Distinction of pseudoprogression from true progression in glioblastomas using machine learning based on multiparametric magnetic resonance imaging and O6-methylguanine-methyltransferase promoter methylation status.

Background: It is imperative to differentiate true progression (TP) from pseudoprogression (PsP) in glioblastomas (GBMs). We sought to investigate the potential of physiologically sensitive quantitative parameters derived from diffusion and perfusion magnetic resonance imaging (MRI), and molecular signature combined with machine learning in distinguishing TP from PsP in GBMs in the present study. Methods: GBM patients (n = 93) exhibiting contrast-enhancing lesions within 6 months after completion of standard treatment underwent 3T MRI. Final data analyses were performed on 75 patients as O6-methylguanine-DNA-methyltransferase (MGMT) status was available only from these patients. Subsequently, patients were classified as TP (n = 55) or PsP (n = 20) based on histological features or mRANO criteria. Quantitative parameters were computed from contrast-enhancing regions of neoplasms. PsP datasets were artificially augmented to achieve balanced class distribution in 2 groups (TP and PsP). A random forest algorithm was applied to select the optimized features. The data were randomly split into training and testing subsets in an 8:2 ratio. To develop a robust prediction model in distinguishing TP from PsP, several machine-learning classifiers were employed. The cross-validation and receiver operating characteristic (ROC) curve analyses were performed to determine the diagnostic performance. Results: The quadratic support vector machine was found to be the best classifier in distinguishing TP from PsP with a training accuracy of 91%, cross-validation accuracy of 86%, and testing accuracy of 85%. Additionally, ROC analysis revealed an accuracy of 85%, sensitivity of 70%, and specificity of 100%. Conclusions: Machine learning using quantitative multiparametric MRI may be a promising approach to distinguishing TP from PsP in GBMs.

Liver fat response to two days fasting and two days isocaloric high-carbohydrate refeeding in lean and obese women.

BACKGROUND AND AIMS: Prolonged fasting, which leads to the mobilization of fat from adipose tissue, can result in the development of hepatosteatosis. However, it is not yet known whether the accumulation of fat in the liver after fasting can be affected by concurrent obesity. Therefore, this study aimed to assess how excessive adiposity influences changes in liver fat content induced by fasting and subsequent refeeding. METHODS AND RESULTS: Ten lean women and eleven women with obesity (age: 36.4 ± 7.9 and 34.5 ± 7.9 years, BMI: 21.4 ± 1.7 and 34.5 ± 4.8 kg/m2) underwent a 60-h fasting period followed by 2 days of isocaloric high-carbohydrate refeeding. Magnetic resonance spectroscopy (MRS) examinations of liver were conducted at baseline, after 48 h of fasting, and at the end of refeeding period. Hepatic fat content (HFC) increased in lean women after fasting, whereas no statistically significant change in HFC was observed in women with obesity. Additionally, fasting led to significant reductions in liver volume in both groups, likely attributable to glycogen depletion, with subsequent restoration upon refeeding. Notably, changes in hepatic fat volume (HFV) rather than HFC inversely correlated with baseline liver fat content and HOMA-IR. CONCLUSION: We demonstrated that prolonged fasting results in accumulation of fat in the liver in lean subjects only and that this accumulation is inversely related to baseline fat content and insulin resistance. Moreover, the study underscored the importance of evaluating hepatic fat volume rather than hepatic fat content in studies that involve considerable changes in hepatic lean volume.

Impactful Cardiac CT and MRI Articles from 2023.

Cardiac imaging is important in diagnosing, treating, and predicting prognosis in patients with cardiovascular disease. Imaging protocols and analysis are consistently evolving, and the implementation of artificial intelligence-based applications is of increasing interest. This review presents recent advancements in noninvasive cardiac imaging, specifically focusing on cardiac CT and MRI, from notable publications across multidisciplinary journals in 2023 of interest to both radiologists and referring clinicians in the field. The discussion encompasses the latest trials of CT fractional flow reserve and the performance of the newest generation of photon-counting detector CT, particularly in coronary stenosis quantification. Additionally, it addresses coronary plaque quantification using artificial intelligence applications and their implications from large patient cohorts, alongside prognostic outcomes, and the value of coronary artery calcification scores. Various aspects of CT trials, such as anatomic planning before revascularization, high-risk plaque features, outcomes, and pericoronary fat index, are evaluated. New insights from cardiac MRI trials for cardiomyopathies, including cardiac amyloidosis, dilated cardiomyopathy, hypertrophic cardiomyopathy, myocarditis, and valvular disease, are also outlined. The review concludes by highlighting impactful societal statements and guidelines. Keywords: CT Angiography, MR Imaging, Transcatheter Aortic Valve Implantation/Replacement (TAVI/TAVR), Cardiac, Coronary Arteries, Heart, Left Ventricle © RSNA, 2024.

