2524 Prognostic value of bone scan index (BSI) using computer-aided diagnosis system for bone scans in hormone-naive prostate cancer patients with bone metastases

2015 ◽  
Vol 51 ◽  
pp. S482
Author(s):  
S. Yoneyama ◽  
Y. Miyoshi ◽  
M. Moriyama ◽  
K. Uemura ◽  
S. Takebayashi ◽  
...  
2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 225-225
Author(s):  
Yasuhide Miyoshi ◽  
Masato Yasui ◽  
Shuko Yoneyama ◽  
Koichi Uemura ◽  
Takashi Kawahara ◽  
...  

225 Background: Recently, the CHAARTED and STAMPEDE studies showed a survival benefit for docetaxel when started with androgen deprivation therapy (ADT) in men with newly diagnosed metastatic hormone-sensitive prostate cancer (mHSPC). While GETUG-AFU 15 failed to demonstrate a survival benefit of early chemotherapy. New biomarker for select the candidate for early chemotherapy in mHSPC is warranted. The objective of this study is to evaluate the bone scan index (BSI) using computer-aided diagnosis system for bone scans for predictive factor in patients receiving ADT as first-line hormone therapy for mHSPC. Methods: We identified consecutive 85 mHSPC patients treated with maximum androgen blockade (MAB) as first-line hormone therapy. We analyzed the correlations between progression-free survival (PFS) of MAB and clinicopathological characteristics, including patients’ age, initial PSA levels, Gleason scores, clinical TNM stage, hemoglobin (Hb), lactase dehydrogenase (LDH), c-reactive protein (CRP), and bone scan index (BSI). Statistical analyses were assessed using cox proportional hazards regression models. Results: The median patients’ age was 73 and the median follow-up duration was 11.3months. The median initial PSA value was 270 ng/ml. Median BSI was 2.7 % (range: 0.0-14.6). Clinical or PSA progression occurred in 55 (64.7%) patients. The median time to progression was 12.9 months. In multivariate analysis, three significant risk factors for PFS were identified; patients’ age ( > 73 years old vs ≤ 73; HR 0.53, p = 0.038), initial PSA levels ( > 270 ng/mL vs ≤ 270; HR 0.53, p = 0.038), and BSI ( > 2.7 vs ≤ 2.7; HR 3.0, p < 0.000). We stratified the patients into two cohorts with low risk (0-1 risk factor present) and high risk (2-3 risk factors present). We found a significant difference in PFS among risk groups (median PFS 15.3 months vs 8.5, p < 0.000). Conclusions: Patients’ age, initial PSA levels, and bone scan index were the significant predictive factors for MAB as first-line hormone therapy in patients with mHSPC. These findings might support the decision-making of induction of early chemotherapy for mHSPC.


Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 973
Author(s):  
Valentina Giannini ◽  
Simone Mazzetti ◽  
Giovanni Cappello ◽  
Valeria Maria Doronzio ◽  
Lorenzo Vassallo ◽  
...  

Recently, Computer Aided Diagnosis (CAD) systems have been proposed to help radiologists in detecting and characterizing Prostate Cancer (PCa). However, few studies evaluated the performances of these systems in a clinical setting, especially when used by non-experienced readers. The main aim of this study is to assess the diagnostic performance of non-experienced readers when reporting assisted by the likelihood map generated by a CAD system, and to compare the results with the unassisted interpretation. Three resident radiologists were asked to review multiparametric-MRI of patients with and without PCa, both unassisted and assisted by a CAD system. In both reading sessions, residents recorded all positive cases, and sensitivity, specificity, negative and positive predictive values were computed and compared. The dataset comprised 90 patients (45 with at least one clinically significant biopsy-confirmed PCa). Sensitivity significantly increased in the CAD assisted mode for patients with at least one clinically significant lesion (GS > 6) (68.7% vs. 78.1%, p = 0.018). Overall specificity was not statistically different between unassisted and assisted sessions (94.8% vs. 89.6, p = 0.072). The use of the CAD system significantly increases the per-patient sensitivity of inexperienced readers in the detection of clinically significant PCa, without negatively affecting specificity, while significantly reducing overall reporting time.


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