuracy, speed, and generalization.

PURPOSE: Chiari malformation type I (CMI) patients have been independently shown to have both increased resistance to cerebrospinal fluid (CSF) flow in the cervical spinal canal and greater cardiac-induced neural tissue motion compared to healthy controls. The goal of this paper is to determine if a relationship exists between CSF flow resistance and brain tissue motion in CMI subjects.

METHODS: Computational fluid dynamics (CFD) techniques were employed to compute integrated longitudinal impedance (ILI) as a measure of unsteady resistance to CSF flow in the cervical spinal canal in thirty-two CMI subjects and eighteen healthy controls. Neural tissue motion during the cardiac cycle was assessed using displacement encoding with stimulated echoes (DENSE) magnetic resonance imaging (MRI) technique.

RESULTS: The results demonstrate a positive correlation between resistance to CSF flow and the maximum displacement of the cerebellum for CMI subjects (r = 0.75, p = 6.77 × 10-10) but not for healthy controls. No correlation was found between CSF flow resistance and maximum displacement in the brainstem for CMI or healthy subjects. The magnitude of resistance to CSF flow and maximum cardiac-induced brain tissue motion were not statistically different for CMI subjects with and without the presence of five CMI symptoms: imbalance, vertigo, swallowing difficulties, nausea or vomiting, and hoarseness.

CONCLUSION: This study establishes a relationship between CSF flow resistance in the cervical spinal canal and cardiac-induced brain tissue motion in the cerebellum for CMI subjects. Further research is necessary to understand the importance of resistance and brain tissue motion in the symptomatology of CMI.

Lung cancer continues to be the most common cause of cancer-related death worldwide. In the past decade, with the implementation of lung cancer screening programs and advances in surgical and nonsurgical therapies, the survival of patients with lung cancer has increased, as has the number of imaging studies that these patients undergo. However, most patients with lung cancer do not undergo surgical re-section, because they have comorbid disease or lung cancer in an advanced stage at diagnosis. Nonsurgical therapies have continued to evolve with a growing range of systemic and targeted therapies, and there has been an associated evolution in the imaging findings encountered at follow-up examinations after such therapies (e.g., with respect to posttreatment changes, treatment complications, and recurrent tumor). This AJR Expert Panel Narrative Review describes the current status of nonsurgical therapies for lung cancer and their expected and unexpected imaging manifestations. The goal is to provide guidance to radiologists regarding imaging assessment after such therapies, focusing mainly on non-small cell lung cancer. Covered therapies include systemic therapy (conventional chemotherapy, targeted therapy, and immunotherapy), radiotherapy, and thermal ablation.

PURPOSE: To assess the accuracy, completeness, and readability of patient educational material produced by a machine learning model and compare the output to that provided by a societal website.

MATERIALS AND METHODS: Content from the Society of Interventional Radiology Patient Center website was retrieved, categorized, and organized into discrete questions. These questions were entered into the ChatGPT platform, and the output was analyzed for word and sentence counts, readability using multiple validated scales, factual correctness, and suitability for patient education using the Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P) instrument.

RESULTS: A total of 21,154 words were analyzed, including 7,917 words from the website and 13,377 words representing the total output of the ChatGPT platform across 22 text passages. Compared to the societal website, output from the ChatGPT platform was longer and more difficult to read on 4 of 5 readability scales. The ChatGPT output was incorrect for 12 (11.5%) of 104 questions. When reviewed using the PEMAT-P tool, the ChatGPT content scored lower than the website material. Content from both the website and ChatGPT were significantly above the recommended fifth or sixth grade level for patient education, with a mean Flesch-Kincaid grade level of 11.1 (±1.3) for the website and 11.9 (±1.6) for the ChatGPT content.

CONCLUSIONS: The ChatGPT platform may produce incomplete or inaccurate patient educational content, and providers should be familiar with the limitations of the system in its current form. Opportunities may exist to fine-tune existing large language models, which could be optimized for the delivery of patient educational content.

PURPOSE: To investigate the role of microRNA-21 (miR21) in radiofrequency (RF) ablation-induced tumor growth and whether miR21 inhibition suppresses tumorigenesis.

MATERIAL AND METHODS: Standardized liver RF ablation was applied to 35 C57/BL6 mice. miR21 and target proteins pSTAT3, PDCD4, and PTEN were assayed 3 hours, 24 hours, and 3 days after ablation. Next, 53 Balb/c and 44 C57BL/6 mice received Antago-miR21 or scrambled Antago-nc control, followed by intrasplenic injection of 10,000 CT26 or MC38 colorectal tumor cells, respectively. Hepatic RF ablation or sham ablation was performed 24 hours later. Metastases were quantified and tumor microvascular density (MVD) and cellular proliferation were assessed at 14 or 21 days after the procedures, respectively.

