When it comes to prostate cancer (PCa) imaging, accurate detection lies in the details.1 And you can’t treat what you can’t detect. Using optimal technology, targets, tracers, and tools such as PET, PSMA, 18F, and AI systems could improve diagnostic performance and help pave the way for more informed prostate cancer treatment decisions.1-5
Unmet Need in Prostate Cancer Imaging
Is the prostate cancer imaging currently available to you, giving you ALL the information you need?
Current imaging can sometimes be suboptimal for the management of prostate cancer1
Accurate detection of the extent of prostate cancer disease lies in the details. The initial staging of high-risk prostate cancer or the restaging of biochemically recurrent (BCR) prostate cancer informs treatment approach.1
However, current guidelines for the management of patients with prostate cancer were established using conventional imaging—such as computed tomography (CT), magnetic resonance imaging (MRI), and bone scans—all of which have some limitations.1
CT and Bone Scans have some limitations for bone lesion detection1
- Evaluation of bone metastases is of key importance, since it is a major contributor to disease-related morbidity and mortality.1
- While standards for interpreting conventional scans are well established, conventional imaging has a very low sensitivity for early detection of bone marrow lesions until there is a reactive marrow response and progressive sclerosis. What’s more, the pattern of CT-detected sclerotic bone lesions may differ from typical widespread metastases, resulting in a range of diagnoses from benign to malignant.1
- Bone scans can survey the whole body for skeletal metastases and can help narrow a differential diagnosis. However, they lack specificity, as they may detect osteoblastic activity (including healing following therapy) rather than the tumor itself.1
CT and MRI largely rely on size and shape1
In prostate cancer, CT and MRI are used for the detection of metastatic nodal disease. However, these modalities rely on morphologic characteristics such as size and shape. Considering that 80% of nodal metastases are smaller than 8 mm, the likelihood of detection of metastatic disease with CT and MRI alone is diminished.1
Furthermore, non-metastatic nodes may be enlarged due to benign conditions like reactive hyperplasia, which can lead to false positives.1
CT and MRI can lack optimal specificity1,9
As for metastatic disease detected in the liver or lungs, lesions noted on CT scans or MRIs often have a range of differential diagnoses, which may be further resolved by their imaging characteristics or additional imaging. That said, these imaging modalities may not offer optimal specificity.1
In addition, while MRIs are currently embraced for localizing recurrence in the prostate bed as well as pelvic lymph node and bone recurrence, patients with post-treatment scarring and fibrosis may see false positives.9
Conventional imaging may not detect metastases with a lower PSA range1,10
Conventional imaging has a lower detection rate for metastatic disease than PET, particularly in the lower PSA (prostate-specific antigen) range.1 In fact, MRIs and CT scans rarely show disease recurrence at low (<1.0 ng/mL) serum PSA levels.10
- Relies on indirect visualization of tumor tissue despite the fact that marrow lesions are generally invisible until there is a reactive response
- Is subject to high false-negative rates for nodal staging of primary intermediate-to-high risk or metastatic prostate cancer as well as high false-positive rates
- Relies primarily on size for detection of nodal metastasis
- Is limited with regard to early detection of bone metastases
- Is not optimal for the detection of metastases with a lower PSA range
Suboptimal imaging may lead to missed opportunities1,8,11
Suboptimal imaging can lead to delayed intervention, less informed treatment choices, inappropriate overtreatment for some patients, and occasionally inadvertent removal of hope from those who may otherwise have qualified for treatment.
Limitations fuel innovation
Fortunately, the limitations of conventional imaging have forged the development of transformative imaging approaches that promise heightened sensitivity and specificity for the detection of prostate cancer.12
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7. Duffy IR, Boyle AJ, Vasdev N. Improving PET imaging acquisition and analysis with machine learning: a narrative review with focus on alzheimer’s disease and oncology. Molecular Imaging. 2018;1-11. doi:10.1177/1536012119869070
8. PET/CT - Positron Emission Tomography/Computed Tomography. RadiologyInfo.org. Updated August 1, 2019. Accessed May 12, 2020. https://www.radiologyinfo.org/en/info.cfm?pg=PET.
9. Bhargava P, Ravizzini G, Chapin, BF, et al. Imaging biochemical recurrence after prostatectomy; where are we headed? Genitourinary Imaging. 2019;1248-1258. doi.org/10.2214/AJR.19.21905
10. Taneja, S. Imaging in the diagnosis and management of prostate cancer. Rev Urol. 2004;6(3):101-113.
11. Padhani R, Lecouvet FE, Tunariu N, et al. Rationale for modernizing imaging in advanced prostate cancer. Eur Urol Focus. 2017;3(2-3):223-229.
12. Rowe SP, Gorin, MA, Allaf ME, et al. PET imaging of prostate-specific membrane antigen in prostate cancer: current state of the art and future challenges. Prostate Cancer Prostatic Dis. 2016 Sep;19(3):223-30. doi:10.1038/pcan.2016.13