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Leveraging ultra-high field (7T) MRI in psychiatric research.

Non-invasive brain imaging has played a critical role in establishing our understanding of the neural properties that contribute to the emergence of psychiatric disorders. However, characterizing core neurobiological mechanisms of psychiatric symptomatology requires greater structural, functional, and neurochemical specificity than is typically obtainable with standard field strength MRI acquisitions (e.g., 3T). Ultra-high field (UHF) imaging at 7 Tesla (7T) provides the opportunity to identify neurobiological systems that confer risk, determine etiology, and characterize disease progression and treatment outcomes of major mental illnesses. Increases in scanner availability, regulatory approval, and sequence availability have made the application of UHF to clinical cohorts more feasible than ever before, yet the application of UHF approaches to the study of mental health remains nascent. In this technical review, we describe core neuroimaging methodologies which benefit from UHF acquisition, including high resolution structural and functional imaging, single (1H) and multi-nuclear (e.g., 31P) MR spectroscopy, and quantitative MR techniques for assessing brain tissue iron and myelin. We discuss advantages provided by 7T MRI, including higher signal- and contrast-to-noise ratio, enhanced spatial resolution, increased test-retest reliability, and molecular and neurochemical specificity, and how these have begun to uncover mechanisms of psychiatric disorders. Finally, we consider current limitations of UHF in its application to clinical cohorts, and point to ongoing work that aims to overcome technical hurdles through the continued development of UHF hardware, software, and protocols.

Regional Variability in MRI Scans with Different Magnetic Field Strengths in Japan: Implications for Healthcare Preparedness for Alzheimer's Disease Treatment.

(1) Background: The 2023 approval of lecanemab for early-stage Alzheimer's disease (AD) highlighted the need for routine 1.5T or 3.0T MRI scans to monitor amyloid-related imaging abnormalities (ARIAs). Regional disparities in MRI scan frequency, MRI scanner availability, and scanner magnetic field strengths could affect readiness for anti-amyloid therapy and lead to inconsistencies in ARIA detection nationwide. (2) Methods: We assessed regional variance in MRI scan frequency and field strength across Japan using the National Database (NDB) Open Data website, which summarizes Japanese public health insurance claims from the fiscal years (FYs) 2015 to 2021. We employed a mixed-effects model with prefecture-level random intercepts and slopes over time, subsequently categorizing prefectures into clusters based on MRI usage. (3) Results: 1.5T MRI was the most common magnetic field strength, remaining stable from FY2015 to FY2021. 3.0T MRI usage slightly increased, although the COVID-19 pandemic in FY2020 led to a maximum reduction of 5%. Prefecture-level variance was higher for 3.0T MRIs, with more frequent usage in western Japan. (4) Conclusions: This study highlights prefecture-level variance in MRI usage across Japan. The insights gained could be instrumental in improving healthcare preparedness for anti-amyloid treatment and patient management.

A scan-specific quality control acquisition for clinical whole-body (WB) MRI protocols

Objective. Image quality in whole-body MRI (WB-MRI) may be degraded by faulty radiofrequency (RF) coil elements or mispositioning of the coil arrays. Phantom-based quality control (QC) is used to identify broken RF coil elements but the frequency of these acquisitions is limited by scanner and staff availability. This work aimed to develop a scan-specific QC acquisition and processing pipeline to detect broken RF coil elements, which is sufficiently rapid to be added to the clinical WB-MRI protocol. The purpose of this is to improve the quality of WB-MRI by reducing the number of patient examinations conducted with suboptimal equipment. Approach. A rapid acquisition (14 s additional acquisition time per imaging station) was developed that identifies broken RF coil elements by acquiring images from each individual coil element and using the integral body coil. This acquisition was added to one centre’s clinical WB-MRI protocol for one year (892 examinations) to evaluate the effect of this scan-specific QC. To demonstrate applicability in multi-centre imaging trials, the technique was also implemented on scanners from three manufacturers. Main results. Over the course of the study RF coil elements were flagged as potentially broken on five occasions, with the faults confirmed in four of those cases. The method had a precision of 80% and a recall of 100% for detecting faulty RF coil elements. The coil array positioning measurements were consistent across scanners and have been used to define the expected variation in signal. Significance. The technique demonstrated here can identify faulty RF coil elements and positioning errors and is a practical addition to the clinical WB-MRI protocol. This approach was fully implemented on systems from two manufacturers and partially implemented on a third. It has potential to reduce the number of clinical examinations conducted with suboptimal hardware and improve image quality across multi-centre studies.

