‘More than 1,000 words’: AI models could be used to communicate procedures to cancer patients

Read the original at Global News ↗
Global News · collected 2026-10-12 · by Rachel Morgan

Quick Summary

Researchers at the University Health Network in Toronto are developing AI technology that creates a 3D model, or "digital twin," of a patient's anatomy to help prepare cancer patients for surgery by showing them exactly what procedures will involve. Adina Isenberg, previously diagnosed with breast cancer, is involved with the project and emphasizes its potential to reduce medical trauma by empowering patients through better understanding and visualization. The technology, though still in clinical trials, could also aid surgeons by providing a more detailed view of patient anatomy before surgery begins.
Written locally by qwen2.5:14b on 2026-10-12, using this article's own text rather than the other coverage of the same event (that is the story summary below).

AI analysis runs on qwen2.5:14b, locally

Story summary

Adina Isenberg, diagnosed with breast cancer nine years ago, was shocked by the additional scar from her armpit surgery during a lumpectomy procedure in Toronto. At University Health Network (UHN) in Toronto, researchers are now developing AI technology to create 3D models of patients' anatomy, known as "digital twins," which could help predict tumor movement and improve patient understanding before procedures. Isenberg is collaborating with the team to ensure better communication about these technological advancements to cancer patients. The goal is to make the overall experience for patients undergoing treatments more comprehensible and less daunting by leveraging AI models that integrate physical properties, potentially enhancing pre-surgical preparation.

Written for “AI for Cancer Patient Communication” on 2026-10-12, grounded in this article and the 0 other(s) covering the same event.

Signals How these are calculated →

Claims extracted
32
claim-shaped sentences
Uncertain
25%
8 of 32 hedged
Leaning
not political
takes no side on a contested political question
Correction & hedging signals
64.1
corrections and hedging in what we collected; not a measure of accuracy
Outlets on this story
1
Technology
Narrative spread
1
articles carrying this framing
Analyzed 2026-10-12 · how these are computed

Story

📰 AI for Cancer Patient Communication
Technology · 1 article(s) covering the same event.

How this is being covered How these are calculated →

Article leaning vs. publisher reliability
Source leaning vs. consistency

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Publisher

Global News · 1573 article(s) · 8 correction(s) detected
Running correction rate · 8 correction(s)
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Who wrote this

Rachel Morgan
33 article(s) here · 1 carrying a prediction
🔮 “When I woke up from my surgery, I couldn’t believe that in addition to the scar that I had prepared for on my breast, I had a second scar in my armpit, which is for when they take out what they call the sentinel node,” she said.
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Also by Rachel Morgan
Nothing else under this byline is closely related to this article, so these are simply their most recent.
All 33 articles by Rachel Morgan →

Topics

Global News Toronto UHN the University Health Network the University of Toronto

Subjects

Souza PERSON · 3× Global News ORG · 2× Isenberg PERSON · 2× UHN ORG · 2× Adina Isenberg PERSON · 1× Amin Madani PERSON · 1× Toronto GPE · 1× Wagner Souza PERSON · 1× the University Health Network ORG · 1× the University of Toronto ORG · 1×

Narrative

“Can we integrate physical properties so that when we’re showing the image, we can actually predict that in this position, at this height, with these variables playing all together, the lesion will actually move from this point to that point and we can be so precise?
framing: mixed · carried by 1 article(s) · first seen 2026-10-12
🔮 “When I woke up from my surgery, I couldn’t believe that in addition to the scar that I had prepared for on my breast, I had a second scar in my armpit, which is for when they take out what they call the sentinel node,” she said.

Claims (32 extracted, 8 hedged)

When Adina Isenberg was diagnosed with breast cancer nine years ago, it came as a shock. asserted
it → diagnose → shock
“You think, like, how is this real? asserted
this → think → ?
But when she woke up from her lumpectomy procedure, she was faced with a whole new host of feelings with how the surgery changed her body. asserted
surgery → wake → body
“When I woke up from my surgery, I couldn’t believe that in addition to the scar that I had prepared for on my breast, I had a second scar in my armpit, which is for when they take out what they call the sentinel node,” she said. asserted
she → wake → what
Researchers at the University Health Network in Toronto are now leveraging AI to help create a 3D picture of what tumours look like. asserted
tumours → leverage → what
Using this technology could better prepare patients for the procedures they are about to undergo. uncertain
they → use → procedures
Isenberg has joined the team to help communicate what this new technology could mean for patients. uncertain
technology → join → patients
“We can’t help if someone has gotten cancer. asserted
someone → help → cancer
We can’t know how their body is going to respond to treatment. asserted
body → know → treatment
That’s out of our control,” she told Global News. asserted
she → ’ → News
“What we can do is make the entire rest of the experience better. asserted
rest → make → experience
Researchers are using AI technology to create what they call a “digital twin” of the patient’s anatomy to better understand the tumour and its effect on the patient. asserted
they → use → patient
Get weekly health news “Instead of being 2D, just a flat image on a screen, it becomes this interactive model that is not just a recreation of what could be, but it’s an image of you,” Wagner Souza, a staff scientist at UHN and assistant professor at the University of Toronto, told Global News. uncertain
Souza → get → News
“It’s you cloned in 3D, and we can play around from different angles so we can show depth, where the lesion is, how it could potentially look after it’s removed.” uncertain
it → ’ → depth
Isenberg said that being able to show the model to patients and explain the process of what they are about to undergo could reduce unnecessary medical trauma. uncertain
they → say → trauma
Souza said it allows patients to become part of the conversation. asserted
patients → say → conversation
“It’s empowering, because you know where you’re fighting,” he said. asserted
he → ’ → ?
“People say that an image is worth 1,000 words. asserted
image → say → ?
Maybe a live image that is not just a model, but it’s you … maybe that will be worth way more than 1,000 words and give you the power that you need to make a decision that you are satisfied with.” asserted
you → ’ → that
The technology still has to go through clinical trials, but early use suggests there may also be benefits in the operating room. uncertain
use → have → room
Amin Madani, an endocrine and acute care surgeon at UHN, said typically surgeons have to look at two-dimensional images, and build in their head what the anatomy might look like. uncertain
anatomy → say → what
“For us surgeons, you have to look at an imaging, like an MRI, a CT scan, and then memorize it in your head and say ‘okay, let’s just go for it’ asserted
’s → look → it
,” he said. asserted
he → say → ?
He said having this kind of technology allows the surgeon to build an understanding and expectations of the patient’s body ahead of time, allowing for better planning and strategizing. asserted
surgeon → say → planning
While researchers say the technology is a huge advancement, there are still some unknowns. asserted
technology → say → ?
“There are some things we can still not do, but we’re working towards being able to achieve,” Souza said. asserted
Souza → be → ?
When patients have their images taken, they are lying on their front, but they are often on their backs for surgery. asserted
they → have → surgery
“That alone changes the structure of the body, the breast, the tissue. asserted
That → change → body
And this is something that we are wondering, can we potentially implement in the model?” Souza said. asserted
Souza → wonder → model
“Can we integrate physical properties so that when we’re showing the image, we can actually predict that in this position, at this height, with these variables playing all together, the lesion will actually move from this point to that point and we can be so precise? asserted
we → integrate → point
These are applications that may be explored as the technology goes through clinical trials, but the promise of what the modelling can do is exciting for surgeons looking to change the game. uncertain
modelling → explore → game
“I think machine learning, AI, algorithms that can see what’s happening in surgery for added intelligence in the OR is going to be the next frontier in my opinion,” Madani said. asserted
Madani → think → opinion
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