Evaluation of a computer-assisted diagnosis system, BONENAVI version 2, for bone scintigraphy in cancer patients in a routine clinical setting

Koizumi, Mitsuru; Wagatsuma, Kei; Miyaji, Noriaki; Murata, Takahiro; Miwa, Koichi; Takiguchi, Tomohiro; Makino, Tomoko; Koyama, Masamichi

doi:10.1007/s12149-014-0921-y

Cited by 42 publications

(35 citation statements)

References 14 publications

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“…The Japanese version of this software, BONENAVI (FUJIFILM RI Pharma, Tokyo, Japan), was modified using a cohort of Japanese patients [8, 9], and revised [11]. In the present study, we used ANN obtained using BONENAVI version 2.1.7. to analyze diagnostic accuracy.…”

Section: Discussionmentioning

confidence: 99%

“…These findings mean that the ANN value and sensitivity of BONENAVI are robust for the various CT types. We formerly reported that the ANN and sensitivity of BONENAVI were not different among the CT types in breast cancer or lung cancer patients with skeletal metastasis [9]. …”

Section: Discussionmentioning

confidence: 99%

“…Patients in whom BS revealed metastasis were further analyzed. The bone metastatic burden of these patients, as shown on BS, was scored using Soloway’s extent of disease (EOD) system [9]. Briefly, EOD scores were decided on the basis of number and extent of metastases.…”

Section: Methodsmentioning

confidence: 99%

“…A Japanese version of this software is BONENAVI. We formally published the development and clinical evaluation of a revised version, called BONENAVI II [9]. As above mentioned, skeletal metastases of prostate cancer are mostly osteoblastic, other types of skeletal metastasis exist.…”

Section: Introductionmentioning

confidence: 99%

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Diagnostic performance of a computer-assisted diagnosis system for bone scintigraphy of newly developed skeletal metastasis in prostate cancer patients: search for low-sensitivity subgroups

et al. 2017

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PurposeThe computer-assisted diagnostic system for bone scintigraphy (BS) BONENAVI is used to evaluate skeletal metastasis. We investigated its diagnostic performance in prostate cancer patients with and without skeletal metastasis and searched for the problems.MethodsAn artificial neural network (ANN) value was calculated in 226 prostate cancer patients (124 with skeletal metastasis and 101 without) using BS. Receiver operating characteristic curve analysis was performed and the sensitivity and specificity determined (cutoff ANN = 0.5). Patient’s situation at the time of diagnosis of skeletal metastasis, computed tomography (CT) type, extent of disease (EOD), and BS uptake grade were analyzed. False-negative and false-positive results were recorded.ResultsBONENAVI showed 82% (102/124) of sensitivity and 83% (84/101) specificity for metastasis detection. There were no significant differences among CT types, although low EOD and faint BS uptake were associated with low ANN values and low sensitivity. Patients showed lower sensitivity during the follow-up period than staging work-up. False-negative lesions were often located in the pelvis or adjacent to it. They comprised not only solitary, faint BS lesions but also overlaying to urinary excretion.ConclusionsBONENAVI with BS has good sensitivity and specificity for detecting prostate cancer’s osseous metastasis. Low EOD and faint BS uptake are associated with low sensitivity but not the CT type. Prostate cancer patients likely to have false-negative results during the follow-up period had a solitary lesion in the pelvis with faint BS uptake or lesions overlaying to urinary excretion.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Diagnostic performance of a computer-assisted diagnosis system for bone scintigraphy of newly developed skeletal metastasis in prostate cancer patients: search for low-sensitivity subgroups

et al. 2017

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“…Each individual hot spot was classified either as a metastasis or not as a metastasis by using an artificial neural network, and the BSI was calculated as the percentage of the sum of all hot spots classified as bone metastases using the artificial neural network values. To calculate BSI, we used Bonenavi version 2 (Fujifilm RI Pharma Co. Ltd., Tokyo, Japan; Exini Bone, Exini Diagnostics, Lund, Sweden) [11].…”

Section: Bone Scan Indexmentioning

confidence: 99%

Prediction of Time to Castration-Resistant Prostate Cancer Using Bone Scan Index in Men with Metastatic Hormone-Sensitive Prostate Cancer

Miyoshi

Yoneyama²,

Kawahara³

et al. 2017

Urol Int

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Introduction: We evaluated bone scan index (BSI) as a predictive biomarker for time to castration-resistant prostate cancer (CRPC) in patients with metastatic hormone-sensitive prostate cancer (mHSPC). Materials and Methods: We identified 85 consecutive mHSPC patients treated with first-line androgen deprivation therapy. We analyzed the correlations between time to CRPC and clinicopathological characteristics, including age, prostate-specific antigen (PSA) level, Gleason score, clinical TNM stage, hemoglobin, lactate dehydrogenase, C-reactive protein, and BSI. Results: The median BSI was 2.7%. Progression to CRPC occurred in 55 (64.7%) patients and the median time to CRPC was 12.9 months. In multivariate analysis, 3 significant risk factors for time to CRPC were identified: age (>73 vs. ≤73 years; hazard ratio [HR] 0.53), p = 0.038, PSA level (>270 vs. ≤270 ng/mL; HR 0.53, p = 0.038), and BSI (>2.7 vs. ≤2.7%; HR 2.97, p < 0.001). Conclusion: Age, PSA level, and BSI were found to be significant predictive factors for time to CRPC in patients with mHSPC.

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Prognostic value of automated bone scan index for predicting overall survival among bone metastatic castration resistant prostate cancer patients treated with radium‐223

et al. 2020

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Introduction The objective of this study was to evaluate automated bone scan index (aBSI) as a prognostic biomarker for overall survival (OS) in bone‐metastatic, castration‐resistant prostate cancer (mCRPC) patients treated with radium‐223 (Ra‐223). Materials and methods We identified 42 men treated with Ra‐223 for mCRPC. We investigated aBSI as an independent prognostic factor by multivariate analysis. Moreover, we evaluated the prognostic value of the aBSI after 12 weeks after the first cycle of Ra‐223 administration and aBSI change from baseline to after 12 weeks (ΔBSI). Results Median baseline PSA and aBSI were 42.8 ng/mL and 1.5%, respectively. Median OS was 20.7 months. Multivariate analysis showed that baseline aBSI was a significant prognostic factor for OS. The aBSI at 12 weeks after first Ra‐223 administration also exhibited significant prognostic value for OS, while we found no evidence of prognostic value for ΔBSI. Conclusions Baseline aBSI may be a significant prognostic factor for OS in bone‐metastatic CRPC patients treated with Ra‐223.

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Evaluation of a computer-assisted diagnosis system, BONENAVI version 2, for bone scintigraphy in cancer patients in a routine clinical setting

Abstract: BONENAVI version 2 is an effective computer-assisted diagnosis system for bone scanning, but the drawbacks of bone scanning remain unresolved.

Cited by 42 publications

References 14 publications

Diagnostic performance of a computer-assisted diagnosis system for bone scintigraphy of newly developed skeletal metastasis in prostate cancer patients: search for low-sensitivity subgroups

Diagnostic performance of a computer-assisted diagnosis system for bone scintigraphy of newly developed skeletal metastasis in prostate cancer patients: search for low-sensitivity subgroups

Prediction of Time to Castration-Resistant Prostate Cancer Using Bone Scan Index in Men with Metastatic Hormone-Sensitive Prostate Cancer

Prognostic value of automated bone scan index for predicting overall survival among bone metastatic castration resistant prostate cancer patients treated with radium‐223

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