Survey on fan-beam computed tomography for radiotherapy: Imaging for dose calculation and delineation

Background and purposeTo obtain an understanding of current practice, professional needs and future directions in the field of fan-beam CT in RT, a survey was conducted. This work presents the collected information regarding the use of CT imaging for dose calculation and structure delineation. Materials and methodsAn online institutional survey was distributed to medical physics experts employed at Belgian and Dutch radiotherapy institutions to assess the status, challenges, and future directions of QA practices for fan-beam CT. A maximum of 143 questions covered topics such as CT scanner availability, CT scanner specifications, QA protocols, treatment simulation workflow, and radiotherapy dose calculation. Answer forms were collected between 1-Sep-2022 and 10-Oct-2022. ResultsA 66 % response rate was achieved, yielding data on a total of 58 CT scanners. For MV photon therapy, all single-energy CT scans are reconstructed in Hounsfield Units for delineation or dose calculation, and a direct- or stoichiometric method was used to convert CT numbers for dose calculation. Limited use of dual-energy CT is reported for photon (N = 3) and proton dose calculations (N = 1). For brachytherapy, most institutions adopt water-based dose calculation, while approximately 26 % of the institutions take tissue heterogeneity into account. Commissioning and regular QA include eleven tasks, which are performed by two or more professions (29/31) with varying frequencies. ConclusionsDual usage of a planning CT limits protocol optimization for both tissue characterization and delineation. DECT has been implemented only gradually. A variation of QA testing frequencies and tests are reported.

Abstract 228: Suboptimal Door‐to‐Puncture Times: Challenges Faced in the Stroke Alert Workflow

Introduction Advances in stroke care have led to more patients eligible for thrombectomy. With these advances, it has become imperative to create a seamless workflow for thrombectomy candidates to ensure rapid door‐to‐puncture times and, ultimately, improve patient outcomes. We sought to determine what barriers are causing delays in patients’ door‐to‐puncture time. Methods A survey was distributed to all members of the Neurology PGY2, PGY3, PGY4 classes and vascular fellows at our single‐center, Comprehensive Stroke Center. The survey allowed participants to freely respond to questions regarding obstacles they encountered that led to delays in door‐to‐puncture times. All survey responses were anonymized. Results The survey was sent to 32 participants, with 26 responses. Of the 26 responses, 11 respondents (42%) noted that obtaining IV access for CTA/CTP scans was a significant cause of delay. Other responses included lack of availability of family for collateral (23%), CT scanner availability (15%), and length of time to decide if the patient is a thrombectomy candidate (15%). Conclusion The goal of this study was to collect data from the individuals involved in the direct care of acute stroke patients who are thrombectomy candidates. We used their experience to determine which points in the stroke alert workflow led to delays in door‐to‐puncture time. Our survey showed the most consistent delay is obtaining proper IV access for CTA and CTP imaging. This information was valuable and has led to the creation of a coalition between the neurology and emergency medicine departments, nursing, and CT technologists to create a “CODE IV” protocol to be implemented into the stroke alert workflow. We aim to report the change in door‐to‐puncture time after the implementation of this new protocol.

National resident survey in dermatopathology: The role of slide scanners in resident learning.

Dermatology residents gain exposure to dermatopathology through a variety of educational modalities. While virtual pathology applications have risen dramatically, resident utilization of digital libraries, slide scanner availability, and comfort with virtual slides are not well-known. This study aims to assess the current landscape of educational resources used by dermatology residents. A 17-question survey was sent to dermatology residents through a national email database. The survey was a self-assessment of their experience in dermatopathology education and the use of departmental slide scanners. The use of digital dermatopathology is high among trainees, despite only half of respondents reporting slide scanner access. Residents report using virtual images more often in non-clinical dermatopathology didactics and independent studies compared to clinical dermatopathology rotations. Public slide set use was common, while professional society and departmental slide sets may be underutilized. Over half of respondents report being extremely or very comfortable navigating interactive scanned slides. Survey data suggests digital slides are currently predominantly used in non-clinical dermatopathology rotations and independent studies. Incorporation of slide scanners into departments may benefit resident education through the development of high-quality, curated departmental slide sets.

