Advancements in Colonoscopies

June is Men’s Health Month, a time dedicated to raising awareness about the unique health challenges men face and promoting preventative measures to ensure long and healthy lives. As part of this important initiative, we’re diving into one of the critical aspects of men’s health: advancements in colonoscopies.

Recent advancements in colon cancer detection have focused on improving the accuracy, accessibility, and non-invasiveness of screening methods. Here are some notable developments:

1. Liquid Biopsy and Blood Tests

Circulating Tumor DNA (ctDNA): Liquid biopsies that analyze ctDNA can detect genetic mutations associated with colon cancer. This method allows for early detection and monitoring of cancer without invasive procedures.
Blood-based Biomarkers: Researchers are identifying specific biomarkers in the blood that indicate the presence of colon cancer. Tests like the Epi proColon, which detects methylated SEPT9 DNA, have been developed and are being refined.

2. Stool-based Tests

Multitarget Stool DNA Tests (mt-sDNA): Tests like Cologuard analyze stool samples for DNA mutations and blood associated with colon cancer and precancerous polyps. These tests have high sensitivity and can be done at home.

Fecal Immunochemical Test (FIT): FIT detects hidden blood in the stool, a common sign of colon cancer. It’s non-invasive, easy to use, and more accurate than older fecal occult blood tests (FOBT).

multitarget FIT (mtFIT) test: Researchers at the Netherlands Cancer Institute have developed a new stool test that may detect signs of colorectal cancer earlier and more effectively than existing tests. Published in The Lancet, the study found that the multitarget FIT (mtFIT) test, which measures hemoglobin, calprotectin, and serpin family F member 2 levels, outperformed the current fecal immunochemical test (FIT). Among 13,187 participants, the mtFIT test identified more abnormal protein levels, suggesting better detection of pre-cancers and polyps. This advancement could lead to a significant reduction in colorectal cancer cases and deaths, improving early detection and survival rates. Further studies are needed to compare the mtFIT test with commercially available tests.

3. Advanced Imaging Techniques

Artificial Intelligence (AI) in Colonoscopy: AI-powered tools assist gastroenterologists during colonoscopies by enhancing polyp detection rates and reducing the likelihood of missing lesions.

High-Resolution Imaging: Techniques like narrow-band imaging (NBI) and confocal laser endomicroscopy provide clearer, more detailed views of the colon’s mucosal surface, improving the detection of subtle lesions.

4. Genetic and Molecular Testing

Next-Generation Sequencing (NGS): NGS technologies enable comprehensive genetic profiling of tumors, helping to identify specific mutations and guide personalized treatment plans.

Molecular Markers: Identifying molecular markers such as KRAS, NRAS, and BRAF mutations, as well as microsatellite instability (MSI), helps in assessing cancer risk and determining appropriate therapies.

5. Non-Invasive Imaging Techniques

Virtual Colonoscopy (CT Colonography): This non-invasive imaging technique uses CT scans to create detailed images of the colon and rectum. It’s a less invasive alternative to traditional colonoscopy and can be particularly useful for patients unable to undergo standard procedures.
Magnetic Resonance Colonography (MRC): Similar to CT colonography, MRC uses MRI technology to visualize the colon. It’s another non-invasive option, though less commonly used.

CT colonography of a rectal mass. | CC BY 4.0

6. Enhanced Patient Accessibility and Comfort

At-Home Screening Kits: Innovations in at-home testing kits, like those for FIT and mt-sDNA, have made screening more accessible and convenient, potentially increasing participation rates in regular screening programs. Research led by the Perelman School of Medicine at the University of Pennsylvania found that colorectal cancer screening rates more than doubled when patients were given a choice between a take-home test or a colonoscopy, compared to offering only a colonoscopy.

Telemedicine and Remote Monitoring: The integration of telemedicine allows patients to discuss test results and next steps with healthcare providers remotely, improving follow-up care and reducing the need for in-person visits.

7. Artificial Intelligence and Machine Learning

AI Algorithms for Risk Assessment: AI is being used to develop algorithms that analyze patient data, including medical history, genetics, and lifestyle factors, to assess individual risk for colon cancer and recommend personalized screening schedules.

