Tag: radiology

Categories : Cancer Pain ManagementTags :

Radiology’s Role in Managing Pain in Cancer Patients

On By ModernMedia
SCP – Dr Winter performing a CT-guided interventional procedure

World Cancer Day, observed every 4 February, aims to raise awareness about cancer, encourage prevention and look at ways of improving a cancer patient’s quality of life. Interventional radiology plays a significant role in pain management for cancer patients.

Traditionally, radiology was used for diagnosing the cause of the pain but interventional radiology has changed this paradigm. Since American radiologist Charles Dotter, first used a guidewire and catheter to perform an interventional procedure in 1964, radiologists have become actively involved in intervention, including interventions for pain management. Today, many minimally invasive procedures are routinely performed in busy radiology departments.

Dr Arthur Winter, a radiologist at SCP Radiology says, ‘Interventional radiology has developed rapidly. Pain management procedures are becoming a daily part of busy radiology departments and play a crucial role in managing pain for cancer patients.

‘Cancer-related pain can be a significant burden, affecting patients’ quality of life and hindering their ability to carry out daily activities,’ says Dr Winter. ‘Radiology offers various techniques and treatments that help alleviate this pain effectively. These therapeutic interventions in pain management include image-guided interventional radiology procedures and radiation therapy.’

Understanding pain

Pain is a signal from the nervous system to let you know that something is wrong in your body. It is transmitted in a complex interaction between specialised nerves, the spinal cord and the brain. It can take many forms, be localised to one part of the body or appear to be widespread.

The nature of cancer pain

Cancer pain can arise from multiple sources, including the tumour itself, which may invade or compress surrounding tissues, organs or nerves. Metastases, the spread of cancer to other parts of the body, can also cause significant pain. Additionally, pain can result from the treatment of cancer, such as chemotherapy and radiation therapy.

Multidisciplinary approach to pain management

Effective pain management for cancer patients requires a comprehensive, multidisciplinary approach. Oncologists, radiologists, pain specialists and other healthcare providers collaborate to develop individualised care plans. Radiology is essential in both the diagnostic and therapeutic phases of this process, providing crucial insights and treatment options.

These personalised care plans, tailored to each patient’s needs, ensure:

  • Accurate diagnosis and identification of pain source or sources
  • Targeted and effective treatment interventions
  • Ongoing monitoring and adjustment of pain management strategies

Imaging techniques

Diagnostic radiology initially uses various imaging techniques to identify the source and extent of pain in cancer patients. These techniques include: X-rays, CT scans, MRI, PET scans and ultrasound.

By identifying the precise location and cause of pain, radiology can help:

  • Determine the most appropriate interventions, such as surgery, radiation therapy or minimally invasive interventional procedures
  • Monitor the effectiveness of pain management strategies and make necessary adjustments
  • Avoid unnecessary treatments that may not address the underlying cause of pain

Interventional radiology

Interventional radiology uses minimally invasive techniques to diagnose and treat various conditions and, for cancer patients experiencing pain, it offers several effective treatments:

  • Radiofrequency ablation (RFA): This uses heat, generated by radiofrequency energy to destroy cancerous tissues – often to treat painful bone metastases or tumours that are difficult to reach surgically
  • Cryoablation: Involves freezing cancerous tissues to destroy them. It is particularly useful for treating painful bone or soft tissue tumours, providing rapid pain relief
  • Nerve blocks: Involve the injection of anaesthetic agents or steroids near specific nerves to block pain signals. They can provide significant pain relief for patients with nerve-related pain

Palliative radiation therapy

In this instance, radiologists are involved with planning imaging only. The actual radiotherapy is performed by the radiation therapist, who works under the supervision of a radiation oncologist. Palliative radiation therapy is specifically designed to relieve symptoms and improve the quality of life for cancer patients. It focuses on pain control and symptom management rather than curing the disease.

