Purpose: Tumor associated macrophages (TAM) in malignant tumors have been linked to tumor aggressiveness and represent a new target for cancer immunotherapy. As new TAM-targeted immunotherapies are entering clinical trials, it is important to detect and quantify TAM with non-invasive imaging techniques. The purpose of this study was to determine if ferumoxytol-enhanced MRI can detect TAM in lymphomas and bone sarcomas of pediatric patients and young adults. Experimental Design: In a first-in-patient, IRB-approved prospective clinical trial, 25 pediatric and young adult patients with lymphoma or bone sarcoma underwent ferumoxytol-enhanced MRI. To confirm ferumoxytol enhancement, five pilot patients (2 lymphoma, 3 bone sarcoma) underwent pre- and post-contrast MRI. Subsequently, 20 patients (10 lymphoma, 10 bone sarcoma) underwent ferumoxytol-enhanced MRI 24-48 hours after intravenous injection, followed by tumor biopsy/resection and macrophage staining. To determine if ferumoxytol-MRI can differentiate tumors with different TAM content, we compared T2* relaxation times of lymphomas and bone sarcomas. Tumor T2* values of 20 patients were correlated with CD68+ and CD163+ TAM quantities on histopathology. Results: Significant ferumoxytol tumor enhancement was noted on post-contrast scans compared to pre-contrast scans (P = 0.036). Bone sarcomas and lymphomas demonstrated significantly different MRI enhancement and TAM density (P < 0.05). Within each tumor group, T2* signal enhancement on MR images correlated significantly with the density of CD68+ and CD163+ TAM (P < 0.05). Conclusions: Ferumoxytol-enhanced MRI is immediately clinically applicable and could be used to stratify patients with TAM-rich tumors to immune-targeted therapies and to monitor tumor response to these therapies.

OBJECTIVE. New MRI sequences based on rapid radial acquisition have reduced gradient noise. The purpose of this study was to compare Silent T1-weighted and unenhanced MR angiography (MRA) against conventional sequences in a clinical population. MATERIALS AND METHODS. The study cohort consisted of 40 patients with suspected brain metastases (median age, 60 years; range, 23–91 years) who underwent T1-weighted contrast-enhanced MRI and 51 patients with suspected vascular lesions or cerebral ischemia (median age, 60 years; range, 16–94 years) who underwent unenhanced intracranial MRA. Three neuroradiologists reviewed the images blindly and rated several measures of image quality on a 5-point Likert scale. Reviewers recorded the number of enhancing lesions and whether Silent images were better than, worse than, or equivalent to conventional images. RESULTS. For T1-weighted MR images, ratings were slightly lower for Silent versus conventional images, except for diagnostic confidence. Although more lesions were ...

Purpose: Amplified MRI (aMRI) has been introduced as a new method of detecting and visualizing pulsatile brain motion in 2D. Here, we improve aMRI by introducing a novel 3D aMRI approach.Methods: 3D aMRI was developed and tested for its ability to amplify sub‐voxel motion in all three directions. In addition, 3D aMRI was qualitatively compared to 2D aMRI on multi‐slice and 3D (volumetric) balanced steady‐state free precession cine data and phase contrast (PC‐MRI) acquired on healthy volunteers at 3T. Optical flow maps and 4D animations were produced from volumetric 3D aMRI data.Results: 3D aMRI exhibits better image quality and fewer motion artifacts compared to 2D aMRI. The tissue motion was seen to match that of PC‐MRI, with the predominant brain tissue displacement occurring in the cranial‐caudal direction. Optical flow maps capture the brain tissue motion and display the physical change in shape of the ventricles by the relative movement of the surrounding tissues. The 4D animations show the complete brain tissue and cerebrospinal fluid (CSF) motion, helping to highlight the “piston‐like” motion of the ventricles.Conclusions: Here, we introduce a novel 3D aMRI approach that enables one to visualize amplified cardiac‐ and CSF‐induced brain motion in striking detail. 3D aMRI captures brain motion with better image quality than 2D aMRI and supports a larger amplification factor. The optical flow maps and 4D animations of 3D aMRI may open up exciting applications for neurological diseases that affect the biomechanics of the brain and brain fluids.

Background: CT scans are often the first and only form of brain imaging that is performed to inform treatment plans for neurological patients due to its time- and cost-effective nature. However, MR images give a more detailed picture of tissue structure and characteristics and are more likely to pick up abnormalities and lesions. The purpose of this paper is to review studies which use deep learning methods to generate synthetic medical images of modalities such as MRI and CT. Methods: A literature search was performed in March 2023, and relevant articles were selected and analyzed. The year of publication, dataset size, input modality, synthesized modality, deep learning architecture, motivations, and evaluation methods were analyzed. Results: A total of 103 studies were included in this review, all of which were published since 2017. Of these, 74% of studies investigated MRI to CT synthesis, and the remaining studies investigated CT to MRI, Cross MRI, PET to CT, and MRI to PET. Additionally, 58% of studies were motivated by synthesizing CT scans from MRI to perform MRI-only radiation therapy. Other motivations included synthesizing scans to aid diagnosis and completing datasets by synthesizing missing scans. Conclusions: Considerably more research has been carried out on MRI to CT synthesis, despite CT to MRI synthesis yielding specific benefits. A limitation on medical image synthesis is that medical datasets, especially paired datasets of different modalities, are lacking in size and availability; it is therefore recommended that a global consortium be developed to obtain and make available more datasets for use. Finally, it is recommended that work be carried out to establish all uses of the synthesis of medical scans in clinical practice and discover which evaluation methods are suitable for assessing the synthesized images for these needs.