Primary Imaging Research Articles

On the RFI Detection in Differential Interferometric Synthetic Aperture Radar

Abstract. Synthetic Aperture Radar (SAR) can image the ground with a wide area and high resolution at all times and in all weather and has become an important means of remote sensing. Differential interferometry SAR technology can obtain high-precision surface deformation information by processing more than two SAR images before and after deformation. In recent years, it has attracted widespread attention and research. However, due to the increasing number of ground electronic devices, ground radio frequency interference (RFI) has become one of the main problems in differential interferometry SAR processing, seriously affecting the performance of differential interferometry SAR imaging and differential interferometry surface deformation monitoring applications. In this paper, a clutter cancellation interference enhancement detection algorithm is proposed. By clutter suppression in the primary and secondary images, the interference-to-signal ratio is increased, which effectively improves the interference detection capabilities. The effectiveness of the algorithm in this paper is verified by the on-orbit measured data of the Lutan-1 satellites.

Characterization of a novel proton-CT scanner based on Silicon and LaBr3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_3$$\\end{document}(Ce) detectors

Treatment planning systems at proton-therapy centres entirely use X-ray computed tomography (CT) as primary imaging technique to infer the proton treatment doses to tumour and healthy tissues. However, proton stopping powers in the body, as derived from X-ray images, suffer from important proton-range uncertainties. In order to reduce this uncertainty in range, one could use proton-CT images instead. The main goal of this work is to test the capabilities of a newly-developed proton-CT scanner, based on the use of a set of tracking detectors and a high energy resolution scintillator for the residual energy of the protons. Different custom-made phantoms were positioned at the field of view of the scanner and were irradiated with protons at the CCB proton-therapy center in Krakow. We measured with the phantoms at different angles and produced sinograms that were used to obtain reconstructed images by Filtered Back-Projection. The obtained images were used to determine the capabilities of our scanner in terms of spatial resolution and proton Relative Stopping Power (RSP) mapping and validate its use as proton-CT scanner. The results show that the scanner can produce medium-high quality images, with spatial resolution better than 2 mm in radiography, below 3 mm in tomography and resolving power in the RSP comparable to other state-of-the-art pCT scanners.

Primary hyperparathyroidism imaging

Primary hyperparathyroidism imaging

Kidney Doppler Ultrasonography in Critical Care Nephrology.

Color pulsed-wave Doppler ultrasound (CPWD-US) emerges as a pivotal tool in intensive care units (ICUs) for diagnosing acute kidney injury (AKI) swiftly and non-invasively. Its bedside accessibility allows for rapid assessments, making it a primary imaging modality for AKI characterization. Furthermore, CPWD-US serves as a guiding instrument for key diagnostic-interventional procedures such as renal needle biopsy and percutaneous nephrostomy, while also facilitating therapy response monitoring and AKI progression tracking. This review shifts focus towards the integration of renal ultrasound into ICU workflows, offering contemporary insights into its utilization through a diagnostic-standard-oriented approach. By presenting a flow chart, this review aims to provide practical guidance on the appropriate use of point-of-care ultrasound (POC-US) in critical care scenarios, enhancing diagnostic precision, patient management, and safety, albeit amidst a backdrop of limited evidence regarding long-term outcomes.

Abstract PO1-01-01: ECOG-ACRIN EA1211: Interim FDG-PET/CT for predicting response of HER2-positive breast cancer to neoadjuvant therapy (DIRECT Trial)