Improved Pathology: Machine learning models are enhancing the accuracy of pathology by analyzing biopsy samples for subtle signs of cancer that might be missed by human eyes.

These advancements are collectively improving the early detection of colon cancer, leading to better patient outcomes through earlier intervention and more personalized treatment plans.

Virtual Colonoscopy Interpretations

As we observe Men’s Health Month and recognize the critical advancements in colorectal cancer screening, it is essential to highlight the importance of accessible and accurate diagnostic tools. At Vesta Teleradiology, we specialize in providing expert interpretations for Virtual Colonoscopies, ensuring timely and precise readings that can make a significant difference in early detection and treatment outcomes. Partner with us for your Virtual Colonoscopy needs and contribute to better health outcomes in your community. Together, we can make a meaningful impact on men’s health and beyond.


Latest in Cardiac Imaging and Interpretation Challenges

A recent study published in European Radiology highlights a significant increase in the use of cardiac imaging techniques such as MRIs and CT scans between 2011 and 2022 across 32 countries. The data, gathered from the European Society of Cardiovascular Radiology’s MR-CT registry, showed a 3.8-fold increase in MRIs and a 4.5-fold increase in CT scans for cardiac concerns during this period.


Radiologists, either independently or in collaboration with non-radiologists, primarily reported these examinations. The study emphasized the importance of radiologists in providing cardiac imaging services, attributing their expertise to the expanding availability of these modalities in both academic and non-academic centers.


Challenges with Interpretations

Interpreting cardiac imaging presents a range of challenges due to the complexity of the heart’s structure, function, and the dynamic nature of cardiac activity. Here are some specific examples of these challenges:


  1. Complex Anatomy and Physiology

Detailed Anatomy: The heart’s intricate structures, such as the coronary arteries, valves, myocardium, and chambers, require careful analysis. Identifying subtle anomalies like small congenital defects or early signs of disease can be difficult.

Example: Diagnosing a small atrial septal defect (ASD) in a transthoracic echocardiogram (TTE) can be challenging due to its subtle presentation and the need to differentiate it from normal anatomical variations.

  1. Motion Artifacts

Heart Motion: The constant movement of the heart can create artifacts, making it difficult to obtain clear and accurate images.

Example: In cardiac MRI, the rapid motion of the heart can blur images, especially if the patient cannot hold their breath adequately during the scan.

  1. Image Quality and Resolution

Image Clarity: Achieving high-resolution images is crucial for accurate diagnosis, but various factors can degrade image quality.

Example: In echocardiography, poor acoustic windows due to obesity, lung disease, or previous surgeries can obscure critical details, making it hard to assess valve function or wall motion abnormalities.

  1. Differentiating Normal Variants from Pathology

Physiological Variants: Distinguishing between normal anatomical variants and pathological findings requires expertise.

Example: Differentiating between a benign variant like a prominent trabeculae in the left ventricle and early signs of cardiomyopathy in a cardiac MRI requires careful interpretation.

  1. Dynamic Functional Assessment

Real-Time Functionality: Assessing the dynamic function of the heart, including systolic and diastolic function, valve movement, and blood flow, can be complex.

Example: Evaluating diastolic dysfunction on an echocardiogram involves interpreting multiple parameters such as mitral inflow patterns, tissue Doppler imaging, and left atrial volume, which can be nuanced and interdependent.

  1. Contrast Agents and Artifacts

Use of Contrast: While contrast agents can enhance visualization of cardiac structures and perfusion, they can also introduce artifacts and complications.

Example: In cardiac CT angiography (CTA), contrast-induced artifacts, such as streak artifacts from dense iodinated contrast, can obscure coronary artery details, complicating the assessment of stenosis.

  1. Interpreting Complex Cases

Multifactorial Disease: Patients with multiple coexisting cardiac conditions present a challenge for comprehensive interpretation.

Example: A patient with ischemic heart disease, heart failure, and arrhythmias may have overlapping imaging findings on a cardiac MRI, requiring a detailed and integrated interpretation to delineate the contribution of each condition.

  1. Stress Imaging

Inducing and Interpreting Stress Conditions: Stress echocardiography or cardiac MRI stress tests involve interpreting the heart’s response to induced stress (exercise or pharmacological agents).