Deformable Mapping of Rectal Cancer Whole-Mount Histology with Restaging MRI at Voxel Scale: A Feasibility Study.

Purpose To develop a radiology-pathology coregistration method for 1:1 automated spatial mapping between preoperative rectal MRI and ex vivo rectal whole-mount histology (WMH). Materials and Methods This retrospective study included consecutive patients with rectal adenocarcinoma who underwent total neoadjuvant therapy followed by total mesorectal excision with preoperative rectal MRI and WMH from January 2019 to January 2022. A gastrointestinal pathologist and a radiologist established three corresponding levels for each patient at rectal MRI and WMH, subsequently delineating external and internal rectal wall contours and the tumor bed at each level and defining eight point-based landmarks. An advanced deformable image coregistration model based on the linearized iterative boundary reconstruction (LIBR) approach was compared with rigid point-based registration (PBR) and state-of-the-art deformable intensity-based multiscale spectral embedding registration (MSERg). Dice similarity coefficient (DSC), modified Hausdorff distance (MHD), and target registration error (TRE) across patients were calculated to assess the coregistration accuracy of each method. Results Eighteen patients (mean age, 54 years ± 13 [SD]; nine female) were included. LIBR demonstrated higher DSC versus PBR for external and internal rectal wall contours and tumor bed (external: 0.95 ± 0.03 vs 0.86 ± 0.04, respectively, P < .001; internal: 0.71 ± 0.21 vs 0.61 ± 0.21, P < .001; tumor bed: 0.61 ± 0.17 vs 0.52 ± 0.17, P = .001) and versus MSERg for internal rectal wall contours (0.71 ± 0.21 vs 0.63 ± 0.18, respectively; P < .001). LIBR demonstrated lower MHD versus PBR for external and internal rectal wall contours and tumor bed (external: 0.56 ± 0.25 vs 1.68 ± 0.56, respectively, P < .001; internal: 1.00 ± 0.35 vs 1.62 ± 0.59, P < .001; tumor bed: 2.45 ± 0.99 vs 2.69 ± 1.05, P = .03) and versus MSERg for internal rectal wall contours (1.00 ± 0.35 vs 1.62 ± 0.59, respectively; P < .001). LIBR demonstrated lower TRE (1.54 ± 0.39) versus PBR (2.35 ± 1.19, P = .003) and MSERg (2.36 ± 1.43, P = .03). Computation time per WMH slice for LIBR was 35.1 seconds ± 12.1. Conclusion This study demonstrates feasibility of accurate MRI-WMH coregistration using the advanced LIBR method. Keywords: MR Imaging, Abdomen/GI, Rectum, Oncology Supplemental material is available for this article. © RSNA, 2024.

A dynamic approach for MR T2-weighted pelvic imaging.

OBJECTIVE: T2-weighted 2D fast spin echo sequence serves as the standard sequence in clinical pelvic MR imaging protocols. However, motion artifacts and blurring caused by peristalsis present significant challenges. Patient preparation such as administering antiperistaltic agents is often required before examination to reduce artifacts, which discomfort the patients. This work introduce a novel dynamic approach for T2 weighted pelvic imaging to address peristalsis-induced motion issue without any patient preparation. Approach: A rapid dynamic data acquisition strategy with complementary sampling trajectory is designed to enable highly undersampled motion-resistant data sampling, and an unrolling method based on deep equilibrium model is leveraged to reconstruct images from the dynamic sampled k-space data. Moreover, the fix-point convergence of the equilibrium model ensures the stability of the reconstruction. The high acceleration factor in each temporal phase, which is much higher than that in traditional static imaging, has the potential to effectively freeze pelvic motion, thereby transforming the imaging problem from conventional motion prevention or removal to motion reconstruction. Main results: Experiments on both retrospective and prospective data have demonstrated the superior performance of the proposed dynamic approach in reducing motion artifacts and accurately depicting structural details compared to standard static imaging. Significance: The proposed dynamic approach effectively captures motion states through dynamic data acquisition and deep learning-based reconstruction, addressing motion-related challenges in pelvic imaging.