Abstract Background: Strategies to optimize treatment decision-making in early stage HER2-positive breast cancer are a current priority for the oncology and patient advocacy community. Recent studies suggest that early metabolic changes on FDG-PET/CT (imaging biomarker) predict response to HER2-directed therapy. The TBCRC026 trial showed that participants not obtaining a 40% reduction in SULmax by cycle 1 day 15 (C1D15) following neoadjuvant trastuzumab/pertuzumab (HP) were unlikely to obtain pCR [negative predictive value (NPV) 91%]. The ECOG-ACRIN EA1211/DIRECT trial aims to validate FDG-PET/CT as a neoadjuvant interim (niFDG-PET/CT) imaging integral biomarker in patients treated with standard HER2-directed regimens (NCT05710328). Design: EA1211/DIRECT is a multicenter, single-arm, primary imaging phase 2 study enrolling patients with stage II/III HER2-positive breast cancer. Patients undergo standard skull base-thigh FDG-PET/CT at baseline and C1D15 and receive standard of care pertuzumab-based neoadjuvant therapy followed by surgery. Eligibility: Age ≥18 years, ECOG performance status 0-2, stage IIa-IIIc, untreated HER2-positive breast cancer with known hormone receptor status, suitable to undergo FDG-PET/CT imaging and neoadjuvant therapy. Methods: ΔSULmaxD15 will be computed as: (D15 SULmax – baseline SULmax)/baseline SULmax. The primary objective is to estimate the NPV of niFDG-PET/CT for pCR using ΔSULmaxD15 of the primary breast cancer at a threshold of 40%, in patients treated with neoadjuvant HER2-directed therapy. NPV is defined as the probability that pCR will not be achieved by participants with ΔSULmaxD15 < 40%. Secondary endpoints include evaluating the sensitivity, specificity, and positive predictive value of ΔSULmaxD15 of the primary breast cancer at a threshold of 40% and the ability of the niFDG-PET/CT biomarker to predict 3-year event free survival (EFS). Sample Size: We expect that 50% of patients will not reach the ΔSULmax threshold of 40% and a pCR rate of 40-60%. The proposed sample size is 210 participants, adjusted to 235 to account for missing data in 10% of cases. Computation of exact, two-sided 95% confidence intervals (CI) for NPV determined the lower limit of the CI is at least 80% when the true NPV is at least 88%. The lower limit is 84% when the true NPV has the value of 91%, which was estimated in the TBCRC026 study. Current Status: EA1211/DIRECT was activated in May 2023 across the NCI National Clinical Trials Network (NCTN), and accrual is anticipated to complete in March 2025. Those interested in the clinical trial can email ea1211team@ecog-acrin.org. Conclusion: The EA1211/DIRECT trial is the first step in implementing a Response-Guided Treatment Strategy by validating the ΔSULmax threshold of 40% as the optimum cut point across standard of care HER2-directed neoadjuvant regimens. If EA1211/DIRECT meets its objectives, the results will be used to design clinical utility studies, and thus hoping to change practice. Citation Format: Heather Jacene, Constantine Gatsonis, Roisin Connolly, Brian Burnette, Erica Stringer-Reasor, Maeve Hennessy, Justin Romanoff, Alexander Taurone, Ciara O'Sullivan, H. T. Carisa Le-Petross, Courtney Lawhn Heath, Vered Stearns, Amy Fowler, Shou-Ching Tang, Karla A Sepulveda, Angela DeMichele, David Mankoff, Antonio Wolff. ECOG-ACRIN EA1211: Interim FDG-PET/CT for predicting response of HER2-positive breast cancer to neoadjuvant therapy (DIRECT Trial) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-01-01.

Imaging thick accretion disks and jets surrounding black holes

Based on the horizon-scale magnetofluid model developed in [1], we investigate the millimeter-wave images of a geometrically thick accretion disk or a funnel wall, i.e., the magnetofluid that encloses the base of the jet region, around a Kerr black hole. By employing the numerical method to solve the null geodesic and radiative transfer equations, we obtain the optical appearances at various observational angles and frequencies, generated by the thermal synchrotron radiation within the magnetofluid. For the thick disk, we specifically examine the impact of emission anisotropy on images, concluding that anisotropic synchrotron radiation could play an important role in the observability of the photon ring. For the funnel wall, we find that both the outflow and inflow funnel walls exhibit annular structures on the imaging plane. The outflow funnel wall yields a brighter primary image than the photon ring, whereas the inflow one does not. Based on our investigation, the inflow funnel wall model can not be ruled out by current observations of M87*.