Feature fusion and latent feature learning guided brain tumor segmentation and missing modality recovery network

Accurate brain tumor segmentation is an essential step for clinical diagnosis and surgical treatment. Multimodal brain tumor segmentation strongly relies on an effective fusion method and an excellent segmentation network. However, it is common to have some missing MR modalities in clinical scenarios due to image corruption, acquisition protocol, scanner availability and scanning cost, which can heavily decrease the tumor segmentation accuracy, and also cause information loss for down-streaming disease analysis. To address this issue, I propose a novel multimodal feature fusion and latent feature learning guided deep neural network. On the one hand, the proposed network can help to segment brain tumors when one or more modalities are missing. On the other hand, it can retrieve the missing modalities to compensate for incomplete data. The proposed network consists of three key components. First, a Multimodal Feature Fusion Module (MFFM) is proposed to effectively fuse the complementary information from different modalities, consisting of a Cross-Modality Fusion Module (CMFM) and a Multi-Scale Fusion Module (MSFM). Second, a Spatial Consistency-based Latent Feature Learning Module (SC-LFLM) is presented to exploit multimodal latent correlation and extract the relevant features to benefit segmentation. Third, the Multi-Task Learning (MTL) paths are integrated to supervise the segmentation and recover the missing modalities. The proposed method is evaluated on BraTS 2018 dataset, and it can achieve superior segmentation results when one or more modalities are missing, compared with the state-of-the-art methods. Furthermore, the proposed modules can be easily adapted to other multimodal network architectures and research fields.

A literature survey of MR-based brain tumor segmentation with missing modalities.

Multimodal MR brain tumor segmentation is one of the hottest issues in the community of medical image processing. However, acquiring the complete set of MR modalities is not always possible in clinical practice, due to the acquisition protocols, image corruption, scanner availability, scanning cost or allergies to certain contrast materials. The missing information can cause some restraints to brain tumor diagnosis, monitoring, treatment planning and prognosis. Thus, it is highly desirable to develop brain tumor segmentation methods to address the missing modalities problem. Based on the recent advancements, in this review, we provide a detailed analysis of the missing modality issue in MR-based brain tumor segmentation. First, we briefly introduce the biomedical background concerning brain tumor, MR imaging techniques, and the current challenges in brain tumor segmentation. Then, we provide a taxonomy of the state-of-the-art methods with five categories, namely, image synthesis-based method, latent feature space-based model, multi-source correlation-based method, knowledge distillation-based method, and domain adaptation-based method. In addition, the principles, architectures, benefits and limitations are elaborated in each method. Following that, the corresponding datasets and widely used evaluation metrics are described. Finally, we analyze the current challenges and provide a prospect for future development trends. This review aims to provide readers with a thorough knowledge of the recent contributions in the field of brain tumor segmentation with missing modalities and suggest potential future directions.

Evolution of Portable Sensors for In-Vivo Dose and Time-Activity Curve Monitoring as Tools for Personalized Dosimetry in Molecular Radiotherapy

Treatment personalization in Molecular Radiotherapy (MRT) relies on pre- and post-treatment SPECT/ PET-based images and measurements to obtain a patient-specific absorbed dose-rate distribution map and its evolution over time. Unfortunately, the number of time points that are available per patient to investigate individual pharmacokinetics is often reduced by limited patient compliance or SPECT or PET/CT scanner availability for dosimetry in busy departments. The adoption of portable sensors for in-vivo dose monitoring during the entire treatment could improve the assessment of individual biokinetics in MRT and, thus, the treatment personalization. The evolution of portable devices, non-SPECT/PET-based options, already used for monitoring radionuclide activity transit and accumulation during therapy with radionuclides (i.e., MRT or brachytherapy), is presented to identify valuable ones, which combined with conventional nuclear medicine imaging systems could be effective in MRT. External probes, integration dosimeters and active detecting systems were included in the study. The devices and their technology, the range of applications, the features and limitations are discussed. Our overview of the available technologies encourages research and development of portable devices and dedicated algorithms for MRT patient-specific biokinetics study. This would represent a crucial advancement towards personalized treatment in MRT.