Pineal gland ADC values in children aged 0 to 4 years: normative data and usefulness in the differential diagnosis with trilateral retinoblastoma.

PURPOSE: Normative ADC values of the pineal gland in young children are currently lacking, however, these are potentially useful in the differential diagnosis of pineal involvement in trilateral retinoblastoma, which is challenging when the size of the tumor is less than 10-15 mm. The main objective of this study was to establish ADC reference values of the normal pineal gland in a large cohort of children between 0 and 4 years. METHODS: This retrospective study was conducted in a tertiary pediatric hospital. We collected 64 patients with normal MRI examination (between 2017 and 2024) and clinical indication unrelated to the pineal gland, and divided them into 5 age groups (0 to 4 years). Gland size and mean ADC values were calculated, using the ellipsoid formula and ROI/histogram analysis, respectively. The established values were tested in three cases of trilateral retinoblastoma (10 to 20 months). RESULTS: Mean ADC values were always above 1000 × 10- 6 mm2/s, while in patients with trilateral retinoblastoma they were around 800 × 10- 6 mm2/s. Pineal ADC values were identical in both genders. The volume of the pineal gland showed a tendency to increase with age. CONCLUSIONS: We present ADC reference data for the pineal gland in children under 4 years of age. The distribution of mean ADC values of trilateral retinoblastoma was significantly different from the normative values, hence, the use DWI/ADC may help to identify small trilateral retinoblastoma in children with ocular pathology.

Imaging of Hemorrhagic Stroke in Children.

Hemorrhagic stroke (HS) is an important cause of neurologic morbidity and mortality in children and is more common than ischemic stroke between the ages of 1 and 14 years, a notable contradistinction relative to adult stroke epidemiology. Rapid neuroimaging is of the utmost importance in making the diagnosis of HS, identifying a likely etiology, and directing acute care. Computed tomography and MR imaging with flow-sensitive MR imaging and other noninvasive vascular imaging studies play a primary role in the initial diagnostic evaluation. Catheter-directed digital subtraction angiography is critical for definitive diagnosis and treatment planning.

Advanced imaging techniques and non-invasive biomarkers in pediatric brain tumors: state of the art.

In the pediatric age group, brain neoplasms are the second most common tumor category after leukemia, with an annual incidence of 6.13 per 100,000. Conventional MRI sequences, complemented by CT whenever necessary, are fundamental for the initial diagnosis and surgical planning as well as for post-operative evaluations, assessment of response to treatment, and surveillance; however, they have limitations, especially concerning histopathologic or biomolecular phenotyping and grading. In recent years, several advanced MRI sequences, including diffusion-weighted imaging, diffusion tensor imaging, arterial spin labelling (ASL) perfusion, and MR spectroscopy, have emerged as a powerful aid to diagnosis as well as prognostication; furthermore, other techniques such as diffusion kurtosis, amide proton transfer imaging, and MR elastography are being translated from the research environment to clinical practice. Molecular imaging, especially PET with amino-acid tracers, complement MRI in several aspects, including biopsy targeting and outcome prediction. Finally, radiomics with radiogenomics are opening entirely new perspectives for a quantitative approach aiming at identifying biomarkers that can be used for personalized, precision management strategies.

Potential Neuroimaging Biomarkers for Autism Spectrum Disorder: A Comprehensive Review of MR Imaging, fMR Imaging, and PET Studies.

Autism spectrum disorder (ASD) is a characteristically heterogeneous disorder, as multiple neurodevelopmental disorders are characterized by similar symptomology and behavior. Research has shown that individuals with ASD benefit from early intervention; neuroimaging data may reveal information that cannot be obtained from traditional behavioral analysis. This review discusses the use of structural MR imaging, functional MR imaging (fMR imaging), and PET in the detection of ASD. Larger datasets, standardized methods of collection and analysis, and more robust meta-analyses are required to implement the observed biomarkers and improve the lives of patients living with AUD.

