- NSF-PAR ID:
- 10028630
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Journal of Magnetic Resonance Imaging
- Volume:
- 46
- Issue:
- 1
- ISSN:
- 1053-1807
- Page Range / eLocation ID:
- 184 to 193
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Introduction The high incidence of prostate cancer, coupled with excellent prostate cancer control rates, has resulted in growing interest in nononcological survivorship issues such as sexual function. Multiparametric magnetic resonance imaging (MRI) is increasingly being performed for local staging of prostate cancer, and due to the close anatomical relationship to the prostate, penile enhancement is often depicted in prostate MRI.
Aim To evaluate the associations between quantitative perfusion-related parameters derived from dynamic contrast-enhanced (DCE)-MRI of the penis and self-reported sexual function in patients with newly diagnosed prostate cancer.
Methods This retrospective study included 50 patients who underwent DCE-MRI for prostate cancer staging before prostatectomy. The following perfusion-related parameters were calculated: volume transfer constant (Ktrans), rate constant (kep), extracellular-extravascular volume fraction (ve), contrast enhancement ratio (CER), area under the gadolinium curve after 180 seconds (AUC180), and slope of the time/signal intensity curve of the corpora cavernosa. Associations between perfusion-related parameters and self-reported sexual function were evaluated using the Wilcoxon Rank-Sum test.
Main Outcome Measures Patient responses to the sexual function domain of the Prostate Quality of Life survey.
Results Five of the six DCE-MRI parameters (Ktrans, ve, CER, AUC180, and slope) were significantly associated with the overall score from the sexual domain of the survey (P = 0.0020–0.0252). CER, AUC180, and slope were significantly associated with the answers to all six questions (P = 0.0020–0.0483), ve was significantly associated with the answers to five of six questions (P = 0.0036–0.1029), and Ktrans was significantly associated with the answers to three of six questions (P = 0.0252–0.1023). kep was not significantly associated with the overall survey score (P = 0.7665) or the answers to any individual questions (P = 0.4885–0.8073).
Conclusion Penile DCE-MRI parameters were significantly associated with self-reported sexual function in patients with prostate cancer. These parameters are readily available when performing prostate MRI for staging and may be relevant to the management of patients considering prostate cancer therapies.
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Abstract Prostate cancer treatment decisions rely heavily on subjective visual interpretation [assigning Gleason patterns or International Society of Urological Pathology (ISUP) grade groups] of limited numbers of two‐dimensional (2D) histology sections. Under this paradigm, interobserver variance is high, with ISUP grades not correlating well with outcome for individual patients, and this contributes to the over‐ and undertreatment of patients. Recent studies have demonstrated improved prognostication of prostate cancer outcomes based on computational analyses of glands and nuclei within 2D whole slide images. Our group has also shown that the computational analysis of three‐dimensional (3D) glandular features, extracted from 3D pathology datasets of whole intact biopsies, can allow for improved recurrence prediction compared to corresponding 2D features. Here we seek to expand on these prior studies by exploring the prognostic value of 3D shape‐based nuclear features in prostate cancer (e.g. nuclear size, sphericity). 3D pathology datasets were generated using open‐top light‐sheet (OTLS) microscopy of 102 cancer‐containing biopsies extracted
ex vivo from the prostatectomy specimens of 46 patients. A deep learning‐based workflow was developed for 3D nuclear segmentation within the glandular epithelium versus stromal regions of the biopsies. 3D shape‐based nuclear features were extracted, and a nested cross‐validation scheme was used to train a supervised machine classifier based on 5‐year biochemical recurrence (BCR) outcomes. Nuclear features of the glandular epithelium were found to be more prognostic than stromal cell nuclear features (area under the ROC curve [AUC] = 0.72 versus 0.63). 3D shape‐based nuclear features of the glandular epithelium were also more strongly associated with the risk of BCR than analogous 2D features (AUC = 0.72 versus 0.62). The results of this preliminary investigation suggest that 3D shape‐based nuclear features are associated with prostate cancer aggressiveness and could be of value for the development of decision‐support tools. © 2023 The Pathological Society of Great Britain and Ireland. -
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Abstract Even in the 21st century, prostate cancer remains the second leading cause of cancer‐related death for men. Since a normal prostate gland has a high ZnIIcontent and there are huge differences in ZnIIcontent between healthy and malignant prostate cancer cells, mobile zinc can be used as a biomarker for prostate cancer prediction. A highly efficient surface enhanced Raman spectroscopy (SERS) probe using a
p ‐(imidazole)azo)benzenethiol attached gold nanoparticle as a Raman reporter, which has the capability to identify prostate cancer cells based on ZnIIsensing, has been designed. A facile synthesis, characterization and evaluation of a ZnIIsensing Raman probe are described. Reported data indicate that after binding with ZnII, Raman reporter attached to a gold nanoparticle forms an assembly structure, which allows selective detection of ZnIIeven at 100 ppt concentration. Theoretical full‐wave finite‐difference time‐domain (FDTD) simulations have been used to understand the enhancement of the SERS signal. The SERS probe is highly promising for in vivo sensing of cancer, where near‐IR light can be easily used to avoid tissue autofluorescence and to enhance tissue penetration depth. Reported data show that the SERS probe can distinguish metastatic cancer cells from normal prostate cells very easily with a sensitivity as low as 5 cancer cells mL−1. The probe can be used as a chemical toolkit for determining mobile ZnIIconcentrations in biological samples.