Example: Identifying stress-induced wall motion abnormalities in a stress echocardiogram requires comparing pre- and post-stress images, which can be subtle and influenced by technical factors and patient effort.

  1. Integration of Multimodal Imaging

Combining Data from Multiple Modalities: Integrating information from various imaging techniques like echocardiography, MRI, and CT to provide a comprehensive diagnosis.

Example: Correlating findings from a cardiac MRI showing myocardial fibrosis with a CT angiogram revealing coronary artery stenosis requires synthesizing data from both modalities to understand the patient’s overall cardiac condition.

These challenges underscore the need for advanced training, experience, and often subspecialty expertise in cardiac imaging to ensure accurate and reliable interpretations.


Vesta Teleradiologists: Specialists in Cardiac Imaging

In conclusion, the surge in cardiac imaging underscores the critical role radiologists play in providing accurate and timely diagnoses for heart patients. With subspecialties in cardiac imaging, Vesta’s board-certified radiologists are well-equipped to meet the growing demand for accurate cardiac imaging interpretation for outpatient centers, mobile radiology units, and hospitals alike, whether on-site or remotely. As the field of cardiac imaging continues to evolve, radiologists remain at the forefront, leveraging their specialized knowledge to support healthcare providers and deliver high-quality imaging services across diverse clinical settings.



Latest News in Outpatient Radiology Centers

Outpatient radiology centers play a crucial role in the healthcare landscape by providing convenient, efficient, and cost-effective access to diagnostic imaging services for patients across a wide range of medical conditions. These services include X-rays, ultrasounds, MRIs, CT scans, mammography, and fluoroscopy, among others. Patients typically visit these centers for imaging tests prescribed by their healthcare providers to diagnose and monitor various medical conditions.

While these centers offer a convenient and efficient alternative to hospital-based imaging services, often providing faster appointments and reduced wait times, they do face challenges.

Issues with Outpatient Imaging Appointments

A recent study published in Academic Radiology reveals that nearly 24% of outpatient imaging appointments are missed, with the majority due to patient cancellations rather than no-shows. Factors such as younger age, being unwed, residing in disadvantaged neighborhoods, or lacking adequate insurance increase the likelihood of missing appointments. The study, conducted by researchers at the University of California, Irvine, analyzed data from their academic health center, finding that over 70% of cancellations were initiated by patients. Interventions are suggested to reduce missed appointments, such as self-scheduling, implementing checklists for necessary processes before imaging exams, and addressing health-related social risks like transportation access. Despite suggestions, limited research exists on reducing appointment cancellations in outpatient imaging.


Delays in MRI Orders

A recent study published in the Journal of the American College of Radiology reveals that nearly half of outpatient MRI orders experience significant delays, being performed more than 10 days from the date chosen by the referring provider. Led by Ronilda Lacson, MD, PhD, from Brigham and Women’s Hospital in Boston, the research emphasizes the critical importance of mitigating factors causing these delays, as they negatively impact patient care. Assessing over 97,000 outpatient MRI exams ordered between October 2021 and December 2022, the study identifies patient demographics, social determinants of health, and radiology practice- and community-level factors associated with delayed MR imaging. The study found that close to 50% of MRI orders had a prolonged order-to-performed interval, with factors such as higher Area Deprivation Index (ADI) scores contributing to delays. The authors stress the need for systemic approaches to address disparities in access to MRI examinations, including staff training, access to patient navigators, and programs tackling transportation barriers to outpatient imaging.


Other Challenges Outpatient Centers Face:


Technological Advancements: Keeping up with rapidly evolving imaging technologies requires significant investment and ongoing training for staff. Outpatient centers need to stay updated with the latest equipment and software to maintain competitiveness and provide accurate diagnostic services.

Regulatory Compliance: Compliance with healthcare regulations and standards, such as those related to patient privacy (HIPAA), radiation safety, and quality assurance, is essential but can be challenging to navigate. Failure to comply can result in fines, legal consequences, and damage to reputation.

Staffing and Workforce Management: Recruiting and retaining skilled radiologists, technicians, and support staff is crucial for maintaining quality and efficiency. Shortages in qualified personnel or high turnover rates can strain operations and affect patient care.