Radiation oncologists deliver targeted doses of radiation to cancerous tissues, this palliative radiation therapy can help:

  • Reduce tumour size, alleviating pressure on surrounding tissues and nerves
  • Control bleeding or ulceration caused by tumours
  • Provide rapid pain relief, often within days to weeks of treatment

Improving quality of life

Dr Winter highlights that chronic pain can significantly diminish quality of life and contribute to depression, particularly in patients with underlying cancer. ‘These patients, in particular, should be considered for interventional procedures. For instance, there are highly effective treatments available to manage pain associated with pancreatic and pelvic cancers’.

‘Specialists, such as oncologists and neurologists, acknowledge the significant role of interventional radiology in pain management and collaborate closely with us to support their patients. As a rapidly advancing branch of radiology, it provides minimally invasive solutions and it is incredibly rewarding to witness patients regain their quality of life through effective symptom relief.’

Categories : Lab Tests and Imaging Pain ManagementTags :

Radiology Helps Treat Chronic Pain

On By ModernMedia
Dr Winter performing a CT-guided interventional procedure. Photo: Supploed

Radiology encompasses more than just imaging. It is a medical field that uses various imaging techniques to diagnose conditions, guide minimally invasive procedures and, much to the relief of agonised patients, treat chronic pain.

‘Traditionally, radiology is known as a modality where causes of pain are only diagnosed’, says Dr Arthur Winter, a radiologist at SCP Radiology. ‘Interventional radiology has changed this. It is a rapidly developing branch of radiology involving minimally invasive procedures.  Pain management procedures are becoming a daily part of busy radiology departments.’

Simply put, interventional radiologists can use precisely targeted injections to intervene in the body’s perception of pain.

Understanding pain

Pain is a signal from the nervous system to let you know that something is wrong in your body. It is transmitted in a complex interaction between specialised nerves, the spinal cord and the brain. It can take many forms, be localised to one part of the body or appear to come from all over.

Pain can be acute or chronic

Harvard Medical School gives an overview of the difference between the two. ‘Most acute pain comes from damage to body tissues. It results from physical trauma such as a sports or exercise injury, a broken bone, a medical procedure or an accident like stubbing your toe, cutting a finger or bumping into something. The pain can feel sharp, aching or throbbing and often heals within a few days to a few weeks.’

In comparison, chronic pain lasts at least two to three months, often long after you have recovered from the injury or illness and may even become permanent. It could also be a result of lifestyle diseases. Symptoms and severity vary and may include a dull ache, shooting, burning, stabbing or electric shock-like pain and sensations like tingling and numbness. Chronic pain can be debilitating and affect your ability to perform activities of daily living.

Interventional pain management

Although some acute pain can be managed with interventions, it is patients with chronic pain that truly benefit. ‘These patients often use high doses of opioid painkillers that may cause nausea, constipation, anorexia and addiction. Other painkillers may also irritate the stomach lining and cause kidney problems,’ says Dr Winter.

An alternative that interventional pain management offers, involves injections called nerve blocks that target very specific nerves.

‘Most of these interventions prevent nerve impulses or pain signals from being transmitted, using long-acting local anaesthetics. The effect is usually temporary but the addition of cortisone – or steroids – often brings longer-lasting relief. In some cases, it could be appropriate to follow the temporary block with neurolysis, which is a permanent disruption or destruction of the target nerves.’

Although nerve blocks and other long-acting pain injections have been done for years, the scope of procedures is evolving fast. The involvement of radiologists has also grown.

Dr Winter explains. ‘Pain management has traditionally been the responsibility of clinicians and anaesthetists. During nerve block procedures, they were typically guided by their knowledge of anatomy or a continuous X-ray technique called fluoroscopy. As ultrasound became more widely available, many anaesthetists learned to do these procedures under ultrasound guidance.

‘These specialists still provide these treatments but, thanks to the availability of specialised imaging equipment, radiologists now have the tools and skill to do procedures under sophisticated image guidance. With CT guidance, some procedures can be performed with great accuracy while avoiding blood vessels and non-target organs,’ says Dr Winter.

‘A lower dose of medication is also needed if the needle is placed accurately next to the target nerves. It is therefore not surprising that this is increasingly becoming a responsibility of interventional radiologists.’