Comparison of Ultrasound and MRI in Detecting Breast Cancer: A Retrospective Study in Mumbai Hospitals, India

Introduction: Breast cancer is the most common cancer in women throughout the world. Early detection of breast cancer is very important to increase the chances of cure. Ultrasonography (USG) and magnetic resonance imaging (MRI) are two imaging methods commonly used to detect breast cancer. The aim of this study was to compare the accuracy of ultrasound and MRI in detecting breast cancer in female patients at Mumbai Hospital, India.
 Methods: A retrospective study was conducted on 2435 female patients who underwent ultrasound and MRI examinations at Mumbai Hospital, India between 2018 and 2023. Patient data was collected from electronic medical records and analyzed to compare the accuracy of ultrasound and MRI in detecting breast cancer.
 Results: The research results show that MRI is more accurate than ultrasound in detecting breast cancer. MRI sensitivity was 95.2%, while ultrasound sensitivity was 78.3%. The specificity of MRI was 98.7%, while the specificity of USG was 94.3%. The positive predictive value of MRI was 95.2%, while the positive predictive value of USG was 87.5%. The negative predictive value of MRI was 98.7%, while the negative predictive value of USG was 94.3%.
 Conclusion: MRI is recommended as the primary imaging method for detecting breast cancer in female patients. Ultrasound can be used as a complementary method to MRI.

The mechanics of congenital heart disease: from a morphological trait to the functional echocardiographic evaluation.

Advances in pediatric cardiac surgery have resulted in a recent growing epidemic of children and young adults with congenital heart diseases (CHDs). In these patients, congenital defects themselves, surgical operations and remaining lesions may alter cardiac anatomy and impact the mechanical performance of both ventricles. Cardiac function significantly influences outcomes in CHDs, necessitating regular patient follow-up to detect clinical changes and relevant risk factors. Echocardiography remains the primary imaging method for CHDs, but clinicians must understand patients' unique anatomies as different CHDs exhibit distinct anatomical characteristics affecting cardiac mechanics. Additionally, the use of myocardial deformation imaging and 3D echocardiography has gained popularity for enhanced assessment of cardiac function and anatomy. This paper discusses the role of echocardiography in evaluating cardiac mechanics in most significant CHDs, particularly its ability to accommodate and interpret the inherent anatomical substrate in these conditions.

B-Mode Sonography Versus Color Doppler Twinkling Artifact in the Diagnosis of Nephrolithiasis

Background: Nephrolithiasis, or kidney stones, is a prevalent condition that prompts numerous patient visits to emergency departments worldwide. The diagnosis of this condition and its complications, such as hydronephrosis, has traditionally relied on various imaging modalities, with ultrasound being a primary, non-invasive option. Recent advancements, including the utilization of the color Doppler twinkling artifact, have potentially enhanced the diagnostic capabilities of ultrasound for nephrolithiasis. Objective: This study aims to evaluate the effectiveness of B-mode sonography and the color Doppler twinkling artifact in the diagnosis of nephrolithiasis and to compare their sensitivity in detecting renal stones and associated hydronephrosis. Methods: A cross-sectional study was conducted at the Department of Radiology, Mahaban Medical and Research Hospital, Topi, Pakistan, from December 2023 to March 2024. Seventy patients presenting with flank pain and aged above 18 years were enrolled. Sonographic examinations were performed using a TOSHIBA Xario Prime ultrasound machine. Data were analyzed using SPSS version 25.0, focusing on the presence of renal stones and hydronephrosis as detected by B-mode sonography and the color Doppler twinkling artifact. Results: Of the 70 patients studied, renal stones were detected in 70% (n=49) via the color Doppler twinkling artifact, while 30% (n=21) showed no stones. Hydronephrosis was observed in 30% (n=21) of patients, with an equal distribution between the left and right kidneys. The mean age of participants was 34.56 years, with a gender distribution of 62.9% male and 37.1% female. The twinkling artifact demonstrated a 100% sensitivity in identifying renal calculi among patients presenting with flank pain. Conclusion: The color Doppler twinkling artifact, when used alongside B-mode sonography, provides a highly sensitive diagnostic tool for nephrolithiasis, underscoring its potential as a primary imaging modality in the evaluation of patients with suspected renal stones. This study highlights the importance of ultrasound in the early detection and management of kidney stones, offering significant implications for improving patient care in healthcare settings lacking advanced imaging technologies.

Early features of pancreatic cancer on magnetic resonance imaging (MRI): a case-control study.