MODL-24. ESTABLISHING A CLINICALLY RELEVANT CT AND ASSOCIATED RADIOMICS PIPELINE FOR INTRACRANIAL RODENT TUMOUR MODELS

Abstract While magnetic resonance imaging (MRI) is the predominant imaging modality for glioblastoma (GBM), pre-clinical MRI scanner availability is limited. As pre-clinical CT is more widely available and cost-effective, this study aimed to 1) establish preclinical-GBM CT and CT-radiomic workflows, 2) identify whether CE-CT could detect murine orthotopic GBM tumours on two CT instruments [TRIUMPHX-O-CT; IVISSPECTRUM-CT], 3) assess whether CT-radiomic features could distinguish tumour from normal tissue, and support earlier detection of tumours, 4) verify translation of pre-clinical CT-radiomic pipelines to, and assess pre-clinical CT-features in, clinical CE-CT scans.U87R-Luc2(n=25) and NFpp10a-Luc2(n=10) orthotopic GBM models were established and tumours monitored via bioluminescence imaging (BLI). Concurrently, mice underwent CE-CT (IV-iodine/300mg/mL/50kV-scan). Extracted radiomic features (PyRadiomics) underwent dimensionality reduction (Spearman correlation; >0.85). Remaining features were analysed (Recursive feature elimination (RFE)/RepeatedCV/randomforest) in normal and tumour tissue and across timepoints (TRIUMPHX-O-CT-Wk3vsWk6,Wk6vsWk9/12; IVISSPECTRUM-CT-Wk6vsWk9/12).CE-CT and radiomic pipelines were successfully established for orthotopic GBM models, using both CT-systems. On visual assessment of images, BLI was significantly more sensitive, with tumours detectable at Wk1 (BLI) vs Wk9 (CE-CT). However, RFE analysis identified CT-radiomic features (first_order&glcm) which differentiated tumour from normal tissue (TRIUMPHX-O-CT). A subsequent feature set (first_order,glcm,gldm&glzm) were identified (TRIUMPHX-O-CT/IVISSPECTRUM-CT), detecting tumours earlier (Wk3&Wk6) than possible by visual assessment of CTs. Preclinical radiomic methods were successfully applied to exploratory clinical CE-CT scans(n=10). Here, several preclinical CT-features (e.g. Zone_Entropy) showed increased intensity in tumour regions. Overall experimental BLI is the most sensitive method for pre-clinical intracranial tumour detection. However, analysis of clinically relevant CT-radiomic features may facilitate tumour identification and earlier tumour detection (Wk3/Wk6-TRIUMPHX-O-CT/Wk6-IVISSPECTRUM-CT) than possible by visual assessment of CT (Wk9). Clinically relevant CT-derived radiomic features may therefore support intracranial rodent tumour assessment. Importantly, preclinical radiomic methods successfully translate to clinical CT-radiomic analysis. Parallel trends in tumour-specific feature intensities across pre-clinical and clinical scans suggest species conservation of features.

Deep Learning Applications in Magnetic Resonance Imaging: Has the Future Become Present?

Deep learning technologies and applications demonstrate one of the most important upcoming developments in radiology. The impact and influence of these technologies on image acquisition and reporting might change daily clinical practice. The aim of this review was to present current deep learning technologies, with a focus on magnetic resonance image reconstruction. The first part of this manuscript concentrates on the basic technical principles that are necessary for deep learning image reconstruction. The second part highlights the translation of these techniques into clinical practice. The third part outlines the different aspects of image reconstruction techniques, and presents a review of the current literature regarding image reconstruction and image post-processing in MRI. The promising results of the most recent studies indicate that deep learning will be a major player in radiology in the upcoming years. Apart from decision and diagnosis support, the major advantages of deep learning magnetic resonance imaging reconstruction techniques are related to acquisition time reduction and the improvement of image quality. The implementation of these techniques may be the solution for the alleviation of limited scanner availability via workflow acceleration. It can be assumed that this disruptive technology will change daily routines and workflows permanently.

Comparison of ultrafast wave-controlled aliasing in parallel imaging (CAIPI) magnetization-prepared rapid acquisition gradient echo (MP-RAGE) and standard MP-RAGE in non-sedated children: initial clinical experience.

