Personalized medicine promises to move healthcare away from treating every patient with the same disease in essentially the same way. The goal is to identify the biological characteristics of an individual patient’s condition and use that information to select the treatment most likely to work. Genomics, circulating biomarkers and tissue analysis have already changed how physicians classify disease, particularly in oncology, but nuclear medicine adds another capability: it can show where a biological target is expressed throughout a living patient, how strongly different lesions express it and whether that expression changes after treatment.
That makes nuclear medicine more than a diagnostic specialty. By connecting molecular information with whole-body imaging, treatment selection and response monitoring, it could become one of the most important operating systems for personalized care.
Tissue biopsies remain essential to cancer diagnosis and molecular characterization, but they provide information from a limited sample taken from a particular location at a particular moment. That sample may not represent every tumor in the body, and it may not capture important differences within the tumor itself.
Metastatic cancer can be biologically heterogeneous. One lesion may express a therapeutic target strongly, another weakly and another not at all, while disease biology can change as cancer evolves under pressure from chemotherapy, immunotherapy, hormonal therapy or radiation. Molecular imaging can evaluate target expression across detectable disease sites simultaneously, revealing whether a target is present throughout the disease and whether some lesions behave differently from others.
That whole-body perspective is particularly important for targeted therapies. A treatment designed to bind to a specific protein may work well in lesions that express the target but provide little benefit where expression is absent or insufficient. By exposing those differences before treatment begins, molecular imaging can help physicians determine whether an individual patient is a strong candidate for a particular therapy.
Theranostics provides the clearest example of nuclear medicine’s role in personalized care. A diagnostic radiopharmaceutical is used to determine whether a patient’s disease expresses a particular target, and a related therapeutic radiopharmaceutical then delivers radiation to cells expressing that same target.
In prostate cancer, PSMA PET can identify patients with PSMA-positive disease who may be candidates for Novartis’ Pluvicto. In neuroendocrine tumors, somatostatin receptor imaging helps determine whether patients are suitable for treatment with Lutathera. In each case, the diagnostic scan does more than confirm that cancer exists; it helps determine whether a particular therapeutic mechanism is relevant to an individual patient.
As the radiopharmaceutical pipeline expands, the same model could extend to additional targets and cancers. Developers are investigating agents directed at fibroblast activation protein, carbonic anhydrase IX, gastrin-releasing peptide receptor, integrins and other markers, with many programs attempting to pair diagnostic imaging with targeted therapy. The growing pipeline can be followed through the Nuclio Clinical Trials Tracker, which reflects how quickly developers are moving beyond the first commercially validated targets.
The personalized-care opportunity extends beyond determining whether a target is present. New imaging agents are being developed to visualize characteristics such as tumor hypoxia, immune activity, cellular proliferation, metabolism and treatment resistance. These characteristics can affect whether a patient responds to radiation, immunotherapy or another targeted treatment, allowing physicians to potentially select a more appropriate therapy or avoid one unlikely to work.
Hypoxia imaging illustrates the potential. Oxygen-deprived regions of a tumor can be more resistant to radiation, but that resistance may not be visible on conventional anatomical imaging. A hypoxia-targeted PET scan could identify patients who require standard or intensified treatment while supporting treatment reduction for those whose tumors appear more responsive.
Immuno-PET could provide another important application by showing the distribution of immune targets throughout the body. That could help physicians understand why an immunotherapy may work in some lesions but not others, providing a more complete picture than tissue taken from a single site. In both cases, the value of imaging comes from making disease behavior visible before months of treatment have passed.
Patient selection is only one level of personalization. Nuclear medicine may also help determine how much treatment an individual patient should receive because patients can absorb and distribute radiation differently even when they receive the same administered activity. Their tumors, kidneys, salivary glands, bone marrow and other organs may receive significantly different absorbed doses.
Quantitative imaging and dosimetry could help physicians measure those differences. In time, that information may support adjustments to administered activity, the number of treatment cycles, intervals between cycles or combinations with other therapies. That transition will require standardized imaging protocols, validated software and clinical evidence showing how absorbed dose relates to tumor response and normal-organ toxicity, along with workflows hospitals can perform without creating an unsustainable burden on scanners and clinical teams.
The challenge is significant, but the opportunity is equally important. Once treatment can be measured inside the patient and connected to clinical outcomes, radiopharmaceutical therapy begins to move from target-based care toward genuinely individualized delivery.
Traditional response assessments often classify a patient’s disease using changes in overall tumor burden or a limited number of selected lesions. Molecular imaging can reveal a more complicated reality in which some tumors respond, others remain stable and others progress. That lesion-level heterogeneity may become increasingly important as radiopharmaceutical therapy moves into combinations and earlier treatment settings.
If one group of lesions loses target expression while another retains it, repeating the same treatment may not be sufficient. Physicians may need to add another therapy, switch targets or use different radiopharmaceuticals against different parts of the disease. AI-based segmentation and quantitative imaging could make that information easier to manage by identifying individual lesions, measuring uptake and tracking changes across serial scans.
This does not mean an algorithm should make treatment decisions independently. It means nuclear medicine could provide physicians with the detailed biological data required to make those decisions with greater precision.
Oncology is the most visible market for theranostics, but nuclear medicine’s personalized-care potential is broader. PET and SPECT can visualize cardiac function, blood flow, neurological processes, inflammation and protein accumulation associated with neurodegenerative disease.
In cardiology, molecular imaging can help distinguish disease subtypes that may require different treatment pathways. In Alzheimer’s disease, amyloid and tau PET can show whether specific pathological proteins are present in the brain, supporting diagnosis and helping determine whether a patient may be suitable for a targeted therapy or clinical trial.
As more treatments become linked to specific biomarkers, imaging could play a larger role in determining which patients qualify and whether the biological target changes during treatment. That would extend the theranostic principle beyond radiopharmaceutical therapy: visualize the disease mechanism, select the intervention and monitor what happens next.
Nuclear medicine’s scientific capabilities do not guarantee that personalized care will be delivered at scale. Many regions still have limited access to PET and SPECT systems, while nuclear medicine departments face shortages of technologists, physicians, pharmacists and medical physicists. New tracers also require dependable isotope production, radiopharmaceutical manufacturing and time-sensitive distribution, since a personalized treatment plan has little value if the required imaging agent or therapeutic dose cannot reach the patient on schedule.
Reimbursement will be another determining factor. Hospitals cannot routinely adopt advanced quantitative imaging and dosimetry if payment covers only the radiopharmaceutical and administration while ignoring the additional scans, software, labor and interpretation required for personalization. The industry must therefore develop the delivery system alongside the science, including scanners, tracers, therapies, software, isotope supply, trained personnel, reimbursement and standardized clinical protocols.
Personalized medicine has generated enormous amounts of biological information, but healthcare still needs practical ways to apply that information across the entire patient. Nuclear medicine is uniquely positioned to help because it can connect molecular biology with location, disease burden and change over time.
A blood test may indicate that a biomarker is present, while a biopsy may confirm that a sampled tumor expresses a target. Nuclear medicine can show where that target exists throughout the body, whether every lesion expresses it, whether a treatment reaches those lesions and how the disease responds. Together, those capabilities create the foundation of a continuous personalized-care system: identify the relevant biology, select the patient, deliver the treatment, measure the absorbed dose, evaluate each lesion and adjust the strategy when the biology changes.
Nuclear medicine will not replace genomics, pathology or circulating biomarkers. Its opportunity is to connect them with a whole-body view of disease that those tools cannot provide on their own. As healthcare moves toward increasingly targeted and individualized treatment, the specialty capable of making biology visible may be the one best positioned to lead.
