Posted on Patient Talk

Level of trust in doctor may influence patient’s brain responses to pain

New research suggests that patients may have more pain and pain-related brain activity when undergoing a painful medical procedure performed by a physician they perceive as less trustworthy

When doctors are seen as less trustworthy by their patients it can increase reported pain and pain-related brain activity, new research from the University of Miami suggests. 

In a study recently published in Cerebral Cortex and led by recent University of Miami Psychology Ph.D. graduate Steven R. Anderson, and Elizabeth Losin, assistant professor of psychology at the University of Miami, participants underwent a series of simulated painful medical procedures with different virtual doctors who appeared more or less trustworthy.

During these medical simulations, participants had their brain activity measured using functional MRI (fMRI). Researchers compared brain responses to the simulated painful medical procedure (actually painful heat stimulations on their arms) and participants’ ratings of their pain when participants were treated by more or less trustworthy appearing virtual doctors.

The doctors in the virtual medical interaction were images of individuals dressed in a doctor’s white coat with faces that were created with a computer algorithm to look more or less trustworthy.  The facial trustworthiness algorithm was previously developed by Alexander Todorov and his colleagues at Princeton University.

“The participants in our study reported increased pain when they received painful heat stimulations from the doctors they perceived as less trustworthy,” said Losin, who also leads the Social and Cultural Neuroscience lab. In addition to influencing how much pain participants reported during the fMRI scan, having the simulated painful procedure with less trusted doctors was also associated with increased brain activity in pain-related brain regions, as well as increased responses in a pain-predictive brain biomarker, the Neurologic Pain Signature.

This study was inspired by an increasing number of studies showing that patients’ trust in their doctors can affect a variety of health outcomes, including pain. These findings have far-reaching implications for understanding health disparities because many studies have also demonstrated the people from marginalized groups including people of color, lower income individuals, and women often have a low degree of trust in the health care system in general and doctors in particular.

Losin and her lab previously conducted a study using face-to-face medical simulations where they experimentally changed how much doctors and patients trusted one another by making them feel more or less culturally similar to each other. This study was published in The Journal of Pain in 2017. Researchers found that the more culturally similar patients felt to their doctors the more they trusted them and the less pain they experienced from a simulated painful diagnostic procedure.   

In the current study, they wanted to understand the brain basis of the trust-related reductions in pain they have previously observed by using functional neuroimaging. “Although we had previously found that how much you trust your doctor can influence your experience of pain, there was surprisingly little known about the brain basis for this effect,” Anderson said.

The researchers found that when patients received a simulated painful diagnostic procedure from the doctors they trusted less they reported that it was more painful (more intense) and that the pain bothered them more (more unpleasant). This was particularly true when the painful diagnostic procedure stimulus was the most intense. This means that the researchers found the same thing that they had in their 2017 study.

When examining the brain, as they predicted, the researchers found that patients had more activity in a number of pain-related brain structures when undergoing the painful diagnostic procedure analogue with a low-trust doctor compared to a high-trust doctor. 

To increase their certainty that the trust-related reductions in brain activity the researchers observed were specific to pain, they also tested a brain-based pain biomarker, the Neurologic Pain Signature. They found that Neurologic pain signature pattern was more strongly expressed when patients received the painful diagnostic procedure analogue for low trust doctors versus high trust doctors, suggesting that pain-specific patterns of brain activity are reduced by trusting your doctor.

Finally, the authors wanted to understand what real-world factors might be leading people to feel more pain and have more pain-related brain activity when they trust their doctors less. To answer this question, they examined whether participants’ mistrust in health care organizations was associated with increased neural responses to the painful diagnostic procedure analogue. The team found that the more mistrust in medical organizations participants had, the more brain activity they had in brain regions involved in pain, attention, and emotion when experiencing and evaluating pain. Importantly, these findings suggest that the trust-related reductions in pain the researchers observed in the lab may extend to real-world medical care.

“The takeaway from this study is not necessarily that we need to train doctors to make different facial expressions. Rather, our results demonstrate that even small changes to the doctor-patient relationship may be enough to decrease patients’ pain,” Anderson noted.