Integration with Healthcare Systems: Outpatient radiology centers need to effectively integrate with larger healthcare systems, including electronic health record (EHR) systems and referral networks. Seamless communication and coordination with referring physicians are essential for delivering comprehensive patient care.


Outpatient Centers Can Rely on Teleradiologists

In conclusion, outpatient radiology centers play a vital role in providing accessible, efficient, and high-quality diagnostic imaging services to patients. However, they face various challenges, including staffing shortages, which can impact their ability to deliver timely care. One solution to alleviate some of these challenges is the adoption of teleradiology services. Teleradiology services from reputable companies like Vesta, enables centers to access remote radiologists who can interpret images and provide diagnostic reports, helping to overcome staffing shortages and ensure continuous coverage. By embracing technology and innovative solutions like teleradiology, outpatient radiology centers can enhance their capabilities, improve patient care, and meet the evolving needs of healthcare delivery.




An Update to the Physician Shortage Problem

The AAMC (Association of American Medical Colleges) has released new projections indicating a physician shortage of up to 86,000 physicians in the United States by 2036. This underscores the critical need for sustained and increased investments in training new physicians to address the country’s healthcare needs. The report, conducted by GlobalData Plc, includes various scenarios based on trends in healthcare delivery and the workforce. While the projected shortfall is smaller than previous estimates, it still highlights the necessity for additional investments in graduate medical education (GME). Demographics, particularly population growth and aging, are driving the increasing demand for physicians. The report also notes a significant portion of the physician workforce nearing retirement age, which will further decrease the physician supply. Addressing underserved communities could require approximately 202,800 more physicians than current estimates. Lifting the federal cap on Medicare support for GME and bipartisan legislation like the Resident Physician Shortage Reduction Act aim to alleviate the shortage, but further efforts are needed to meet future healthcare demands.


Rural Americans’ Healthcare Challenges

Rural Americans face significant healthcare challenges, with fewer available doctors compared to urban areas, exacerbating existing health issues. Dr. Bruce A. Scott, President of the American Medical Association, emphasizes the urgent need for policymakers to address these disparities. Rural communities experience higher rates of various illnesses, exacerbated by economic pressures and limited access to healthy living conditions. The shortage of specialists and the closure of rural hospitals further compound the problem. Insufficient access to primary care physicians is a pressing issue, with inadequate residency spots and decreasing applications from rural areas. The AMA advocates for changes to the Medicare physician payment system, which has seen a decline in rates over the years. Administrative burdens, such as prior authorizations, are also contributing to physician burnout and compromising patient care. To combat the doctor shortage and rural health challenges, the AMA advocates for healthcare reforms, including overhauling the Medicare payment system, expanding telehealth, increasing residency positions, incentivizing rural practice, and addressing workforce stresses.

hospitals in rural America

Radiology Is Being Hit, Too

Radiology departments are grappling with worsening staffing shortages alongside declining reimbursements. During the RSNA 2023 meeting, Ashish Sant from Merge by Merative discussed key trends and challenges. Staffing and cost management remain top concerns due to burnout and insufficient replacements for retiring radiologists. To address these issues, there’s a push towards cloud-based solutions, with a modular approach easing concerns about data security and patient information management. The pandemic has accelerated the shift towards cloud adoption, highlighting benefits such as accessibility and cost reduction. Integrating AI into radiology workflows is another focus, though challenges persist in seamlessly embedding AI solutions. Merge’s partnership with Microsoft Azure aims to provide customers with cloud solutions tailored to their needs.


Radiology Support for the US

Addressing radiology staffing shortages is crucial for ensuring efficient and effective healthcare delivery. Whether you’re a hospital, outpatient center, or part of the Indian Health Service (IHS), Vesta is here to help. Our team can provide on-site radiologists or teleradiologists to meet the specific needs of your facility. By partnering with us, you can ensure timely and accurate radiology services, ultimately improving patient care and outcomes. Don’t let staffing shortages hinder your operations – reach out today to learn how we can support your radiology department.






