Re: Diagnostic Accuracy of Multiparametric MRI versus 68Ga-PSMA-11 PET/MRI for Extracapsular Extension and Seminal Vesicle Invasion in Patients with Prostate Cancer

2020 ◽  
Vol 203 (2) ◽  
pp. 253-254
Author(s):  
Samir S. Taneja
Radiology ◽  
2019 ◽  
Vol 293 (2) ◽  
pp. 350-358 ◽  
Author(s):  
Urs J. Muehlematter ◽  
Irene A. Burger ◽  
Anton S. Becker ◽  
Khoschy Schawkat ◽  
Andreas M. Hötker ◽  
...  

2007 ◽  
Vol 53 (2) ◽  
pp. 233-240 ◽  
Author(s):  
Thomas Steuber ◽  
Andrew J Vickers ◽  
Angel M Serio ◽  
Ville Vaisanen ◽  
Alexander Haese ◽  
...  

Abstract Background: We evaluated the association of total and free forms of serum human kallikrein 2 (hK2) and prostate-specific antigen (PSA) with prostate cancers of unfavorable prognosis. Methods: We retrospectively measured total PSA (tPSA), free PSA (fPSA), and total hK2 (thK2) in preoperative serum samples from 867 men [and assessed free hK2 (fhK2) measured in 577 of these men] treated with radical prostatectomy for clinically localized prostate cancer. Associations between biomarker concentrations and extracapsular extension, seminal vesicle invasion, and biochemical recurrence (BCR) were evaluated. A subset of patients with PSA ≤10 μg/L, the group most commonly seen in clinical practice in the US, was analyzed. Results: thK2 was the strongest predictor of extracapsular extension and seminal vesicle invasion (areas under the ROC curve [AUC], 0.662 and 0.719, respectively), followed by tPSA (AUC, 0.654 and 0.663). All biomarkers were significant predictors of BCR. hK2 forms, but not PSA forms, remained highly significant for predicting BCR in the low-PSA group. Combining tPSA, fPSA, and thK2 in a multivariable model improved prediction compared with any biomarker used individually (AUC, 0.711, 0.755, and 0.752 for this combination predicting extracapsular extension, seminal vesicle invasion, and BCR, respectively; P <0.001 for all). Conclusions: Increased concentrations of hK2 in the blood are significantly associated with unfavorable features of prostate cancer, and thK2 is predictive of locally advanced and recurrent cancer in patients with PSA ≤10 μg/L. Independent of tPSA and fPSA, hK2 predicts unfavorable prognosis.


2021 ◽  
Vol 20 (1) ◽  
pp. 10-12
Author(s):  
Mallinath Biradar ◽  

Background: The incidence of prostatic carcinoma is increasing worldwide. With its high resolution, ability to provide excellent tissue characterization and multiplanar imaging capabilities, multi-parametric magnetic resonance imaging (mpMRI) plays a crucial role in detection, local staging and follow-up of carcinoma prostate. It also helps guide targeted biopsies in initial biopsy negative patient. Objectives: Study diagnostic accuracy of mp-MRI and primarily that of the three MR sequences T2, DWI and DCE in detection of prostatic cancer by correlating them with histopathology and thus whether it is feasible for a short MRI of 3 sequences to be used on a large scale in Indian scenario. Materials and Methods: A prospective study was done at a tertiary care hospital between April 2017 to November 2018 in which 50 patients who presented with suspicion of prostate cancer were referred to radiology department for evaluation using MRI. MRIexamination was done using 3T Siemens Magnetom Verio. Followed by this MRI directed TRUS guided cognitive fusion biopsy was done from the prostate. Samples were sent for histopathology. Results: Out of 50 cases studied, 24 cases (48%) were found to be malignant and 26 cases (52 %) were benign on histopathology. In our study, combined T2 + DWI + DCE gave sensitivity of 95.83 %, specificity of 57.69%, positive predictive value of 68.21 % and negative predictive value of 93.75%. Conclusion: Multiparametric MRI using T2, DWI and DCE has a high diagnostic accuracy for evaluation of prostatic cancer.


2021 ◽  
Author(s):  
Ying Hou ◽  
Yi-Hong Zhang ◽  
Jie Bao ◽  
Mei-Ling Bao ◽  
Guang Yang ◽  
...  

Abstract Purpose: A balance between preserving urinary continence and achievement of negative margins is of clinical relevance while implementary difficulty. Preoperatively accurate detection of prostate cancer (PCa) extracapsular extension (ECE) is thus crucial for determining appropriate treatment options. We aimed to develop and clinically validate an artificial intelligence (AI)-assisted tool for the detection of ECE in patients with PCa using multiparametric MRI. Methods: 849 patients with localized PCa underwent multiparametric MRI before radical prostatectomy were retrospectively included from two medical centers. The AI tool was built on a ResNeXt network embedded with a spatial attention map of experts’ prior knowledges (PAGNet) from 596 training data sets. The tool was validated in 150 internal and 103 external data sets, respectively; and its clinical applicability was compared with expert-based interpretation and AI-expert interaction.Results: An index PAGNet model using a single-slice image yielded the highest areas under the receiver operating characteristic curve (AUC) of 0.857 (95% confidence interval [CI], 0.827-0.884), 0.807 (95% CI, 0.735-0.867) and 0.728 (95% CI, 0.631-0.811) in the training, internal test and external test cohorts, compared to the conventional ResNeXt networks. For experts, the inter-reader agreement was observed in only 437/849 (51.5%) patients with a Kappa value 0.343. And the performance of two experts (AUC, 0.632 to 0.741 vs 0.715 to 0.857) was lower (paired comparison, all p values < 0.05) than that of AI assessment. When expert’ interpretations were adjusted by the AI assessments, the performance of both two experts was improved.Conclusion: Our AI tool, showing improved accuracy, offers a promising alternative to human experts for imaging staging of PCa ECE using multiparametric MRI.


Sign in / Sign up

Export Citation Format

Share Document