Fast magnetic resonance imaging (MRI) sequences are advantageous in pediatric imaging as they can lessen child discomfort, decrease motion artifact and improve scanner availability. To evaluate the feasibility of an ultrafast wave-CAIPI (controlled aliasing in parallel imaging) MP-RAGE (magnetization-prepared rapid gradient echo) sequence for brain imaging of awake pediatric patients. Each MRI included a standard MP-RAGE sequence and an ultrafast wave-MP-RAGE sequence. Two neuroradiologists evaluated both sequences in terms of artifacts, noise, anatomical contrast and pathological contrast. A predefined 5-point scale was used by two independent pediatric neuroradiologists. A Wilcoxon signed-rank test was used to evaluate the difference between sequences for each variable. Twenty-four patients (14 males; mean age: 11.5±4.5years, range: 1month to 17.8years) were included. Wave-CAIPI MP-RAGE provided a 77% reduction in scan time using a 32-channel coil and a 70% reduction using a 20-channel coil. Visualization of the pathology, artifacts and pathological enhancement (including parenchymal, leptomeningeal and dural enhancement) was not significantly different between standard MP-RAGE and wave-CAIPI MP-RAGE (all P>0.05). For central (P<0.001) and peripheral (P<0.001) noise, and the evaluation of the anatomical structures (P<0.001), the observers favored standard MP-RAGE over wave-CAIPI MP-RAGE. Ultrafast brain imaging with wave-CAIPI MP-RAGE is feasible in awake pediatric patients, providing a substantial reduction in scan time at a cost of subjectively increased image noise.

Imaging in myeloma: a Royal College of Radiologists national survey of current imaging practice

To evaluate current national imaging practice in myeloma with reference to National Institute for Health and Care Excellence (NICE) guidelines (NG35, 2016) and compare results with an initial survey conducted in 2017 (61 participating sites). All UK radiology departments treating myeloma patients and with a Royal College of Radiologists (RCR) Audit Lead were invited to participate. Data were collected using an online questionnaire. Descriptive statistics were performed. One hundred and fourteen hospitals supplied data (54% return rate). Skeletal survey (SS) remains the most-commonly performed first-line imaging test for suspected/confirmed myeloma or plasmacytoma (39%, 45/114 hospitals), followed by whole-body magnetic resonance imaging (WBMRI) (27%, 31/114) and whole-body computed tomography (WBCT) (19%, 22/114). Integrated positron-emission tomography/CT (PET/CT) was first-line in 14% (16/114). The NICE recommended initial investigation, WBMRI, is currently offered in 27% of surveyed hospitals (<10% in 2017). Ongoing challenges to implementing WBMRI include scanner availability, financial constraints, reporting time, and radiologist training. Despite NICE recommendations regarding WBMRI in diagnosis/follow-up of myeloma, SS (poor sensitivity and specificity) remains the most commonly performed first-line test. Radiologists, haematologists, and patients should continue to emphasise the superiority and benefit of modern and more accurate imaging, such that they are prioritised in clinical service planning.

Novel artificial neural network and linear regression based equation for estimating visceral adipose tissue volume.

There is a growing interest in fast and reliable assessment of abdominal visceral adipose tissue (VAT) volume for risk stratification of metabolic disorders. However, imaging based measurement of VAT is costly and limited by scanner availability. Therefore, we aimed to develop equations to estimate abdominal VAT volume from simple anthropometric parameters and to assess whether linear regression based equations differed in performance from artificial neural network (ANN) based equations. MRI-measured abdominal VAT volumes and anthropometric parameters of 5772 subjects (White ethnicity, age 45-76 years, 52.7% females) were obtained from the UK Biobank. Subjects were divided into the derivation sample (n=5195) and the validation sample (n=577). Basic models (age, sex, height, weight) and expanded models (basic model+waist circumference and hip circumference) were constructed from the derivation sample by linear regression and ANN respectively. Performance of the linear regression and ANN based equations in the validation sample were compared and estimating accuracies were evaluated by receiver-operating characteristic curves (ROC). The basic and expanded equations based on linear regression and ANN demonstrated the adjusted coefficient of determination (R2) ranging from 0.71 to 0.78, with bias ranging from less than 0.001L-0.07L in comparison with MRI-measured VAT. Both basic and expanded ANN based equations demonstrated slightly higher adjusted R2 and lower error measurements than linear regression equations. However, no statistical difference was found between linear regression equations and their ANN based counterparts in ROC analysis. Both linear regression and ANN based expanded equations presented higher estimating accuracies (76.9%-90.1%) than the basic equations (74.5%-87.5%) in ROC analysis. We present equations based on linear regression and artificial neural networks to estimate abdominal VAT volume by simple anthropometric parameters for middle-aged and elderly White population. These equations can be used to estimate VAT volume in general practice as well as population-based studies.