AI in Radiology: Biden’s New Executive Order and Latest News

The Biden administration’s recent executive order on artificial intelligence (AI) has significant implications for radiology, as discussed in a review published in JACR. The order aims to ensure responsible use of AI in healthcare and establish a federal program to address unsafe practices. While immediate changes to radiology practice may not be expected, the order signals forthcoming regulatory shifts, particularly in oversight and enforcement by government agencies. This includes scrutiny of computer-aided detection systems and AI for noninterpretative tasks. The FDA premarket review for medical devices like CAD programs is likely to be augmented with additional quality and equity requirements. Health and Human Services will oversee data input into AI algorithms, possibly mandating disclosure of training datasets. Radiologists seeking Medicare reimbursement for AI products will need to prioritize security and compliance with nondiscrimination laws. The order also emphasizes data sharing with the National AI Research Resource and encourages radiologists to engage in policy creation and provide input on regulatory frameworks. However, specific parameters and regulatory details are yet to be defined. Overall, the order serves as a call for federal agencies to mobilize efforts in AI oversight, with radiologists urged to actively participate in shaping policies and best practices.


Predicting Lymph Node Metastasis

A recent study published in Radiology: Imaging Cancer compared the effectiveness of a four-dimensional (4D) convolutional neural network (CNN) model, incorporating clinical and breast MRI findings, with a machine learning model based solely on clinicopathologic features in predicting axillary node status in women with breast cancer. The 4D CNN model achieved a significantly higher area under the curve (AUC) of 87% compared to 63% for the clinical model. It also demonstrated higher sensitivity (89% vs. 75%) and specificity (76% vs. 52%), with a lower false-negative rate (11% vs. 25%). The study suggests that the 4D hybrid model could serve as a valuable tool in selecting patients who may avoid invasive procedures like sentinel lymph node biopsy and aid in treatment decisions for breast cancer patients. However, further external validation of the model is needed, and limitations such as reliance on manual tumor bounding boxes and specific MRI device imaging need to be addressed for broader clinical adoption.


FDA Clearance for Cardiac and Lung AI

Exo, a medical imaging software and device company, has announced FDA clearance for its cardiac and lung artificial intelligence (AI) applications on Exo Iris, their handheld ultrasound device. This expands Exo’s cleared applications to include cardiac, lung, bladder, hip, and thyroid assessments. Iris, powered by AI, facilitates point-of-care ultrasound, particularly benefiting rural or underserved communities, enabling faster diagnosis and treatment. Sandeep Akkaraju, Exo’s CEO, emphasizes the aim of democratizing AI-empowered medical imaging for all caregivers. The AI applications were trained on a diverse dataset and validated across various patient populations and scan types. They enable reliable assessment of pulmonary edema and cardiac function, with additional doppler capabilities for cardiac, abdominal, and vascular applications. Clinicians, including those with limited experience, welcome the efficiency and reliability of Exo’s AI applications, which enhance patient care and healthcare system efficiency.


History of the IHS: Indian Health Services

When experts study health across various U.S. demographics, one particular metric often falls into sharp relief: there is a significant health burden weighing on American Indians and Alaska Natives. The AI/AN population accounts for about 9.7 million people in the United States (about 2.9% of the population), and this group routinely ranks near the bottom for life expectancy, insurance coverage, and overall health (both mental and physical).

About 2.6 million of AI/AN people receive healthcare services from the IHS, or Indian Health Services. This program aims (to use their own words), “to raise the physical, mental, social, and spiritual health of American Indians and Alaska Natives to the highest level,” but is the program succeeding? Let’s examine the IHS and its mission, challenges, and efficacy.

The IHS Story

While the U.S. government and federally recognized tribes have worked in partnership to provide AI/AN people with healthcare since the 1700s, the IHS officially began its work in July of 1955. The organization first worked to build hospitals in remote parts of the country that served Native individuals in the area; over the years, the IHS has expanded its efforts to include both health services and public health education.

Today, the IHS is a part of the U.S. Department of Health and Human Services. They operate more than 600 medical facilities on or near Indian reservations across 37 states, and they also work to tackle challenges impacting AI/AN public health.

Challenges Facing the IHS

There’s no arguing that the IHS has laudable goals and that its team of 15,000 employees works hard to improve AI/AN lives. But IHS still faces significant challenges in its efforts. Research shows that about 61% of IHS medical buildings are in “fair” or “poor” conditions, which severely limits medical professionals’ ability to treat their patients. Similarly, many IHS facilities report working with broken or unreliable equipment, which affects the standard of care they can provide.