External Validation of a Previously Developed Deep Learning-based Prostate Lesion Detection Algorithm on Paired External and In-House Biparametric MRI Scans.

Purpose To evaluate the performance of an artificial intelligence (AI) model in detecting overall and clinically significant prostate cancer (csPCa)-positive lesions on paired external and in-house biparametric MRI (bpMRI) scans and assess performance differences between each dataset. Materials and Methods This single-center retrospective study included patients who underwent prostate MRI at an external institution and were rescanned at the authors' institution between May 2015 and May 2022. A genitourinary radiologist performed prospective readouts on in-house MRI scans following the Prostate Imaging Reporting and Data System (PI-RADS) version 2.0 or 2.1 and retrospective image quality assessments for all scans. A subgroup of patients underwent an MRI/US fusion-guided biopsy. A bpMRI-based lesion detection AI model previously developed using a completely separate dataset was tested on both MRI datasets. Detection rates were compared between external and in-house datasets with use of the paired comparison permutation tests. Factors associated with AI detection performance were assessed using multivariable generalized mixed-effects models, incorporating features selected through forward stepwise regression based on the Akaike information criterion. Results The study included 201 male patients (median age, 66 years [IQR, 62-70 years]; prostate-specific antigen density, 0.14 ng/mL2 [IQR, 0.10-0.22 ng/mL2]) with a median interval between external and in-house MRI scans of 182 days (IQR, 97-383 days). For intraprostatic lesions, AI detected 39.7% (149 of 375) on external and 56.0% (210 of 375) on in-house MRI scans (P < .001). For csPCa-positive lesions, AI detected 61% (54 of 89) on external and 79% (70 of 89) on in-house MRI scans (P < .001). On external MRI scans, better overall lesion detection was associated with a higher PI-RADS score (odds ratio [OR] = 1.57; P = .005), larger lesion diameter (OR = 3.96; P < .001), better diffusion-weighted MRI quality (OR = 1.53; P = .02), and fewer lesions at MRI (OR = 0.78; P = .045). Better csPCa detection was associated with a shorter MRI interval between external and in-house scans (OR = 0.58; P = .03) and larger lesion size (OR = 10.19; P < .001). Conclusion The AI model exhibited modest performance in identifying both overall and csPCa-positive lesions on external bpMRI scans. Keywords: MR Imaging, Urinary, Prostate Supplemental material is available for this article. © RSNA, 2024.

Targeted delivery of cisplatin magnetic nanoparticles for diagnosis and treatment of nasopharyngeal carcinoma.

Rapid advances in nanotechnology are paving the way for innovative breakthroughs in overcoming the current limitations in the clinical treatment of cancer and other prevalent diseases plaguing mankind. Magnetic nanoparticles composed of iron oxide (Fe3O4) are a novel class of nanoparticles that are receiving increasing attention in the field of cancer therapy. To address the inherent limitations, bare Fe3O4 can be functionalized, polymerized, assembled, or combined with other functional materials to produce a range of smart nanoplatforms suitable for tumor therapy. In this paper, we present a unique multifunctional therapeutic nanoplatform centered on aldehyde-oxidized sodium alginate-stabilized iron oxide nanoparticles (NPs) designed for T2-weighted magnetic resonance (MR) imaging. Sodium alginate oxide and ferric oxide nanoparticles were prepared respectively, and the two particles were mixed in a certain molar ratio to form a complex, which was coupled to target polypeptide GE11 by Schiff base reaction, and finally supported by cisplatin through coordination complexation. The prepared magnetic nanoparticles (hereinafter referred to as GE11-CDDP-ASA@Fe3O4) have an average diameter of 152.9 nm, and have good colloidal stability and cytocompatibility. The distinctive structure and composition of GE11-CDDP-ASA@Fe3O4 contribute to its excellent MRI imaging performance, positioning it as a nano platform suitable for enhancing the efficacy of combination therapy in tumor treatment. This is of great significance for translational nanomedicine applications.

Coupled stack-up volume RF coils for low-field open MR imaging.