Magnetresonanztomographie des Gehirns bei Säuglingen und Kleinkindern

Magnetic resonance imaging (MRI) is increasingly being used for infants and small children due to rapid sequence protocols, broader scanner availability and good monitoring possibilities. The sequence protocol should always be adapted to the individual clinical needs of the infant or toddler. For some clinical indications, such as control of ventricular width in children with shunted hydrocephalus, ultrafast protocols can be used with ascanning time of just afew minutes. For more complex clinical questions, more extensive sequence protocols are warranted. Particularly for neonates and using a rapid investigation protocol, MRI examinations can very often be performed without sedation. The necessity of using gadolinium-based contrast agents has to be critically deliberated in infants and neonates and has to be exactly tailored to the clinical needs. In many cases MRI examinations of the brain in infants and neonates do not require gadolinium-based contrast agents.

Dual-Energy Computed Tomography in Thoracic Imaging-Current Practices and Utility: Survey of the Society of Thoracic Radiology.

The purpose of this study was to determine the current practice patterns of utilization of dual-energy computed tomography (DECT) in thoracic imaging. In this IRB-approved study, the URL link for an anonymous 26-question survey was sent by email to all the members of the Society of Thoracic Radiology (STR). Survey questions focused on the practice type, case volume, DECT scanner availability, common indications, image types, and perceived utility of DECT. Study data were collected and managed using SurveyMonkey tools and analyzed with χ tests. The survey response rate was 11% (104/962). DECT was available in 75% of respondents' institutions, with 90% of these having 1 to 5 DECT scanners (P<0.001). Seventy percent performed 1 to 500 DECT chest CTs per month (P<0.001). Dual-source was the most common DECT scanner (81%) (P=0.239). DECT was opted depending on the clinical indication in 89% (P=0.433). The technologist reconstructs the additional DECT images in 75% of instances (P<0.001). Acute pulmonary embolism (PE) was the most common indication of DECT (53%) (P=0.006), while chronic PE was considered the most valuable use of DECT (33%) (P<0.001). Iodine map was the most commonly used DECT image (53%) (P<0.001) followed by low-energy virtual monoenergetic image (VMI) (29%). For VMI, 50 keV was the most commonly used energy level for improving vascular contrast (43%) (P=0.048), whereas 120 keV was the most commonly used energy in VMI for decreasing artifacts (25%) (P=0.027). There is wide variability on the utilization of DECT in thoracic imaging. PE is perceived to be the most valuable utility of DECT, and iodine map is considered the most valuable DECT image.

Preoperative cross-sectional mapping for deep inferior epigastric and profunda artery perforator flaps.

Perforator flap-based breast reconstruction in a post mastectomy patient requires dissection of the artery-vein bundle (perforators) responsible for perfusion of the subcutaneous fat and skin of the flap. Traditionally, these reconstructions were performed with the transverse rectus abdominis myocutaneous (TRAM) flap, but autologous breast reconstruction using muscle sparing free flaps has become steadily more popular in recent years. Preoperative imaging to locate and evaluate candidate perforators has become an essential step before patients undergo the microsurgical procedure. Preoperative mapping assists with operative planning, reduces operating times, and brings anatomical variations to their attention. Pre-operative imaging also assists in choosing the appropriate donor site for harvesting flaps. Computed tomography angiography (CTA) and magnetic resonance angiography (MRA) have been widely used for this type of preoperative imaging. Both MRA and CTA have their inherent advantages and disadvantages, and the preferred modality for this purpose varies by institution based on factors such as scanner availability, radiologist and surgeon experience, and comfort in interpreting the images. Concerns over excessive exposure to ionizing radiation and poor iodinated contrast agent enhancement of the intramuscular perforator course has made MRA the first-choice imaging modality in many centers. The purpose of the article is to review technique and protocols for the pre-operative CTA/MRA in patients who are being considered for a deep inferior epigastric artery perforator (DIEP) or profunda artery perforator (PAP) flap and to familiarize the reader with the normal and variant anatomic features of the deep inferior epigastric and PAP vessels along with the anatomic and surgical considerations used in the selection of perforator flap donor site for breast reconstruction post mastectomy.