RESULTS: RF ablation significantly increased miR21 levels in plasma and hepatic tissue at 3 and 24 hours as well as target proteins at 3 days after ablation (P < .05, all comparisons). RF ablation nearly doubled tumor growth (CT26, 2.0 SD ± 1.0 fold change [fc]; MC38, 1.9 SD ± 0.9 fc) and increased MVD (CT26, 1.9 SD ± 1.0 fc; MC38, 1.5 ± 0.5 fc) and cellular proliferation (CT26, 1.7 SD ± 0.7 fc; MC38, 1.4 SD ± 0.5 fc) compared with sham ablation (P < .05, all comparisons). RF ablation-induced tumor growth was suppressed when Antago-miR21 was administered (CT26, 1.0 SD ± 0.7 fc; MC38, 0.9 SD ± 0.4 fc) (P < .01, both comparisons). Likewise, Antago-miR21 decreased MVD (CT26, 1.0 SD ± 0.3 fc; MC38, 1.0 SD ± 0.2 fc) and cellular proliferation (CT26, 0.9 SD ± 0.3 fc; MC38, 0.8 SD ± 0.3 fc) compared with baseline (P < .05, all comparisons).

CONCLUSIONS: RF ablation upregulates protumorigenic miR21, which subsequently influences downstream tumor-promoting protein pathways. This effect can potentially be suppressed by specific inhibition of miR21, rendering this microRNA a pivotal and targetable driver of tumorigenesis after hepatic thermal ablation.

Emerging evidence regarding the effectiveness of locoregional therapies (LRTs) for breast cancer has prompted investigation of the potential role of interventional radiology (IR) in the care continuum of patients with breast cancer. The Society of Interventional Radiology Foundation invited 7 key opinion leaders to develop research priorities to delineate the role of LRTs in both primary and metastatic breast cancer. The objectives of the research consensus panel were to identify knowledge gaps and opportunities pertaining to the treatment of primary and metastatic breast cancer, establish priorities for future breast cancer LRT clinical trials, and highlight lead technologies that will improve breast cancer outcomes either alone or in combination with other therapies. Potential research focus areas were proposed by individual panel members and ranked by all participants according to each focus area's overall impact. The results of this research consensus panel present the current priorities for the IR research community related to the treatment of breast cancer to investigate the clinical impact of minimally invasive therapies in the current breast cancer treatment paradigm.

OBJECTIVES: To determine the factors that affect successful ultrasound-guided biopsy of liver lesions and build a model predicting feasibility of US-guided liver biopsy.

METHODS: This is IRB-approved HIPAA-compliant retrospective review of consecutive ultrasound-guided targeted liver biopsies performed or attempted between 1/2018 and 9/2020 at a single tertiary academic institution with a total of 501 patients included. Mann-Whitney and chi-square tests were used to compare continuous and categorical variables, respectively. Logistic regression model was built to predict feasibility of successful ultrasound-guided biopsy.

RESULTS: Liver lesion biopsy was successfully performed with US guidance in 429/501 (86%) patients. Lesions not amenable for US biopsy were smaller (median size 1.6 cm vs 3.3 cm, p < 0.0001) and deeper within the liver (median depth 9.0 cm vs 5.8 cm, p < 0.0001). The technical success rate was lowest for lesions in segment II (40/53, 75%), while lesions in segment IVb (87/91, 96%) had highest success rate (p < 0.003). US targeting in patients with 1 or 2 lesions was less feasible than in patients with 3 or more lesions, 126/180 (70%) vs. 303/321 (94%), (p < 0.0001). Model including lesion size, depth, location, and number of lesions predicts feasibility of US-guided biopsy with Area under the ROC curve (AUC) = 0.92.

CONCLUSIONS: Linear logistic regression model that includes lesion size, depth and location, and number of lesions is highly successful in predicting feasibility of ultrasound-guided biopsy for liver lesions. Smaller lesions, deeper lesions, and lesions in segment II and VIII in patients with less than 3 lesions were less feasible for ultrasound-guided biopsy of liver lesions.

PURPOSE: To characterize intratumoral immune cell trafficking in ablated and synchronous tumors following combined radiofrequency ablation (RFA) and systemic liposomal granulocyte-macrophage colony stimulation factor (lip-GM-CSF).

