ArticleTranslational oncology2015
Quantitative ultrasound spectroscopic imaging for characterization of disease extent in prostate cancer patients.
Article in Translational oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 25 citations in OpenAlex.
- Developments in Ultrasound-Based Imaging for Prostate Cancer Detection.The Prostate · 2025Review
- A first-in-human study of quantitative ultrasound to assess transplant kidney fibrosis.Nature medicine · 2025Article
- Multiparametric Ultrasound Imaging of Prostate Cancer Using Deep Neural Networks.Ultrasound in medicine & biology · 2024Article
- Evaluation of prostate cancer detection using micro-ultrasound versus MRI through co-registration to whole-mount pathology.Scientific reports · 2024Article
- Deep learning of quantitative ultrasound multi-parametric images at pre-treatment to predict breast cancer response to chemotherapy.Scientific reports · 2022Article
- Characterizing intra-tumor regions on quantitative ultrasound parametric images to predict breast cancer response to chemotherapy at pre-treatment.Scientific reports · 2021Article
- Quantitative MRI Biomarkers of Stereotactic Radiotherapy Outcome in Brain Metastasis.Scientific reports · 2019Article
- Ultrasound Elastography of the Prostate Using an Unconstrained Modulus Reconstruction Technique: A Pilot Clinical Study.Translational oncology · 2017Review
- Interpretation of cardiac wall motion from cine-MRI combined with parametric imaging based on the Hilbert transform.Magma (New York, N.Y.) · 2017Article
- Photoacoustic signal characterization of cancer treatment response: Correlation with changes in tumor oxygenation.Photoacoustics · 2017Article
- Quantification of Ultrasonic Scattering Properties of In Vivo Tumor Cell Death in Mouse Models of Breast Cancer.Translational oncology · 2015Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Three-dimensional quantitative ultrasound spectroscopic imaging of prostate was investigated clinically for the noninvasive detection and extent characterization of disease in cancer patients and compared to whole-mount, whole-gland histopathology of radical prostatectomy specimens. Fifteen patients with prostate cancer underwent a volumetric transrectal ultrasound scan before radical prostatectomy. Conventional-frequency (~5MHz) ultrasound images and radiofrequency data were collected from patients. Normalized power spectra were used as the basis of quantitative ultrasound spectroscopy. Specifically, color-coded parametric maps of 0-MHz intercept, midband fit, and spectral slope were computed and used to characterize prostate tissue in ultrasound images. Areas of cancer were identified in whole-mount histopathology specimens, and disease extent was correlated to that estimated from quantitative ultrasound parametric images. Midband fit and 0-MHz intercept parameters were found to be best associated with the presence of disease as located on histopathology whole-mount sections. Obtained results indicated a correlation between disease extent estimated noninvasively based on midband fit parametric images and that identified histopathologically on prostatectomy specimens, with an r(2) value of 0.71 (P<.0001). The 0-MHz intercept parameter demonstrated a lower level of correlation with histopathology. Spectral slope parametric maps offered no discrimination of disease. Multiple regression analysis produced a hybrid disease characterization model (r(2)=0.764, P<.05), implying that the midband fit biomarker had the greatest correlation with the histopathologic extent of disease. This work demonstrates that quantitative ultrasound spectroscopic imaging can be used for detecting prostate cancer and characterizing disease extent noninvasively, with corresponding gross three-dimensional histopathologic correlation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.