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Abstractβ1-adrenergic receptors (β1-AR) are internalized in response to agonists and then recycle back for another round of signaling. The serine 312 to alanine mutant of the β1-AR (S312A) is internalized but does not recycle. We determined that WT β1-AR and S312A were internalized initially to an early sorting compartment because they colocalized by >70% with the early endosomal markers rab5a and early endosomal antigen-1 (EEA1). Subsequently, the WT β1-AR trafficked via rab4a-expressing sorting endosomes to recycling endosomes. In recycling endosomes WT β1-AR were colocalized by >70% with the rab11 GTPase. S312A did not colocalize with either rab4a or rab11, instead they exited from early endosomes to late endosomes/lysosomes in which they were degraded. Rab11a played a prominent role in recycling of the WT β1-AR because dominant negative rab11a inhibited, while constitutively active rab11a accelerated the recycling of the β1-AR. Next, we determined the effect of each of the rab11-intercating proteins on trafficking of the WT β1-AR. The recycling of the β1-AR was markedly inhibited when myosin Vb, FIP2, FIP3 and rabphillin were knocked down. These data indicate that rab11a and a select group of its binding partners play a prominent role recycling of the human β1-AR.

Computational tools are beginning to enable patient-specific surgical planning to localize and prescribe thermal dosing for liver cancer ablation therapy. Tissue-specific factors (e.g., tissue perfusion, material properties, disease state, etc.) have been found to affect ablative therapies, but current thermal dosing guidance practices do not account for these differences. Computational modeling of ablation procedures can integrate these sources of patient specificity to guide therapy planning and delivery. This paper establishes an imaging-data-driven framework for patient-specific biophysical modeling to predict ablation extents in livers with varying fat content in the context of microwave ablation (MWA) therapy. Patient anatomic scans were segmented to develop customized three-dimensional computational biophysical models and mDIXON fat-quantification images were acquired and analyzed to establish fat content and determine biophysical properties. Simulated patient-specific microwave ablations of tumor and healthy tissue were performed at four levels of fatty liver disease. Ablation models with greater fat content demonstrated significantly larger treatment volumes compared to livers with less severe disease states. More specifically, the results indicated an eightfold larger difference in necrotic volumes with fatty livers vs. the effects from the presence of more conductive tumor tissue. Additionally, the evolution of necrotic volume formation as a function of the thermal dose was influenced by the presence of a tumor. Fat quantification imaging showed multi-valued spatially heterogeneous distributions of fat deposition, even within their respective disease classifications (e.g., low, mild, moderate, high-fat). Altogether, the results suggest that clinical fatty liver disease levels can affect MWA, and that fat-quantitative imaging data may improve patient specificity for this treatment modality.

Fibrolipomatous hamartoma (FLH) is a rare, benign lesion of the peripheral nerves most frequently involving the median nerve and its digital branches (80 %). Pathognomonic MR features of FLH such as coaxial-cable-like appearance on axial planes and a spaghetti-like appearance on coronal planes have been described by Marom and Helms, obviating the need for diagnostic biopsy. We present a case of fibrolipomatous hamartoma of the inferior calcaneal nerve (Baxter nerve) with associated subcutaneous fat proliferation.

Computational tools, such as "digital twin" modeling, are beginning to enable patient-specific surgical planning of ablative therapies to treat hepatocellular carcinoma. Digital twins models use patient functional data and biomarker imaging to build anatomically accurate models to forecast therapeutic outcomes through simulation, i.e., providing accurate information for guiding clinical decision-making. In microwave ablation (MWA), tissue-specific factors (e.g., tissue perfusion, material properties, disease state, etc.) can affect ablative therapies, but current thermal dosing guidelines do not account for these differences. This study establishes an imaging-data-driven framework to construct digital twin biophysical models to predict ablation extents in livers with varying fat content in MWA. Patient anatomic scans were segmented to develop customized three-dimensional computational biophysical models, and fat-quantification images were acquired to reconstruct spatially accurate biophysical material properties. Simulated patient-specific microwave ablations of homogenous digital-twin models (control) and enhanced digital twin models were performed at four levels of fatty liver disease. When looking at the short diameter (SD), long diameter (LD), ablation volume, and spherical index of the ablation margins -the heterogenous digital-twin models did not produce significantly different ablation margins compared to the control models. Both models produced results that report ablation margins for patients with high-fat livers are larger than low-fat livers (LD of 6.17cm vs. 6.30cm and SD of 2.10 vs. 1.99, respectively). Overall, the results suggest that modeling heterogeneous clinical fatty liver disease using fat-quantitative imaging data has the potential to improve patient specificity for this treatment modality.

Abdominal radiologists are often asked to perform difficult percutaneous chest, abdomen, and pelvis biopsies and drainages with imaging guidance. Many of these procedures involve small target lesions far from the skin surface, in close proximity to critical structures. Organ location is changeable due to respiration, peristalsis, and pulsation, further complicating the planning process. High-level three-dimensional spatial awareness is critical to mastery of complex image-guided procedures. A comprehensive grasp of anatomy and expected changes can be exploited in certain cases to target lesions within a solid organ or to avoid injury to sensitive structures during biopsy, drain placement, or thermal ablation. In this article, we will use illustrative cases to explore the use of anatomic knowledge and the ability to synthesize this three-dimensional data dynamically during planning and execution of difficult CT- and ultrasound-guided procedures. We will discuss unusual biopsy requests-such as bowel biopsies-and the benefits of using ultrasound guidance for certain procedures in the chest. Additionally, we will describe multiple special techniques, including out of standard plane angulation and endocavitary techniques, in order to maximize chances of success.

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