Anderson further added that the results of this study “make clear that even non-verbal aspects of the doctor-patient relationship make a difference in the patient’s pain, which can inform interventions aimed at reducing patient pain and pain disparities.”

Posted on A to Z of Medical Conditions

Efficient AI technology for MRI data analysis

AI technology for MRI data analysis

AI technology for MRI data analysis by Prof. Dr. Shadi Albarqouni, Professor of Computational Medical Imaging Research at University Hospital Bonn and Helmholtz AI Junior Research Group Leader at Helmholtz Munich CREDIT © Johann F. Saba, University Hospital Bonn (UKB)

An algorithm developed by researchers from Helmholtz Munich, the Technical University of Munich (TUM) and its University Hospital rechts der Isar, the University Hospital Bonn (UKB) and the University of Bonn is able to learn independently across different medical institutions. The key feature is that it is “self-learning”, i.e. it does not require extensive, time-consuming findings or markings by radiologists in the MRI images. This federated algorithm was trained on more than 1,500 MR scans of healthy study participants from four institutions while maintaining data privacy. The algorithm then was used to analyze more than 500 patient MRI scans to detect diseases such as multiple sclerosis, vascular disease, and various forms of brain tumors that the algorithm had never seen before. This opens up new possibilities for developing efficient AI-based federated algorithms that learn autonomously while protecting privacy. The study has now been published in the journal Nature Machine Intelligence.

Healthcare is currently being revolutionized by artificial intelligence. With precise AI solutions, doctors can be supported in diagnosis. However, such algorithms require a considerable amount of data and the associated radiological specialist findings for training. The creation of such a large, central database, however, places special demands on data protection. Additionally, the creation of the findings and annotations, for example the marking of tumors in an MRI image, is very time-consuming. To overcome these challenges, a multidisciplinary team from Helmholtz Munich, the University Hospital Bonn and the University of Bonn collaborated with clinicians and researchers at Imperial College London and TUM and its University Hospital rechts der Isar. The aim was to develop an AI-based medical diagnostic algorithm for MRI images of the brain, without any data annotated or processed by a radiologist. Furthermore, this algorithm was to be trained “federally”: In this way, the algorithm “comes to the data”, so that the medical image data requiring special protection could remain in the respective clinic and did not have to be collected centrally.

Learning from several institutes without data exchange

In their study, the researchers were able to show that the federated AI algorithm they developed outperformed any AI algorithm trained using only data from a single institution. “In his ‘The Wisdom of Crowds,’ James Surowiecki argued that large groups of people are smarter, no matter how smart an individual might be. Basically, this is how our federated AI algorithm works,” says Prof. Dr. Shadi Albarqouni, Professor of Computational Medical Imaging Research at the Department of Diagnostic and Interventional Radiology at University Hospital Bonn and Helmholtz AI junior research group leader at Helmholtz Munich. To pool knowledge about MRI images of the brain, the research team trained the AI algorithm in different and independent medical institutions without violating data privacy or collecting data centrally. “Once this algorithm learns what MRI images of the healthy brain look like, it will be easier for it to detect disease. To achieve this requires intelligent computational aggregation and coordination between the participating institutes,” says Prof. Dr. Albarqouni. PD Dr. Benedikt Wiestler, senior physician at TUM’s University Hospital rechts der Isar and also involved in the study, adds: “Training the model on data from different centers contributes significantly to the fact that our algorithm detects diseases much more robustly than other algorithms that are only trained with data from one center.”

Towards affordable collaborative AI solutions

By protecting patient data while reducing radiologists’ workloads, the researchers believe their federated AI technology will significantly advance digital medicine. “AI and healthcare should be affordable, and that is our goal. With our study, we have taken a step in this direction,” says Prof. Dr. Albarqouni. “Our major goal is to develop AI algorithms, collaboratively trained at different, decentralized medical institutes, including those with limited resources.”