Other procedures where radiologists are involved include targeted Botox injections to treat the symptoms of Piriformis syndrome, epidural cortisone injections for inflammation in the spine and a procedure called epidural blood patch. This is to seal spinal fluid leaks that cause low-pressure headaches.

In conclusion, Dr Winter says chronic pain may cause poor quality of life and depression, often seen in patients with underlying cancer. ‘It is especially these patients who should be considered for interventions. There are, for example, very effective procedures to manage pain caused by pancreatic and pelvic cancers.

‘Specialists like oncologists and neurologists recognise the value of interventional radiology in pain management and work closely with us to support their patients. It is a growing branch of radiology that offers a minimally invasive solution and it’s quite rewarding to see patients regain some quality of life.’

Categories : IT in Healthcare Lab Tests and ImagingTags :

Is AI a Help or Hindrance to Radiologists? It’s Down to the Doctor

On By ModernMedia

New research shows AI isn’t always a help for radiologists

Photo by Anna Shvets

One of the most touted promises of medical artificial intelligence tools is their ability to augment human clinicians’ performance by helping them interpret images such as X-rays and CT scans with greater precision to make more accurate diagnoses.

But the benefits of using AI tools on image interpretation appear to vary from clinician to clinician, according to new research led by investigators at Harvard Medical School, working with colleagues at MIT and Stanford.

The study findings suggest that individual clinician differences shape the interaction between human and machine in critical ways that researchers do not yet fully understand. The analysis, published in Nature Medicine, is based on data from an earlier working paper by the same research group released by the National Bureau of Economic Research.

In some instances, the research showed, use of AI can interfere with a radiologist’s performance and interfere with the accuracy of their interpretation.

“We find that different radiologists, indeed, react differently to AI assistance – some are helped while others are hurt by it,” said co-senior author Pranav Rajpurkar, assistant professor of biomedical informatics in the Blavatnik Institute at HMS.

“What this means is that we should not look at radiologists as a uniform population and consider just the ‘average’ effect of AI on their performance,” he said. “To maximize benefits and minimize harm, we need to personalize assistive AI systems.”

The findings underscore the importance of carefully calibrated implementation of AI into clinical practice, but they should in no way discourage the adoption of AI in radiologists’ offices and clinics, the researchers said.

Instead, the results should signal the need to better understand how humans and AI interact and to design carefully calibrated approaches that boost human performance rather than hurt it.

“Clinicians have different levels of expertise, experience, and decision-making styles, so ensuring that AI reflects this diversity is critical for targeted implementation,” said Feiyang “Kathy” Yu, who conducted the work while at the Rajpurkar lab with co-first author on the paper with Alex Moehring at the MIT Sloan School of Management.

“Individual factors and variation would be key in ensuring that AI advances rather than interferes with performance and, ultimately, with diagnosis,” Yu said.

AI tools affected different radiologists differently

While previous research has shown that AI assistants can, indeed, boost radiologists’ diagnostic performance, these studies have looked at radiologists as a whole without accounting for variability from radiologist to radiologist.

In contrast, the new study looks at how individual clinician factors – area of specialty, years of practice, prior use of AI tools – come into play in human-AI collaboration.

The researchers examined how AI tools affected the performance of 140 radiologists on 15 X-ray diagnostic tasks – how reliably the radiologists were able to spot telltale features on an image and make an accurate diagnosis. The analysis involved 324 patient cases with 15 pathologies: abnormal conditions captured on X-rays of the chest.

To determine how AI affected doctors’ ability to spot and correctly identify problems, the researchers used advanced computational methods that captured the magnitude of change in performance when using AI and when not using it.

The effect of AI assistance was inconsistent and varied across radiologists, with the performance of some radiologists improving with AI and worsening in others.

AI tools influenced human performance unpredictably

AI’s effects on human radiologists’ performance varied in often surprising ways.