Magnetic resonance imaging has been recommended as a primary imaging modality among high-risk individuals undergoing screening for pancreatic cancer. We aimed to delineate potential precursor lesions for pancreatic cancer on MR imaging. We conducted a case-control study at Kaiser Permanente Southern California (2008-2018) among patients that developed pancreatic cancer who had pre-diagnostic MRI examinations obtained 2-36months prior to cancer diagnosis (cases) matched 1:2 by age, gender, race/ethnicity, contrast status and year of scan (controls). Patients with history of acute/chronic pancreatitis or prior pancreatic surgery were excluded. Images underwent blind review with assessment of a priori defined series of parenchymal and ductal features. We performed logistic regression to assess the associations between individual factors and pancreatic cancer. We further assessed the interaction among features as well as performed a sensitivity analysis stratifying based on specific time-windows (2-3months, 4-12months, 13-36months prior to cancer diagnosis). We identified 141 cases (37.9% stage I-II, 2.1% III, 31.4% IV, 28.6% unknown) and 292 matched controls. A solid mass was noted in 24 (17%) of the pre-diagnostic MRI scans. Compared to controls, pre-diagnostic images from cancer cases more frequently exhibited the following ductal findings: main duct dilatation (51.4% vs 14.3%, OR [95% CI]: 7.75 [4.19-15.44], focal pancreatic duct stricture with distal (upstream) dilatation (43.6% vs 5.6%, OR 12.71 [6.02-30.89], irregularity (42.1% vs 6.0%, OR 9.73 [4.91-21.43]), focal pancreatic side branch dilation (13.6% vs1.6%, OR 11.57 [3.38-61.32]) as well as parenchymal features: atrophy (57.9% vs 27.4%, OR 46.4 [2.71-8.28], focal area of signal abnormality (39.3% vs 4.8%, OR 15.69 [6.72-44,78]), all p < 0.001). In addition to potential missed lesions, we have identified a series of ductal and parenchymal features on MRI that are associated with increased odds of developing pancreatic cancer.

A Comprehensive Review of Machine Learning Techniques for Pneumonia Detection from Chest X-ray Images

Pneumonia, a significant contributor to global respiratory illnesses, demands prompt diagnosis for successful treatment. Chest X-rays, being widely accessible and cost-effective, serve as the primary imaging modality for pneumonia detection. However, manual interpretation of chest X-rays is subjective and susceptible to errors due to the often subtle and diverse visual indicators of pneumonia. This study delves into the potential of deep learning, a subfield of artificial intelligence, to automate pneumonia detection utilizing chest X-ray images. By leveraging the well-established VGG-16 model, a convolutional neural network architecture renowned for its image recognition capabilities, the study aims to develop a robust and accurate classification system. This system, if successful, has the potential to alleviate the burden on healthcare professionals by assisting in the timely and efficient detection of pneumonia, ultimately contributing to improved patient outcomes. Key Words: Deep Learning, VGG16, CNN, Pneumonia, Chest X-rays .

Hemodynamic property incorporated brain tumor segmentation by deep learning and density-based analysis of dynamic susceptibility contrast-enhanced magnetic resonance imaging (MRI).

Magnetic resonance imaging (MRI) is a primary non-invasive imaging modality for tumor segmentation, leveraging its exceptional soft tissue contrast and high resolution. Current segmentation methods typically focus on structural MRI, such as T1-weighted post-contrast-enhanced or fluid-attenuated inversion recovery (FLAIR) sequences. However, these methods overlook the blood perfusion and hemodynamic properties of tumors, readily derived from dynamic susceptibility contrast (DSC) enhanced MRI. This study introduces a novel hybrid method combining density-based analysis of hemodynamic properties in time-dependent perfusion imaging with deep learning spatial segmentation techniques to enhance tumor segmentation. First, a U-Net convolutional neural network (CNN) is employed on structural images to delineate a region of interest (ROI). Subsequently, Hierarchical Density-Based Scans (HDBScan) are employed within the ROI to augment segmentation by exploring intratumoral hemodynamic heterogeneity through the investigation of tumor time course profiles unveiled in DSC MRI. The approach was tested and evaluated using a cohort of 513 patients from the open-source University of Pennsylvania glioblastoma database (UPENN-GBM) dataset, achieving a 74.83% Intersection over Union (IoU) score when compared to structural-only segmentation. The algorithm also exhibited increased precision and localized predictions of heightened segmentation boundary complexity, resulting in a 146.92% increase in contour complexity (ICC) compared to the reference standard provided by the UPENN-GBM dataset. Importantly, segmenting tumors with the developed new approach uncovered a negative correlation of the tumor volume with the scores in the Karnofsky Performance Scale (KPS) clinically used for assessing the functional status of patients (-0.309), which is not observed with the prevailing segmentation standard. This work demonstrated that including hemodynamic properties of tissues from DSC MRI can improve existing structural or morphological feature-based tumor segmentation techniques with additional information on tumor biology and physiology. This approach can also be applied to other clinical indications that use perfusion MRI for diagnosis or treatment monitoring.