Background: Low-field open magnetic resonance imaging (MRI) systems, typically operating at magnetic field strengths below 1 Tesla, has greatly expanded the accessibility of MRI technology to meet a wide range of patient needs. However, the inherent challenges of low-field MRI, such as limited signal-to-noise ratios and limited availability of dedicated radiofrequency (RF) coils, have prompted the need for innovative coil designs that can improve imaging quality and diagnostic capabilities. Purpose: In response to these challenges, we introduce the coupled stack-up volume coil, a novel RF coil design that addresses the shortcomings of conventional birdcage in the context of low-field open MRI. Methods: The proposed coupled stack-up volume coil design utilizes a unique architecture that optimizes both transmit/receive efficiency and RF field homogeneity and offers the advantage of a simple design and construction, making it a practical and feasible solution for low-field MRI applications. This paper presents a comprehensive exploration of the theoretical framework, design considerations, and experimental validation of this innovative coil design. Results: We demonstrate the superior performance of the coupled stack-up volume coil in achieving 47.7% higher transmit/receive efficiency and 68% more uniform magnetic field distribution compared to traditional birdcage coils in electromagnetic simulations. Bench tests results show that the B1 field efficiency of coupled stack-up volume coil is 57.3% higher compared with that of conventional birdcage coil. Conclusions: The proposed coupled stack-up volume coil outperforms the conventional birdcage coil in terms of B1 efficiency, imaging coverage, and low-frequency operation capability. This design provides a robust and simple solution to low-field MR RF coil design.

Preoperative breast MR imaging influences surgical management in patients with invasive lobular carcinoma.

INTRODUCTION: The purpose of the study is to assess the role of preoperative magnetic resonance (MR) imaging on the surgical management of invasive lobular carcinoma (ILC) and to evaluate whether breast density and background parenchymal enhancement (BPE) influence surgical treatment. METHODS: This retrospective study was conducted on 56 patients who were diagnosed with ILC between 2014 and 2020. All patients had mammogram and ultrasound. Preoperative MRI was available in 34 patients. Age, menopausal status, breast density, BPE, multifocality/multicentricity and surgical treatment were collected. RESULTS: Mean pathological tumour size was 36.4 mm (range 5-140 mm). Dense breasts had larger tumours compared to non-dense breasts (P = 0.072). Of the 34 patients with MRI, 6 opted for mastectomy. Of the remaining 28 cases, MRI findings upgraded surgery to mastectomy in 54% (15/28) because mammogram/ultrasound underestimated tumour extent in 25% (7/28), or multifocal/multicentric disease was identified in 29% (8/28). Tumour size was underestimated by MRI in 7% (2/28). In the non-MRI subgroup, 64% (14/22) of patients underwent breast-conserving surgery, but 29% of them (4/14) required a second-stage mastectomy due to extensive margin involvement. There was no difference in mastectomy rate between patients with MRI (62%) and without MRI (55%) (P = 0.061). Tumour size correlation between MRI and histopathology demonstrated an excellent intraclass correlation coefficient (P < 0.001). Surgical treatment recommendation was not significantly impacted by breast density or BPE. CONCLUSION: Breast MRI improves surgical management of patients with ILC in providing additional diagnostic information often missed with standard imaging modalities, and without increasing mastectomy rate. Surgical treatment is not impacted by breast density or BPE.

MR Imaging-Guided Focused Ultrasound for Breast Tumors.

Breast tumors remain a complex and prevalent health burden impacting millions of individuals worldwide. Challenges in treatment arise from the invasive nature of traditional surgery and, in malignancies, the complexity of treating metastatic disease. The development of noninvasive treatment alternatives is critical for improving patient outcomes and quality of life. This review aims to explore the advancements and applications of focused ultrasound (FUS) technology over the past 2 decades. FUS offers a promising noninvasive, nonionizing intervention strategy in breast tumors including primary breast cancer, fibroadenomas, and metastatic breast cancer.

MR-guided Focused Ultrasound Focal Therapy for Prostate Cancer.

Prostate cancer (PCa) is a prevalent malignancy in men, and the management of localized disease has evolved significantly in recent years. Focal therapy, wherein the biopsy confirmed site of tumor with margins is treated leaving the remaining gland intact, has emerged as a promising strategy for treating localized clinically significant PCa, minimizing side effects associated with radical therapies. We present the technical aspects, a summary of the most relevant evidence to date on the performance and safety of this technique, and the characteristic MR imaging findings during treatment, in the early posttreatment period and in the long term.

MR-guided Focused Ultrasound Thalamotomy for Chronic Pain.