Furthermore, many IHS buildings are located in remote, rural locations with few amenities like grocery stores, schools, or even adequate housing. This makes recruiting and retaining medical staff especially difficult and limits the pool of quality professionals willing to practice in their network (notably, 50-75% of physicians who contact IHS recruiters have conduct or licensure issues on their record).


Despite these challenges, the IHS continues to make changes that benefit AI/AN peoples across the country. For example, in 2022 the IHS fought to secure $3.5 billion in funding from the government that allowed them to improve water supplies and wastewater disposal systems on tribal lands. Efforts like these help American Indians and Alaskan Natives improve their health and enjoy a better quality of life, and they prove that organizations like the IHS offer a tremendous benefit to the people they serve.


Teleradiology Support for IHS

Ensuring all populations in the US receive adequate care is the goal of your healthcare facility. Vesta is here should you find yourself short staffed for radiologists—we have U.S. Board certified radiologists available for preliminary and final interpretations whenever you need it. In fact, Vesta is already proving teleradiology services to several IHS sites.  Please reach out to us to learn more:


Vesta Teleradiology 1071 S. Sun Dr. Suite 2001 Lake Mary, FL, 32746
Phone: 877-55-VESTA


New FDA Clearances for Imaging Systems and Solutions

FDA clearance for a diagnostic imaging machine indicates that the device has been deemed safe and effective for its intended use by the Food and Drug Administration (FDA) in the United States. This clearance process involves thorough evaluation of the device’s design, performance, and manufacturing processes to ensure that it meets regulatory standards for quality, safety, and efficacy. Here’s the latest devices that have received FDA clearance.


The Magnetom Terra.X: MRI System

The Magnetom Terra.X, a new 7T MRI system, has received 510(k) clearance from the FDA. Manufactured by Siemens Healthineers, it’s a second-generation successor to the Magnetom Terra and offers several enhancements for 7T imaging. Key features include an eight-channel parallel transmit architecture for clinical use, deep learning image reconstruction optimized for 7T, improved diffusion imaging with a high-performance gradient system, and accelerated image acquisition enabling high-resolution brain and knee exams in under 20 minutes. Siemens Healthineers sees this as a significant step in providing better patient care, particularly in neurological and knee imaging. Additionally, the FDA clearance allows existing Magnetom Terra systems to be upgraded to the Magnetom Terra.X.

Image courtesy of Siemens Healthineers

SyMRI 3D for Brain Imaging

SyntheticMR has announced that its latest imaging solution, SyMRI 3D, has received FDA 510(k) clearance for clinical use in the United States. This clearance marks a significant advancement in quantitative MRI technology, offering exceptional resolution and accuracy in brain imaging. SyMRI 3D enables precise volumetric estimations of brain regions, known as parcellation, providing clinicians with deeper insights into brain structure and function. The enhanced resolution facilitates comprehensive lesion analysis, leading to more accurate medical condition assessments. This clearance empowers physicians to make more informed decisions in diagnosis and treatment planning, ultimately improving patient outcomes. SyntheticMR reaffirms its dedication to advancing medical imaging technology and providing innovative tools to enhance patient care through this milestone.


nCommand Lite for Remote Scanning

GE Healthcare has highlighted the FDA clearance of a solution by Ionic Health that enables technologists to remotely supervise patient scans. The system, called “nCommand Lite,” has been tested in Brazil for three years and is vendor-agnostic, allowing remote supervision across MRI, CT, and PET modalities. GE has secured exclusive distribution rights for nCommand in the U.S., aiming to address ongoing workforce shortages in healthcare. Rekha Ranganathan, GE’s chief digital officer for imaging, emphasized the company’s commitment to remote operations and increasing patient access to expert technologists. The system facilitates not only scanning supervision but also training, procedure assessment, and scanning parameter management. GE’s announcement coincides with growing interest in remote scanning, with the American College of Radiology advocating for permanent remote supervision of diagnostic tests. However, technologists have expressed reservations about managing imaging remotely, according to recent survey data from the American Society of Radiologic Technologists.