METHODS: Phase I, 72 rats with single subcutaneous R3230 adenocarcinoma were randomized to 6 groups: a) sham; b&c) free or liposomal GM-CSF alone; d) RFA alone; or e&f) combined with blank liposomes or lip-GM-CSF. Animals were sacrificed 3 and 7 days post-RFA. Outcomes included immunohistochemistry of dendritic cells (DCs), M1 and M2 macrophages, T-helper cells (Th1) (CD4+), cytotoxic T- lymphocytes (CTL) (CD8+), T-regulator cells (T-reg) (FoxP3+) and Fas Ligand activated CTLs (Fas-L+) in the periablational rim and untreated index tumor. M1/M2, CD4+/CD8+ and CD8+/FoxP3+ ratios were calculated. Phase II, 40 rats with double tumors were randomized to 4 groups: a) sham, b) RFA, c) RFA-BL and d) RFA-lip-GM-CSF. Synchronous untreated tumors collected at 7d were analyzed similarly.

RESULTS: RFA-lip-GMCSF increased periablational M1, CTL and CD8+/FoxP3+ ratio at 3 and 7d, and activated CTLs 7d post-RFA (p<0.05). RFA-lip-GMSCF also increased M2, T-reg, and reduced CD4+/CD8+ 3 and 7d post-RFA respectively (p<0.05). In untreated index tumor, RFA-lip-GMCSF improved DCs, M1, CTLs and activated CTL 7d post-RFA (p<0.05). Furthermore, RFA-lip-GMSCF increased M2 at 3 and 7d, and T-reg 7d post-RFA (p<0.05). In synchronous tumors, RFA-BL and RFA-lip-GM-CSF improved DC, Th1 and CTL infiltration 7d post-RFA.

CONCLUSION: Systemic liposomal GM-CSF combined with RFA improves intratumoral immune cell trafficking, specifically populations initiating (DC, M1) and executing (CTL, FasL+) anti-tumor immunity. Moreover, liposomes influence synchronous untreated metastases increasing Th1, CTL and DCs infiltration.

BACKGROUND AND OBJECTIVE: In recent years, there has been a large-scale dissemination of guidelines in radiology in the form of Reporting & Data Systems (RADS). The use of iodinated contrast media (ICM) has a fundamental role in enhancing the diagnostic capabilities of computed tomography (CT) but poses certain risks. The scope of the present review is to summarize the current role of ICM only in clinical reporting guidelines for CT that have adopted the "RADS" approach, focusing on three specific questions per each RADS: (I) what is the scope of the scoring system; (II) how is ICM used in the scoring system; (III) what is the impact of ICM enhancement on the scoring.

METHODS: We analyzed the original articles for each of the latest versions of RADS that can be used in CT [PubMed articles between January, 2005 and March, 2023 in English and American College of Radiology (ACR) official website].

KEY CONTENT AND FINDINGS: We found 14 RADS suitable for use in CT out of 28 RADS described in the literature. Four RADS were validated by the ACR: Colonography-RADS (C-RADS), Liver Imaging-RADS (LI-RADS), Lung CT Screening-RADS (Lung-RADS), and Neck Imaging-RADS (NI-RADS). One RADS was validated by the ACR in collaboration with other cardiovascular scientific societies: Coronary Artery Disease-RADS 2.0 (CAD-RADS). Nine RADS were proposed by other scientific groups: Bone Tumor Imaging-RADS (BTI-RADS), Bone‑RADS, Coronary Artery Calcium Data & Reporting System (CAC-DRS), Coronavirus Disease 2019 Imaging-RADS (COVID-RADS), COVID-19-RADS (CO-RADS), Interstitial Lung Fibrosis Imaging-RADS (ILF-RADS), Lung-RADS (LU-RADS), Node-RADS, and Viral Pneumonia Imaging-RADS (VP-RADS).

CONCLUSIONS: This overview suggests that ICM is not strictly necessary for the study of bones and calcifications (CAC-DRS, BTI-RADS, Bone-RADS), lung parenchyma (Lung-RADS, LU-RADS, COVID-RADS, CO-RADS, VP-RADS and ILF-RADS), and in CT colonography (C-RADS). On the other hand, ICM plays a key role in CT angiography (CAD-RADS), in the study of liver parenchyma (LI-RADS), and in the evaluation of soft tissues and lymph nodes (NI-RADS, Node-RADS). Future studies are needed in order to evaluate the impact of the new iodinated and non-iodinate contrast media, artificial intelligence tools and dual energy CT in the assignment of RADS scores.