For instance, contrary to what the researchers expected, factors such how many years of experience a radiologist had, whether they specialised in thoracic, or chest, radiology, and whether they’d used AI readers before, did not reliably predict how an AI tool would affect a doctor’s performance.

Another finding that challenged the prevailing wisdom: Clinicians who had low performance at baseline did not benefit consistently from AI assistance. Some benefited more, some less, and some none at all. Overall, however, lower-performing radiologists at baseline had lower performance with or without AI. The same was true among radiologists who performed better at baseline. They performed consistently well, overall, with or without AI.

Then came a not-so-surprising finding: More accurate AI tools boosted radiologists’ performance, while poorly performing AI tools diminished the diagnostic accuracy of human clinicians.

While the analysis was not done in a way that allowed researchers to determine why this happened, the finding points to the importance of testing and validating AI tool performance before clinical deployment, the researchers said. Such pre-testing could ensure that inferior AI doesn’t interfere with human clinicians’ performance and, therefore, patient care.

What do these findings mean for the future of AI in the clinic?

The researchers cautioned that their findings do not provide an explanation for why and how AI tools seem to affect performance across human clinicians differently, but note that understanding why would be critical to ensuring that AI radiology tools augment human performance rather than hurt it.

To that end, the team noted, AI developers should work with physicians who use their tools to understand and define the precise factors that come into play in the human-AI interaction.

And, the researchers added, the radiologist-AI interaction should be tested in experimental settings that mimic real-world scenarios and reflect the actual patient population for which the tools are designed.

Apart from improving the accuracy of the AI tools, it’s also important to train radiologists to detect inaccurate AI predictions and to question an AI tool’s diagnostic call, the research team said. To achieve that, AI developers should ensure that they design AI models that can “explain” their decisions.

“Our research reveals the nuanced and complex nature of machine-human interaction,” said study co-senior author Nikhil Agarwal, professor of economics at MIT. “It highlights the need to understand the multitude of factors involved in this interplay and how they influence the ultimate diagnosis and care of patients.”

Source: Harvard Medical School

Categories : Hospitals Lab Tests and ImagingTags :

Joint Statement Says Prior Radiation Should not Affect Decisions to Image

On By ModernMedia
Photo by National Cancer Institute on Unsplash

Previous radiation exposure should not be considered when assessing the clinical benefit of radiological exams, according to a statement by three scientific groups representing medical physicists, radiologists, and health physicists.

Medical radiation exposure is a hot topic. People receive average annual background radiation levels of around 3 mSv; exposure from a chest X-ray is about 0.1 mSv, and exposure from a whole-body CT scan is about 10 mSv. The annual radiation limit for nuclear workers is 20mSv.

The American Association of Physicists in Medicine, along with the American College of Radiology and the Health Physics Society, issued a joint statement opposing cumulative radiation dose limits for patient imaging, saying that there could be negative impacts on patient care. The statement opposes the position taken by several organisations and recently published papers.

“It is the position of the American Association of Physicists in Medicine (AAPM), the American College of Radiology (ACR), and the Health Physics Society (HPS) that the decision to perform a medical imaging exam should be based on clinical grounds, including the information available from prior imaging results, and not on the dose from prior imaging-related radiation exposures,” the statement reads.

“AAPM has long advised, as recommended by the International Commission on Radiological Protection (ICRP), that justification of potential patient benefit and subsequent optimization of medical imaging exposures are the most appropriate actions to take to protect patients from unnecessary medical exposures. This is consistent with the foundational principles of radiation protection in medicine, namely that patient radiation dose limits are inappropriate for medical imaging exposures.

“Therefore, the AAPM recommends against using dose values, including effective dose, from a patient’s prior imaging exams for the purposes of medical decision-making. Using quantities such as cumulative effective dose may, unintentionally or by institutional or regulatory policy, negatively impact medical decisions and patient care.

“This position statement applies to the use of metrics to longitudinally track a patient’s dose from medical radiation exposures and infer potential stochastic risk from them. It does not apply to the use of organ-specific doses for purposes of evaluating the onset of deterministic effects (e.g., absorbed dose to the eye lens or skin) or performing epidemiological research.”

