Novel anti-neoplastic agents such as gene targeting vectors and encapsulated carriers are quite large (approximately 100-300 nm in diameter). An understanding of the functional size and physiological regulation of transvascular pathways is necessary to optimize delivery of these agents. Here we analyze the functional limits of transvascular transport and its modulation by the microenvironment. One human and five murine tumors including mammary and colorectal carcinomas, hepatoma, glioma, and sarcoma were implanted in the dorsal skin-fold chamber or cranial window, and the pore cutoff size, a functional measure of transvascular gap size, was determined. The microenvironment was modulated: (i) spatially, by growing tumors in subcutaneous or cranial locations and (ii) temporally, by inducing vascular regression in hormone-dependent tumors. Tumors grown subcutaneously exhibited a characteristic pore cutoff size ranging from 200 nm to 1.2 m. This pore cutoff size was reduced in tumors grown in the cranium or in regressing tumors after hormone withdrawal. Vessels induced in basic fibroblast growth factor-containing gels had a pore cutoff size of 200 nm. Albumin permeability was independent of pore cutoff size. These results have three major implications for the delivery of therapeutic agents: (i) delivery may be less efficient in cranial tumors than in subcutaneous tumors, (ii) delivery may be reduced during tumor regression induced by hormonal ablation, and (iii) permeability to a molecule is independent of pore cutoff size as long as the diameter of the molecule is much less than the pore diameter.

The ribs are frequently affected by blunt or penetrating injury to the thorax. In the emergency department setting, it is vital for the interpreting radiologist to not only identify the presence of rib injuries but also alert the clinician about organ-specific injury, specific traumatic patterns, and acute rib trauma complications that require emergent attention. Rib injuries can be separated into specific morphologic fracture patterns that include stress, buckle, nondisplaced, displaced, segmental, and pathologic fractures. Specific attention is also required for flail chest and for fractures due to pediatric nonaccidental trauma. Rib fractures are associated with significant morbidity and mortality, both of which increase as the number of fractured ribs increases. Key complications associated with rib fracture include pain, hemothorax, pneumothorax, extrapleural hematoma, pulmonary contusion, pulmonary laceration, acute vascular injury, and abdominal solid-organ injury. Congenital anomalies, including supernumerary or accessory ribs, vestigial anterior ribs, bifid ribs, and synostoses, are common and should not be confused with traumatic pathologic conditions. Nontraumatic mimics of traumatic rib injury, with or without fracture, include metastatic disease, primary osseous neoplasms (osteosarcoma, chondrosarcoma, Ewing sarcoma, Langerhans cell histiocytosis, and osteochondroma), fibrous dysplasia, and Paget disease. Principles of management include supportive and procedural methods of alleviating pain, treating complications, and stabilizing posttraumatic deformity. By recognizing and accurately reporting the imaging findings, the radiologist will add value to the care of patients with thoracic trauma. Online supplemental material is available for this article. RSNA, 2017.

No abstract

Purpose: To investigate the correlation between gadolinium contrast-enhancement patterns on T1-weighted magnetic resonance (MR) images and spatial changes in protein expression profiles in human glioblastoma multiforme (GBM) and the use of imaging as a noninvasive technique to evaluate the heterogeneity of solid tumors prior to microarray analysis. Materials and Methods:Four patients with MR images and confirmed diagnosis of GBM were enrolled in the study. Intraoperative stereotaxy was used in conjunction with MR images to identify contrast-enhanced (CE) and nonenhanced (NE) regions of the tumor during surgical resection. Total protein was extracted from resected tumor samples using standard techniques and subjected to proteomic analysis using surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS). Results:We found that protein profiles from CE and NE regions within a given tumor have qualitative and semiquantitative proteomic pattern differences, suggesting an altered gene expression profile that correlates with detectable tissue imaging parameters. We also found that CE regions within the same tumor exhibited distinct differences in protein expression profiles, despite similar histological features. In addition, there were marked similarities in the proteomic patterns among the NE regions across all patients, while the CE regions were distinct, suggesting that the CE regions have complex protein profiles unique to individuals. Conclusion:The results demonstrate that major differences in protein expression patterns within a tumor can be correlated to radiographic findings. Image-guided proteomics holds promise for characterizing tissue prior to microarray analysis designed to identify specific diagnostic markers and therapeutic targets within solid tumors.

Familiarity with the basic pulse sequences, imaging planes, and anatomy pertaining to cardiac MRI is essential to formulate optimal protocols and interpretations.

The large airways can be affected by a wide spectrum of acquired benign and malignant diseases. These lesions may present as focal or diffuse processes and with narrowing or widening of the airway. Some of these may be asymptomatic for quite some time and may be incidentally detected on imaging, while others may be symptomatic, causing airway compromise. There may be a characteristic radiograph and computed tomography (CT) appearance, suggesting a narrow differential. When the imaging findings are not definitive, tissue may be obtained for pathological analysis. It behooves the radiologist to be familiar with the pathologic findings that correlate with the radiographic or CT appearance of the most frequently seen large airway lesions. In this way, we may improve our diagnostic accuracy. This paper will present the imaging findings of the most prevalent tracheobronchial lesions along with any associated pathology.Teaching Points• The large airways can be affected by many acquired benign and malignant diseases.• Large airway lesions may present as focal or diffuse processes, with narrowing or widening.• There may or may not be characteristic imaging appearance of large airway disease.• If imaging findings are not definitive, tissue may be obtained for pathological analysis.

No abstract

We explore a computational framework for functional connectivity analysis in resting-state functional MRI (fMRI) data acquired from the human brain for recovering the underlying network structure and understanding causality between network components. Termed mutual connectivity analysis (MCA), this framework involves two steps, the first of which is to evaluate the pair-wise cross-prediction performance between fMRI pixel time series within the brain. In a second step, the underlying network structure is subsequently recovered from the affinity matrix using non-metric network clustering approaches, such as the so-called Louvain method. Finally, we use convergent cross-mapping (CCM) to study causality between different network components. We demonstrate our MCA framework in the problem of recovering the motor cortex network associated with hand movement from resting state fMRI data. Results are compared with a ground truth of active motor cortex regions as identified by a task-based fMRI sequence involving a finger-tapping stimulation experiment. Our results regarding causation between regions of the motor cortex revealed a significant directional variability and were not readily interpretable in a consistent manner across subjects. However, our results on whole-slice fMRI analysis demonstrate that MCA-based model-free recovery of regions associated with the primary motor cortex and supplementary motor area are in close agreement with localization of similar regions achieved with a task-based fMRI acquisition. Thus, we conclude that our MCA methodology can extract and visualize valuable information concerning the underlying network structure between different regions of the brain in resting state fMRI.