Microvascular imaging findings in infants with bacterial meningitis: a case series.

Bacterial meningitis is a severe and life-threatening disease that rapidly progresses in neonates and infants; prompt diagnosis and appropriate treatment are lifesaving. Magnetic resonance imaging remains the primary imaging technique for diagnosing meningitis; however, due to its limited availability and cost, ultrasound is often used for initial screening. Microvascular imaging ultrasound (MVI) is an emerging technique that offers insight into the brain microvasculature beyond conventional ultrasound. Here we present three patients with confirmed bacterial meningitis and associated cerebral microvascular findings on brain MVI to instigate further validation of cerebral microvascular imaging markers of bacterial meningitis for early detection and intervention.

Abstract 2310: Integrating real-world histopathological and clinicogenomic data from 1799 lung cancer patients by applying unsupervised deep learning

Abstract Hematoxylin and eosin (H&amp;E) stained histologic sections contain invaluable information that remains largely untapped because of its complexity. To this end, AI applications employing deep learning (DL) can facilitate the translation of image data to enable human interpretation and yield novel oncological insights that would have otherwise remained imperceptible. DL-based methodologies are multimodal, capable of integrating imaging with clinicogenomic data to furnish a more holistic perspective and affording more accurate predictions in oncology. Here, we developed an unsupervised DL workflow to analyze 1,799 H&amp;E images of lung cancer (NSCLC n = 951; SCLC n = 50; others n = 798) incorporating comprehensive patient-level clinical data (electronic health records [ConcertAI]) integrated with genomics (WES and RNA-seq [Caris Labs]). There are three steps in our approach: (1) image preprocessing and filtering, yielding &amp;gt; 30 million image patches; (2) utilizing pretrained SimCLR models from 57 public oncology histopathology datasets with ResNet-18 as a backbone structure to extract 512-dimensional-feature vectors for each patch; (3) using three unsupervised clustering methods (kmeans, DBSCAN, Leiden clustering) to cluster patches and selected Leiden clustering. We identified 635 primary imaging clusters using an elbow method and generated an image feature matrix by calculating correlations between each patch and cluster centroids; these were aggregated and mapped back to source slides. In this proof-of-concept, distinct image feature patterns characterized SCLC and NSCLC samples. For SCLC, one of the salient features was the presence of hemorrhage, which may be associated with higher rates of fine-needle aspiration biopsy procedure for SCLC compared with NSCLC which was confirmed in the EHR data (p = 0.032). Derived morphological clusters were correlated with tumor-immune genomic features (Tumor Mutational Burden [TMB], Immunologic Constant of Rejection [ICR], and Miracle scores1) serving as predictors of response to immune-checkpoint inhibitor therapy. By applying linear models, we detected 11, 96 and 249 significantly associated imaging clusters, respectively, highly enriched with immune cells e.g., plasma cells, macrophages, lymphocytes, and supporting an infiltrated and inflamed tumor-immune microenvironment. In summary, a multimodal, unsupervised deep learning workflow combining H&amp;E imaging with clinicogenomic data was developed to identify histologic feature clusters associated with well-established tumor-immune genomic signatures of NSCLC immune infiltration and molecular phenotypes. These studies demonstrate enormous potential to yield histopathological and translational insights in NSCLC and SCLC that can empower clinicians to make better therapeutic response predictions. Citation Format: Si Wu, Yujie Zhao, Hugo Luo, Kevin Kolahi, Thanh Bui, Xu Shi, Aditee Shrotre, Alexander Liede, Xi Zhao, Josue Samayoa, Weilong Zhao. Integrating real-world histopathological and clinicogenomic data from 1799 lung cancer patients by applying unsupervised deep learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2310.

