91ĚŇÉ«

Software may help mitigate the side effects of cancer treatments

AI-based image analysis detects early organ damage

A research team at the 91ĚŇÉ« (TUM) has developed a method to predict early-stage kidney damage caused by certain cancer treatments. The kidneys begin to shrink slightly—months before any measurable decline in kidney function occurs. The researchers identified this trend using CT scans analyzed by an AI-powered algorithm. They also observed similar changes in the spleen. In the future, these findings could help adapt treatments earlier to prevent organ damage.

Dr. Lisa Steinhelfer and Dr. Friederike Jungmann Astrid Eckert / TUM
A team led by Dr. Lisa Steinhelfer (left) discovered that certain cancer therapies can damage the kidneys. Together with Dr. Friederike Jungmann (right), she describes how this damage can be predicted at a particularly early stage so that therapies can be adapted if necessary.

In their latest study, researchers from the departments of radiology and nuclear medicine at TUM University Hospital evaluated data from 121 patients undergoing treatment for prostate cancer with lutetium-177 PSMA. This radioligand therapy—a targeted form of nuclear medicine—is relatively new and shows promise for treating specific tumor types. However, one potential side effect is a decline in kidney function over the course of treatment.

“In an earlier study, we found that patients whose kidney function worsened after lutetium-177 PSMA therapy showed changes in kidney structure,” says lead author Dr. Lisa Steinhelfer. “Since it's not feasible to routinely take tissue samples, we wanted to explore whether these changes could be detected using less invasive methods.”

Kidney volume may serve as a biomarker

Dr. Steinhelfer and her colleagues opted for an approach that does not place any additional burden on patients. CT scans and blood tests are part of standard cancer care in order to monitor treatment progress. The Munich researchers examined various indicators in these routinely collected data to find early signs of kidney damage.

While factors such as kidney length or patient age did not yield reliable predictions, changes in kidney volume proved to be a strong signal: when kidney volume decreased by 10% or more within six months of starting treatment, there was a high likelihood that kidney function would decline significantly within an additional six months.

“These changes in kidney volume are very subtle. They can easily be missed during routine image assessments because clinicians are mainly focused on tracking tumors and other critical findings,” explains , one of the study’s senior authors, alongside . “In contrast, image analysis algorithms—if properly trained—can reliably detect even these minor changes,” adds Dr. Friederike Jungmann, who shares first authorship with Dr. Steinhelfer.

Method could be useful across multiple cancer therapies

“If it becomes clear that a patient is at increased risk of kidney impairment after six months of treatment, both the number of therapy cycles and the dosage can be individually adjusted,” explains Dr. Steinhelfer. “This would allow for a more personalized treatment approach.” TUM University Hospital is currently involved in two prospective studies further evaluating this strategy.

In a , Dr. Steinhelfer’s team also demonstrated that changes in spleen size can serve as an early warning sign for disruptions in blood cell production. “Many cancer therapies can affect liver function or the hematopoietic system,” she notes. “I believe our approach could help identify a wide range of treatment-related side effects much earlier than currently possible,” says Lisa Steinhelfer.

Publications
  • L. Steinhelfer, F. Jungmann et al. ““. Radiology (2025). DOI:

  • L. Steinhelfer, F. Jungmann et al. .Journal of Nuclear Medicine (2024). DOI:

  • L. Steinhelfer, L. Lunger et al. . Journal of Nuclear Medicine (2024). DOI: 10.2967/jnumed.123.265986 

91ĚŇÉ«

Corporate Communications Center

Contacts to this article:

Dr. Lisa Steinhelfer
TUM University Hospital
91ĚŇÉ«
Department of Diagnostic and Interventional Radiology
Tel. +49 89 4140-7064
lisa.steinhelferspam prevention@tum.de

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