Posted on Cardiovascular disease

Cardiac arrest survival rate rising

Araz Rawshani

Araz Rawshani, Sahlgrenska Academy at the University of Gothenburg CREDIT Photo by Charlotta Sjöstedt

The probability of surviving sudden cardiac arrest outside hospital has more than doubled in 30 years. This is shown by a national Swedish register study covering more than 130,000 cases.

Sudden cardiac arrest affects some 10,000 people in Sweden annually. Saving them is a race against the clock, and the actions of bystanders who can perform cardiopulmonary resuscitation (CPR) and use a defibrillator are entirely crucial. Three in four events occur as people go about their everyday lives, while only one in four takes place in hospital.

The outcome of sudden cardiac arrest is usually fatal, regardless of where it happens. The condition is also the most common cause of death for people with diabetes, heart failure, or coronary artery disease, making it a widespread form of ill-health.

The current study, published in the European Heart Journal, includes data from the Swedish Cardiopulmonary Resuscitation Registry on 106,296 cases of out-of-hospital cardiac arrest (OHCA) in the years 1990–2020. The study also includes data on 30,032 in-hospital cardiac arrest (IHCA) cases in the period 2004–2020.

Three decades of development

Araz Rawshani, a researcher at Sahlgrenska Academy at the University of Gothenburg and a specialist doctor at Sahlgrenska University Hospital, is the corresponding author of the study.

“This is a comprehensive study that describes care and survival following sudden cardiac arrest. It’s a detailed report that clarifies three decades’ resuscitation in Sweden as a whole, and it shows that the situation has been changing rapidly for patients and the care providers alike,” he notes.

The findings show that for OHCA, survival more than doubled in 1990–2020 to approximately 11 percent. This whole improvement occurred in the late 1990s and early 2000s, and that no further rise in survival has taken place over the past decade.

For IHCA, survival rose by a factor of 1.2 in the period from 2004 to 2020, reaching about 35 percent. This improvement occurred largely from 2010 on and, according to the researchers, was due to better skills and resources in healthcare.

“In out-of-hospital cardiac arrest,” Rawshani says, “the rise in the number of people trained to perform CPR is probably the driver of that positive trend. Millions of Swedes have been trained in this vital skill, which can come in useful at any time, and these people intervene ever more often. Today, nonprofessionals (bystanders) start the CPR in the majority of all cases of cardiac arrest outside a hospital.”

Ambulance delays, more difficult cases

“The upward trend of out-of-hospital survival came to an end for several reasons,” Rawshani continues. “First, the ambulances aren’t managing to arrive in time for the patients; the delays in getting to them have constantly increased. Second, the proportion of patients who are relatively easy to resuscitate ­­­­— that is, those whose heart stops because of acute or chronic coronary artery disease ­­­­— has fallen dramatically in the past few decades.”

The fact that hard-to-treat cases ­­­­— with cardiac arrests caused by lung disease or heart failure, for example — are a growing category means that successful resuscitation will become harder to achieve in the future. What is more, women are overrepresented in this category, which explains the survival gap between the sexes. In 2020 almost 14 percent of the men, against some 8 percent of the women, survived OHCA.

“The study indicates that health care, from the emergency measures taken by paramedics to post-resuscitation nursing, is set to face new and daunting challenges in the years ahead, with a patient population who will get increasingly difficult to resuscitate.

“Further improvements in survival call for new ways of training considerably more people in cardiopulmonary resuscitation; maintenance of expertise; and the requisite technical advances to deliver defibrillators earlier,” Rawshani concludes.

Posted on Autism

How the sounds we hear help us predict how things feel

Researchers at the University of East Anglia have made an important discovery about the way our brains process the sensations of sound and touch.

A new study published today shows how the brain’s different sensory systems are all closely interconnected – with regions that respond to touch also involved when we listen to specific sounds associated with touching objects.

They found that these areas of the brain can tell the difference between listening to sounds such as a ball bouncing or the sound of typing on a keyboard.

It is hoped that understanding this key area of brain function may in the future help people who are neurodiverse or with conditions such as schizophrenia or anxiety. And it could lead to developments in brain-inspired computing and AI.