A3C: An Image-Association-Based Computing Device Authentication Framework for People with Upper Extremity Impairments

Current computing device authentication often presents accessibility barriers for people with upper extremity impairments (UEI). In this paper, we present a framework called Accessible image-Association-based Authentication for Computing-devices (A3C) , a novel recognition-based graphical authentication framework specifically designed for people with UEI to authenticate to their computing devices. A3C requires users to provide a set of primary images that the user knows that are recognizable to them and subsequently associate each primary image with a secondary image. To evaluate the efficacy of the A3C framework, we instantiated the framework by implementing a version of A3C called A3C-FA , which uses images of faces of people the user knows as the primary image and animal images as the secondary image. We then performed three studies to evaluate A3C-FA: a shoulder-surfing attack study ( N=319 ), a close-adversary attack study ( N=268 ), and a usability study with people with UEI ( N=14 ). We found that A3C was robust against both shoulder-surfing and close-adversary attacks. We also performed a detailed study to evaluate the accessibility of A3C-FA. Our participants reported that A3C-FA was more usable and more secure than the authentication approaches with which they were familiar. Based on these findings, we suggest four areas of future research to further improve the design of A3C framework.

The Role of Cardiovascular Magnetic Resonance Imaging in the Assessment of Mitral Regurgitation.

Mitral regurgitation (MR), a primary cause of valvular disease in adults, affects millions and is growing due to an ageing population. Cardiovascular magnetic resonance (CMR) has emerged as an essential tool, offering insights into valvular and myocardial pathology when compared to the primary imaging modality, echocardiography. This review highlights CMR's superiority in high-resolution volumetric assessment and tissue characterization, including also advanced techniques like late gadolinium enhancement imaging, parametric mapping, feature tracking and 4D flow analysis. These techniques provide a deeper understanding of MR's pathophysiology and its effect on cardiac chambers, enabling CMR to surpass echocardiography in predicting hard clinical outcomes and left ventricular (LV) remodelling post mitral valve surgery. Despite its advantages, CMR's application faces limitations like cost, lack of standardization, and susceptibility to arrhythmia artifacts. Nonetheless, as technological advancements continue and new evidence emerges, CMR's role in MR assessment is set to expand, offering a more nuanced and personalized approach to cardiac care. This review emphasizes the need for further research and standardized protocols to maximize CMR's potential in MR management.

Somatostatin receptor imaging of thyroid tissue and differentiated thyroid cancer using gallium-68-labeled radiotracers-a review of clinical studies.

The rise in thyroid cancer incidence, especially papillary thyroid cancer (PTC), has underscored the need for improved diagnostic methods and management strategies. Herein, we aim to comprehensively review the evolving landscape in thyroid cancer diagnosis and the potential utility of Gallium-68 (Ga-68) based somatostatin receptor imaging. We reviewed the clinical studies involving Ga-68 based radiotracers by looking at the following literature databases -PUBMED, EMBASE, WEB OF SCIENCE and COCHRANE. We employed a detailed search strategy with the following search terms; PubMed: ("gallium Ga 68 dotatate" [Supplementary Concept]) AND ("Thyroid Gland"[Mesh] OR "Thyroid Nodule"[Mesh] OR "Thyroid Neoplasms"[Mesh]), Embase ("gallium 68" AND "Thyroid Disease"), Web of Science: ("Gallium 68 and Thyroid"). A comparison between Ga-68 DOTATATE and Ga-68 DOTANOC showed similar sensitivities but a higher uptake for Ga-68 DOTATATE. Studies comparing Ga-68-based SSTR PET with FDG PET highlighted the potential advantages of both approaches, with Ga-68-based SSTR PET being more specific in certain cases. Ga-68-based somatostatin receptor imaging displays clinical utility in RAI-R DTC, offering valuable insight into detecting skeletal lymph node metastases. Notably, it shows potential as a primary imaging tool, potentially augmenting the role of FDG PET. However, SSTR PET imaging's efficacy in distinguishing benign from malignant thyroid nodules varies, with a complex interplay of factors influencing its specificity, indicating its value as an adjunct to existing methods, warranting further research for a refined role in thyroid cancer management. Although study variations exist, Ga-based somatostatin receptor imaging holds potential as a complementary tool alongside diagnostic methods in thyroid cancer diagnosis, with particular relevance to RAI-R DTC. In carefully selected patients demonstrating the presence of Ga-68 DOTATATE avid lesions, further exploration, and investigation into the potential utilization of Lu177 DOTATATE are warranted.