The Radiological Society of North America also endorses the position.

The AAPM emphasises the importance of patient safety in their position. Radiation usage must be both justified and optimised and benefits should outweigh the risks.

“This statement is an important reminder that patients may receive substantial clinical benefit from imaging exams,” said James Dobbins, AAPM President. “While we want to see prudent use of radiation in medical imaging, and many of our scientific members are working on means of reducing overall patient radiation dose, we believe it is an important matter of patient safety and clinical care that decisions on the use of imaging exams be made solely on the presenting clinical need and not on prior radiation dose.

“AAPM is pleased to partner with our fellow societies—the American College of Radiology and the Health Physics Society—to bring a broadly shared perspective on the important issue of whether previous patient radiation exposure should play a role in future medical decision making.”

The AAPM cites the International Commission on Radiological Protection, which stresses that setting radiation exposure limits to patients is not appropriate. This is partly due to a lack of standardised dose estimates.

The position only addresses stochastic risks from radiation exposure, which are chance effects whose risk for a given imaging exam, like cancer,is unrelated to the amount of prior radiation. Deterministic effects, incremental, direct exposure responses, such as skin damage, result from different biological mechanisms and are not included.

The AAPM compiled a list of answers to frequently asked questions on the topic of medical radiation safety along with references to research papers which support the organisation’s position.

Source: News-Medical.Net

Categories : HospitalsTags :

Optimised Scheduling Algorithm Cuts Delays for MRI Scans

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A team of researchers from Dartmouth Engineering and Philips have developed an optimised scheduling algorithm that significantly cuts the waiting time of patients for MRI at Lahey Hospital in Massachusetts, cutting overall associated costs by 23%.

“Excellence in service and positive patient experiences are a primary focus for the hospital. We continuously monitor various aspects of patient experiences and one key indicator is patient wait times,” said Christoph Wald, professor and chair, Department of Radiology, Lahey Hospital, Tufts University Medical School. With a goal of wanting to improve patient wait times, we worked with data science researchers at Philips and Dartmouth to help identify levers for improvement that might be achieved without impeding access.”

Exam waiting times can be stressful for patients, depending on the perceived value of the visit, and the associated costs of a delay to the patient.

Before the new algorithm, the average outpatient’s waiting time at the hospital was 54 minutes. The researchers found that the problem was a complicated scheduling system, which must cater to emergency room patients, inpatients, and outpatients; while other appointments are relatively inflexible, inpatient exams usually can be delayed if necessary.
“By analysing the patient data, we found that delays were prominent because the schedule was not optimal,” explained first author Yifei Sun, a Dartmouth Engineering PhD candidate. “This research uses optimisation and simulation tools to help the MRI centres of Lahey Hospital better plan their schedule to reduce overall cost, which includes patient waiting time.”

After identifying sources of delays, the researchers then created a mathematical model which optimised the length of each exam slot, and then worked in inpatient exams. Then they created an algorithm which cut down on the waiting time with its associated costs for outpatients, idle equipment time, employee overtime, and cancelled inpatient exams.

“This iterative improvement process did result in measurable improvements of patient wait times,” said Prof Wald. “The construction and use of a simulation model have been instrumental in educating the Lahey team about the benefits of dissecting workflow components to arrive at an optimised process outcome. We have extended this approach to identify bottlenecks in our interventional radiology workflow and to add additional capacity under the constraints of staffing schedules.”

The researchers believe that this solution may have great applicability, as the problem is common to mid-sized hospitals.

“We also provided suggestions for hospitals that don’t have optimisation tools or have different priorities, such as patient waiting times or idle machine times,” said Sun, who worked on the paper with her advisor Vikrant Vaze, the Stata Family Career Development Associate Professor of Engineering at Dartmouth.

Source: News-Medical.Net

Journal information: Sun, Y., et al. (2021) Stochastic programming for outpatient scheduling with flexible inpatient exam accommodation. Health Care Management Science. doi.org/10.1007/s10729-020-09527-z.