March AI News in Diagnostic Imaging

New Research by Harvard Medical School, MIT and Stanford on AI and Clinician Performance

The potential of medical artificial intelligence (AI) tools to enhance clinicians’ performance in interpreting medical images varies among individual clinicians, as highlighted by recent research led by Harvard Medical School, MIT, and Stanford. Published in Nature Medicine, the study underscores the intricate nature of human-AI interaction, which remains incompletely understood. While some radiologists benefit from AI assistance, others experience interference, affecting diagnostic accuracy.

The findings stress the necessity for personalized AI systems tailored to individual clinicians, emphasizing careful implementation to maximize benefits and minimize harm. Despite variations in AI’s impact, the results shouldn’t deter AI adoption but rather prompt a deeper understanding of human-AI dynamics to design approaches that enhance human performance.

To ensure effective integration of AI in clinical practice, collaboration between AI developers and clinicians is essential, alongside rigorous testing in real-world scenarios. Furthermore, efforts should focus on improving AI accuracy and training radiologists to discern AI inaccuracies, facilitating informed decision-making. Ultimately, understanding the complexities of machine-human interaction is pivotal for optimizing patient care through AI integration in radiology.

A radiologist examines an x-ray

AI and Workflows

New research highlights a novel reporting workflow that automatically incorporates artificial intelligence (AI) findings into structured radiology reports, streamlining physicians’ tasks and saving valuable time. German experts shared their experience with the “AI to SR pipeline,” which integrates a commercially available AI tool for chest X-ray pathology detection and localization into structured report templates.

In evaluations conducted at University Medical Center Mainz, expert radiologists found that reports generated using the AI to SR pipeline were faster compared to free-text reporting and conventional structured reporting. Additionally, subjective quality assessments indicated higher ratings for reports created with the pipeline.

In the hospital’s clinical routine, chest X-ray images are sent to the picture archiving and communication system, then automatically forwarded to the AI tool for analysis. The results are output in a DICOM structured reporting format, taking approximately five minutes from image acquisition to final reporting. Radiologists were able to create chest X-ray reports significantly faster with the pipeline compared to free-text and conventional structured reporting, while also rating the AI-generated reports more favorably.

The authors suggest that this AI-driven reporting pipeline offers standardized, time-efficient, and high-quality reporting for chest X-rays, potentially enhancing AI integration into daily clinical practice and maximizing its benefits.




The Latest in Native American Health News: Healthcare Worker Challenges

Physician Shortages

The Indian Health Service (IHS) faces significant physician shortages, with a vacancy rate of 25% in 2018. To address this, the American Medical Association (AMA) recommends creating an office of academic affiliations to establish partnerships with medical schools and residency programs. Currently, the IHS lacks formalized connections with academic medical centers, unlike other federal health systems such as the Veterans Health Administration and the Military Health System. These partnerships could offer training opportunities and help attract physicians to underserved areas. The AMA also suggests raising physician compensation, modernizing facilities, and developing funding streams for rotations and learning opportunities. Additionally, the IHS should evaluate regulatory barriers and provide resources to support physicians serving American Indian, Alaska Native, and Native Hawaiian communities. Overall, the AMA is committed to addressing the physician shortage within the IHS to ensure access to healthcare for these populations.


Cortez Masto’s Legislation for Enhancing Recruitment Efforts

Representatives from the Reno-Sparks Indian Colony Tribal Health Center and the U.S. Department of Health and Human Services advocated for the approval of the IHS Workforce Parity Act before a Senate panel. This legislation, co-sponsored by Senators Catherine Cortez Masto and Markwayne Millen, aims to address healthcare worker recruitment and retention challenges at Indian Health Service (IHS) facilities.

The proposed act would enable part-time providers to access IHS scholarship and loan repayment programs, aligning them with similar programs like the National Health Service Corps (NHSC). This alignment would enhance recruitment efforts in provider-shortage areas, improving access to healthcare in tribal communities.

Testimonies revealed that IHS facilities face significant staffing shortages, with a national vacancy rate of 25%, which can escalate to 50% in rural and frontier tribal clinics in Nevada. The current full-time work requirement for accessing grant and loan repayment benefits acts as a barrier to recruitment and retention efforts.