Arterial spin labeled perfusion MRI for the assessment of radiation-treated meningiomas.

Conventional contrast-enhanced MRI is currently the primary imaging technique used to evaluate radiation treatment response in meningiomas. However, newer perfusion-weighted MRI techniques, such as 3D pseudocontinuous arterial spin labeling (3D pCASL) MRI, capture physiologic information beyond the structural information provided by conventional MRI and may provide additional complementary treatment response information. The purpose of this study is to assess 3D pCASL for the evaluation of radiation-treated meningiomas. Twenty patients with meningioma treated with surgical resection followed by radiation, or by radiation alone, were included in this retrospective single-institution study. Patients were evaluated with 3D pCASL and conventional contrast-enhanced MRI before and after radiation (median follow up 6.5 months). Maximum pre- and post-radiation ASL normalized cerebral blood flow (ASL-nCBF) was measured within each meningioma and radiation-treated meningioma (or residual resected and radiated meningioma), and the contrast-enhancing area was measured for each meningioma. Wilcoxon signed-rank tests were used to compare pre- and post-radiation ASL-nCBF and pre- and post-radiation area. All treated meningiomas demonstrated decreased ASL-nCBF following radiation (p < 0.001). Meningioma contrast-enhancing area also decreased after radiation (p = 0.008) but only for approximately half of the meningiomas (9), while half (10) remained stable. A larger effect size (Wilcoxon signed-rank effect size) was seen for ASL-nCBF measurements (r = 0.877) compared to contrast-enhanced area measurements (r = 0.597). ASL perfusion may provide complementary treatment response information in radiation-treated meningiomas. This complementary information could aid clinical decision-making and provide an additional endpoint for clinical trials.

Immediate and delayed risk of breast cancer associated with classic lobular carcinoma in situ and its variants.

To determine the risk of breast cancer due to lobular carcinoma in situ (LCIS). This retrospective IRB-approved study identified cases of LCIS after percutaneous breast biopsy from 7/2005 to 7/2022. Excluded were cases with less than 2years of imaging surveillance or a concurrent ipsilateral breast cancer diagnosis within 6months of the LCIS diagnosis. Final outcomes of cancer versus no cancer were determined by pathology at surgical excision or the absence of cancer on imaging surveillance. A total of 116 LCIS lesions were identified. The primary imaging findings targeted for percutaneous biopsy included calcifications (50.0%, 58/116), MR enhancing lesions (25.0%, 29/116), noncalcified mammographic architectural distortions (10.3%, 12/116), or masses (14.7%, 17/116). Surgical excision was performed in 49.1% (57/116) and imaging surveillance was performed in 50.9% (59/116) of LCIS cases. There were 22 cancers of which 11 cancers were discovered at immediate excision [19.3% (11/57) immediate upgrade] and 11 cancers developed later while on imaging surveillance [18.6% (11/59) delayed risk for cancer]. Among all 22 cancers, 63.6% (14/22) occurred at the site of LCIS (11 at immediate excision and 3 at surveillance) and 36.4% (8/22) occurred at a location away from the site of LCIS (6 in a different quadrant and 2 in the contralateral breast). LCIS has both an immediate risk (19.3%) and a delayed risk (18.6%) for cancer with 90.9% occurring in the ipsilateral breast (63.6% at and 27.3% away from the site of LCIS) and 9.1% occurring in the contralateral breast.

Current Trends and Applications of PET/MRI Hybrid Imaging in Neurodegenerative Diseases and Normal Aging.

Dementia is a significant global health issue that is exacerbated by an aging population. Imaging plays an established role in the evaluation of patients with neurocognitive disorders such as dementia. In current clinical practice, magnetic resonance imaging (MRI) and positron emission tomography (PET) are primary imaging modalities used separately but in concert to help diagnose and classify dementia. The clinical applications of PET/MRI hybrid imaging in dementia are an active area of research, particularly given the continued emergence of functional MRI (fMRI) and amyloid PET tracers. This narrative review provides a comprehensive overview of the rationale and current evidence for PET/MRI hybrid dementia imaging from 2018 to 2023. Hybrid imaging offers advantages in the accuracy of characterizing neurodegenerative disorders, and future research will need to address the cost of integrated PET/MRI systems compared to stand-alone scanners, the development of new biomarkers, and image correction techniques.