MR-guided focused ultrasound (FUS) represents a promising alternative for patients with chronic neuropathic who have failed medical management and other treatment options. Early single-center experience with chronic neuropathic pain and trigeminal neuralgia has demonstrated favorable long-term outcomes. Excellent safety profile with low risk of motor and sensory complications and so far anecdotal permanent neurologic deficits make FUS a powerful tool to treat patients who are otherwise hopeless. Neuromodulation may be the most influential factor driving outcomes and studies devised to detect neuroplasticity will be critical to guide such therapies.

MR Imaging-Guided Focused Ultrasound-Clinical Applications in Managing Malignant Gliomas.

Malignant gliomas (MGs) are the most common primary brain tumors in adults. Despite recent advances in understanding the biology and potential therapeutic vulnerabilities of MGs, treatment options remain limited as the delivery of drugs is often impeded by the blood-brain barrier (BBB), and safe, complete surgical resection may not always be possible, especially for deep-seated tumors. In this review, the authors highlight emerging applications for MR imaging-guided focused ultrasound (MRgFUS) as a noninvasive treatment modality for MGs. Specifically, the authors discuss MRgFUS's potential role in direct tumor cell killing, opening the BBB, and modulating antitumor immunity.

Association of Cardiac MRI-derived Aortic Stiffness with Early Stages and Progression of Heart Failure with Preserved Ejection Fraction.

Purpose To investigate if aortic stiffening as detected with cardiac MRI is an early phenomenon in the development and progression of heart failure with preserved ejection fraction (HFpEF). Materials and Methods Both clinical and preclinical studies were performed. The clinical study was a secondary analysis of the prospective HFpEF stress trial (August 2017 through September 2019) and included 48 participants (median age, 69 years [range, 65-73 years]; 33 female, 15 male) with noncardiac dyspnea (NCD, n = 21), overt HFpEF at rest (pulmonary capillary wedge pressure [PCWP] ≥ 15 mm Hg, n = 14), and masked HFpEF at rest diagnosed during exercise stress (PCWP ≥ 25 mm Hg, n = 13) according to right heart catheterization. Additionally, all participants underwent echocardiography and cardiac MRI at rest and during exercise stress. Aortic pulse wave velocity (PWV) was calculated. The mechanistic preclinical study characterized cardiac function and structure in transgenic mice with induced arterial stiffness (Runx2-smTg mice). Statistical analyses comprised nonparametric and parametric comparisons, Spearman correlations, and logistic regression models. Results Participants with HFpEF showed increased PWV (NCD vs masked HFpEF: 7.0 m/sec [IQR: 5.0-9.5 m/sec] vs 10.0 m/sec [IQR: 8.0-13.4 m/sec], P = .005; NCD vs overt HFpEF: 7.0 m/sec [IQR: 5.0-9.5 m/sec] vs 11.0 m/sec [IQR: 7.5-12.0 m/sec], P = .01). Increased PWV correlated with higher PCWP (P = .006), left atrial and left ventricular long-axis strain (all P < .02), and N-terminal pro-brain natriuretic peptide levels (P < .001). Participants with overt HFpEF had higher levels of myocardial fibrosis, as demonstrated by increased native T1 times (1199 msec [IQR: 1169-1228 msec] vs 1234 msec [IQR: 1208-1255 msec], P = .009). Aortic stiffness was independently associated with HFpEF on multivariable analyses (odds ratio, 1.31; P = .049). Runx2-smTG mice exhibited an "HFpEF" phenotype compared with wild-type controls, with preserved left ventricular fractional shortening but an early and late diastolic mitral annulus velocity less than 1 (mean, 0.67 ± 0.39 [standard error of the mean] vs 1.45 ± 0.47; P = .004), increased myocardial collagen deposition (mean, 11% ± 1 vs 2% ± 1; P < .001), and increased brain natriuretic peptide levels (mean, 171 pg/mL ± 23 vs 101 pg/mL ± 10; P < .001). Conclusion This study provides translational evidence that increased arterial stiffness might be associated with development and progression of HFpEF and may facilitate its early detection. Keywords: MR Functional Imaging, MR Imaging, Animal Studies, Cardiac, Aorta, Heart ClinicalTrials.gov identifier NCT03260621 Supplemental material is available for this article. © RSNA, 2024.