Lead researcher Dr Fraser Smith, from UEA’s School of Psychology, said: “We know that when we hear a familiar sound such as a bouncing ball, this leads us to expect to see a particular object. But what we have found is that it also leads the brain to represent what it might feel like to touch and interact with that object.

“These expectations can help the brain process sensory information more efficiently.”

The research team used an MRI scanner to collect brain imaging data while 10 participants listened to sounds generated by interacting with objects – such as bouncing a ball, knocking on a door, crushing paper, or typing on a keyboard.

Using a special imaging technique called functional MRI (fMRI), they measured brain activity throughout the brain.

They used sophisticated machine learning analysis techniques to test whether the activity generated in the earliest touch areas of the brain (primary somatosensory cortex) could tell apart sounds generated by different types of object interaction (bouncing ball verses typing on a keyboard).

They also performed a similar analysis for control sounds, similar to those used in hearing tests, to rule out that just any sounds can be discriminated in this brain region.

Researcher Dr Kerri Bailey said: “Our research shows that parts of our brains, which were thought only to respond when we touch objects, are also involved when we listen to specific sounds associated with touching objects.

“This supports the idea that a key role of these brain areas is to predict what we might experience next, from whatever sensory stream is currently available.

Dr Smith added: “Our findings challenge how neuroscientists traditionally understand the workings of sensory brain areas and demonstrate that the brain’s different sensory systems are all interconnected.

“Our assumption is that the sounds provide predictions to help our future interaction with objects, in line with a key theory of brain function – called Predictive Processing.

“Understanding this key mechanism of brain function may provide compelling insights into mental health conditions such as schizophrenia, autism or anxiety and in addition, lead to developments in brain-inspired computing and AI.”

This study was led by UEA in collaboration with researchers at Aix-Marseille University (France) and Maastricht University (Netherlands).

‘Decoding sounds depicting hand-object interactions in primary somatosensory cortex’ is published in the journal Cerebral Cortex on August 24, 2022.

Posted on Exercise

Dogs with more active owners may get more exercise

A dog and its owner exercising together

Compared to inactive owners, active dog owners report exercising their dogs more and report their dogs’ weight as healthier CREDIT Diego Perez-Lopez, PLOS, CC-BY 4.0

A new, international study suggests that dog owners who spend more time exercising themselves tend to exercise their dogs more, and more active owners are also more likely to perceive their dog’s body weight as being ideal. Sydney Banton of the University of Guelph in Ontario, Canada, and colleagues present these findings in the open-access journal PLOS ONE on August 24, 2022.

Obese dogs may face a number of health problems, such as diabetes and cardiac disease, and concerns about dog obesity are increasing worldwide. Earlier research has identified associations between dogs’ body weight and diet, exercise, and sociodemographic factors. However, those studies tended to be small and focused on individual countries.

For a broader, international perspective, Banton and colleagues analyzed results from a survey of 3,298 dog owners living in France, Germany, the United Kingdom, Canada and the United States. The survey included questions about both owners’ and dogs’ diet and exercise routines, and each owner’s perception of their dog’s body weight.

Analysis of the survey responses showed that dogs were more likely to get more exercise if their owners spent more time exercising themselves. More active owners were also more likely to perceive their dog as having an ideal body weight. Compared to owners in other countries, owners in Germany tended to exercise their dogs for a longer time, were more likely to perceive their dog’s body weight as ideal, and were less likely to report having been told that their dog was overweight.

Among dogs who were 5 years old and older, owners were less likely to perceive their dog as having an ideal body weight if they had been told their dog was overweight, if they reported attempting to control their dog’s weight by limiting food intake, and if they reported giving dogs other foods, such as treats, every day.

The findings suggest that many owners may attempt to control dogs’ body weight through diet, but not through exercise. The researchers therefore call for veterinarians to be given more resources to help owners develop exercise routines to avoid weight gain in dogs.

Sydney Banton adds: “Results from the survey revealed that feeding practices play a main role in owner perception of their dog being overweight, while exercise practices play a main role in owner perception of their dog being an ideal weight. While many weight loss strategies for dogs focus on feeding, this data highlights the need to incorporate exercise into weight loss regimens.”