Understaffing negatively impacts healthcare outcomes in tribal communities, exacerbating conditions such as diabetes, cirrhosis, chronic lung diseases, and behavioral health issues. Failure to address these challenges undermines the U.S. government’s trust responsibility to ensure the healthcare needs of Native communities are met, as outlined in legal agreements between First Nations and the federal government.

New Facilities in Arizona

In Arizona, three new health facilities have opened recently to improve healthcare access for Native American communities, with more projects in progress. Despite strides, Native Americans still face health disparities like diabetes and cardiovascular disease. The Navajo Nation, home to over 244,000 people, operates 12 primary care facilities under the Indian Health Service (IHS), crucial in an underserved area.


The Supai Health Station, nestled in the Grand Canyon and reachable only by air, mule, or foot, offers expanded services like primary care and dental. Similarly, the Dilkon Medical Center in the Navajo Nation provides comprehensive healthcare, including in-patient beds and behavioral health support.

Scheduled for May 2024, Sage Memorial Hospital in Ganado will further strengthen healthcare, serving around 23,000 people. Despite progress, challenges persist, including a shortage of hospital beds and healthcare professionals. Recruitment incentives like loan repayment aim to attract Native American individuals to healthcare careers.

Future plans include constructing new facilities in Bodaway Gap, Arizona, and Gallup and Pueblo Pintado, New Mexico, to enhance healthcare access for Native American communities in the region.


Any healthcare facilities needing support in radiology can look to Vesta for accurate and timely interpretations, even for subspecialties. Please contact us to learn more about our 24/7/365 teleradiology services.




February AI News in Radiology

Brain Tumor Spotted on PET Imaging

An AI algorithm named “JuST_BrainPET” identified a glioblastoma in a patient that had been missed by physicians. This finding, reported in the Journal of Nuclear Medicine, underscores the potential of AI-based decision support in diagnostic and treatment planning. The algorithm automatically segments metabolic tumor volume from healthy tissue on brain PET imaging. In a case study, it detected a lesion in the frontoparietal region, not identified by an expert, which progressed to a small tumor. The AI tool’s early detection could have influenced diagnostic and treatment decisions.


Using Eye-Tracking

Researchers in Lisbon, Portugal, have pioneered a method to enhance AI interpretability in radiology by integrating eye-tracking data into deep learning algorithms. This innovative approach, outlined in the European Journal of Radiology, aims to align AI systems more closely with human understanding, marking a significant leap towards more human-centered AI technologies in radiology. By leveraging eye-gaze data, the researchers sought to bridge the gap between human expertise and AI computational power, anticipating that AI models could learn from the nuanced patterns of image analysis observed by radiologists.


This integration promises AI models that prioritize image characteristics relevant for diagnosis, potentially reducing the disparity between AI decision-making processes and human radiologists’ diagnostic approaches. The potential benefits of this research are vast, potentially leading to AI systems that are not only more effective in identifying pathologies but also more understandable to radiologists, thus fostering trust in AI-assisted diagnostics and accelerating their adoption in healthcare.


Review Paper on AI and Cancer Detection

Professor Pegah Khosravi and her team of researchers explore how artificial intelligence (AI) can enhance anomaly detection in MRI scans to advance precision medicine. Their comprehensive review, published in the Journal of Magnetic Resonance Imaging, focuses on AI techniques like machine learning and deep learning, particularly in identifying tumors in the brain, lungs, breast, and prostate.

The authors discuss several AI strategies for improving tumor detection, including a holistic approach that integrates data from various imaging techniques such as MRI, CT scans, and PET scans, along with genomic information and patient histories. This approach not only enhances anomaly detection accuracy but also facilitates personalized treatments based on comprehensive patient profiles.

Furthermore, the paper explores the use of ensemble methods in AI, which combine different AI models’ strengths to improve anomaly detection. By leveraging these methods, a more thorough analysis of MRI data is ensured. The authors advocate for AI systems that are accurate and transparent in their decision-making processes, fostering trust among healthcare professionals. They also stress the importance of collaboration among researchers, clinicians, and policymakers to effectively implement AI in medical imaging, guiding future advancements in the field.