Establishing a Concise and Unified PET/MR requisition process

Currently there is no concise and formal procedure to obtain all the necessary participant and study information needed for a research PET/MR exam. From the moment a research participant is consented for a study, there are many steps leading up to the exam. Study eligibility, scanner and radiopharmaceutical availability and patient preparation all need to be addressed before a participant arrives for their exam. The purpose of this work is to design and evaluate a novel requisition form to be implemented for a research PET/MR exam.

Abstract 212: What are the Imaging Capabilities at Referring Hospitals for Large Vessel Occlusion Triage? Results from the Massachusetts Statewide Survey

Introduction: We assessed availability/ feasibility of computed tomography angiography (CTA) acquisition and its potential for screening stroke patients for large-vessel occlusion (LVO) at referring hospitals (RH) (hospitals without endovascular capabilities) in Massachusetts (MA). Methods: The MA CTA Stroke Workgroup (a statewide committee of stroke neurologists, neurointerventionalists, and radiologists) developed a CTA capability survey with 28 questions on logistics, protocols and CT scanner availability. The survey was sent to all 62 RH to be completed by interdisciplinary stroke teams. Results: Response rate was 100 % (62/62 RH); 96.8% have protocols for acute stroke care; 77.4% have protocols for transferring patients to a receiving center; only 35.5% have revised protocols reflecting the extended thrombectomy window. Regarding CTA availability, 95.2% have 24-hour CTA imaging available all year, with 64.5% having two or more scanners. CTA technologist availability is high with 95.2% having a technologist available 24/7. Just over half (53.2%) report protocols where CTA head and neck are obtained immediately after non-contrast head CT, while patient remains in scanner; 29.0 % report non- contrast head CT with patient removed from scanner for further clinical evaluation, followed by CTA head and neck as indicated. For CTA interpretation, 36.9% use emergent reads by local radiology; 31.5% use Nighthawk (remote) radiology; 14.6 % transmit scans for interpretation by the receiving hospital; the remainder use a combination of scan interpretation options. The majority (90.3%) have capability to share images through the cloud. The most challenging element of the CTA process was changing emergency department protocols (45.2%); availability of scanners and technology was identified as least challenging. The majority of RH (88. 7%) prefer to retain patients not in need of transfer to a receiving hospital if no LVO is present on CTA. Conclusion: There is wide spread availability of CTA across MA. Improving LVO detection and triage to thrombectomy capable centers with a focus on RH CTA acquisition is a clear opportunity for intervention. The methods and survey tool developed may prove useful for other states/regions working to enhance stroke systems.

Predictors of missed appointments in patients referred for congenital or pediatric cardiac magnetic resonance.

Congenital cardiac magnetic resonance is a limited resource because of scanner and physician availability. Missed appointments decrease scheduling efficiency, have financial implications and represent missed care opportunities. To characterize the rate of missed appointments and identify modifiable predictors. This single-center retrospective study included all patients with outpatient congenital or pediatric cardiac MR appointments from Jan. 1, 2014, through Dec. 31, 2015. We identified missed appointments (no-shows or same-day cancellations) from the electronic medical record. We obtained demographic and clinical factors from the medical record and assessed socioeconomic factors by U.S. Census block data by patient ZIP code. Statistically significant variables (P<0.05) were included into a multivariable analysis. Of 795 outpatients (median age 18.5years, interquartile range 13.4-27.1years) referred for congenital cardiac MR, a total of 91 patients (11.4%) missed appointments; 28 (3.5%) missed multiple appointments. Reason for missed appointment could be identified in only 38 patients (42%), but of these, 28 (74%) were preventable or could have been identified prior to the appointment. In multivariable analysis, independent predictors of missed appointments were referral by a non-cardiologist (adjusted odds ratio [AOR] 5.8, P=0.0002), referral for research (AOR 3.6, P=0.01), having public insurance (AOR 2.1, P=0.004), and having scheduled cardiac MR from November to April (AOR 1.8, P=0.01). Demographic factors can identify patients at higher risk for missing appointments. These data may inform initiatives to limit missed appointments, such as targeted education of referring providers and patients. Further data are needed to evaluate the efficacy of potential interventions.