MRI/Transrectal Ultrasound Fusion-Guided Targeted Biopsy and Transrectal Ultrasound-Guided Systematic Biopsy for Diagnosis of Prostate Cancer: A Systematic Review and Meta-analysis

Xie, Jianfeng; Jin, Chen; Liu, Mengmeng; Sun, Kening; Jin, Zhanqiang; Ding, Zhongxiang; Gong, Xun

doi:10.3389/fonc.2022.880336

Cited by 17 publications

(14 citation statements)

References 53 publications

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“…The advancement in prostate cancer diagnosis has developed MRI-TRUS fusion-guided needle biopsies to efficiently predict prostate cancer [ 49 , 50 ]. The technique is time-consuming and laborious, so AI has been introduced to automate the process to reduce the burden on clinicians.…”

Section: Resultsmentioning

confidence: 99%

Artificial Intelligence for Clinical Diagnosis and Treatment of Prostate Cancer

Rabaan

Bakhrebah

AlSaihati

et al. 2022

Cancers

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As medical science and technology progress towards the era of “big data”, a multi-dimensional dataset pertaining to medical diagnosis and treatment is becoming accessible for mathematical modelling. However, these datasets are frequently inconsistent, noisy, and often characterized by a significant degree of redundancy. Thus, extensive data processing is widely advised to clean the dataset before feeding it into the mathematical model. In this context, Artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL) algorithms based on artificial neural networks (ANNs) and their types, are being used to produce a precise and cross-sectional illustration of clinical data. For prostate cancer patients, datasets derived from the prostate-specific antigen (PSA), MRI-guided biopsies, genetic biomarkers, and the Gleason grading are primarily used for diagnosis, risk stratification, and patient monitoring. However, recording diagnoses and further stratifying risks based on such diagnostic data frequently involves much subjectivity. Thus, implementing an AI algorithm on a PC’s diagnostic data can reduce the subjectivity of the process and assist in decision making. In addition, AI is used to cut down the processing time and help with early detection, which provides a superior outcome in critical cases of prostate cancer. Furthermore, this also facilitates offering the service at a lower cost by reducing the amount of human labor. Herein, the prime objective of this review is to provide a deep analysis encompassing the existing AI algorithms that are being deployed in the field of prostate cancer (PC) for diagnosis and treatment. Based on the available literature, AI-powered technology has the potential for extensive growth and penetration in PC diagnosis and treatment to ease and expedite the existing medical process.

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Section: Resultsmentioning

confidence: 99%

Artificial Intelligence for Clinical Diagnosis and Treatment of Prostate Cancer

Rabaan

Bakhrebah

AlSaihati

et al. 2022

Cancers

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“…Проведение МР-прицельной биопсии, предположительно, снижает выявление клинически незначимых форм РПЖ. При выполнении мпМР/УЗ fusion-биопсии выявляемость клинически незначимого РПЖ меньше по сравнению со стандартной биопсией, что подтверждается данными исследований MRI-FIRST (5,6 и 19,5 %; p <0,001) и 4M (14 и 25 %; p <0,001) [14,20], а также метаанализа, в котором показано, что выявляемость клинически незначимого РПЖ ниже при выполнении МР-прицельной биопсии по сравнению со стандартной (относительный риск 0,65; 95 % доверительный интервал 0,55-0,77; p <0,001) [23]. Тем не менее результаты нашей работы не подтверждают это предположение, что, в свою очередь, согласуется с данными, полученными H. Goldberg и соавт.…”

Section: Discussionunclassified

“…В ряде работ отмечается более высокая общая выявляемость РПЖ при проведении мпМР/УЗ fusion-биопсии, чем при стандартной биопсии [23,25]. Однако при сравнении общей выявляемости РПЖ в исследовании M. Kroenig и соавт.…”

Section: Discussionunclassified

Prospective study of prostate cancer detection using multiparametric magnetic resonance imaging ultrasound-guided fusion, standard, and saturation biopsy

et al. 2023

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Background. Currently, about 80 % of men with low-grade prostate cancer (per ISUP 1 (International Society of Urological Pathology)) have indications for radical treatment. Overdiagnosis of low-grade cancer is associated with the use of systematic biopsy methods (standard transrectal, saturation) under ultrasound control for diagnosis verification. To improve prostate cancer diagnosis, the European Association of Urology (2019) recommended multiparametric magnetic resonance imaging before biopsy, and in case of detection of a suspicious lesion magnetic resonance imaging (MRI)-targeted biopsy. In clinical practice, the most common method of MRI-targeted biopsy is multiparametric MRI ultrasound-guided (mpMRI/US) fusion biopsy. However, some studies show contradictory results in detection of prostate cancer using systematic and MRI-targeted biopsy techniques.Aim. To compare detection of clinically significant prostate cancer (ISUP ≥2) using mpMRI/US fusion, standard, and saturation biopsy.Materials and methods. The study included 96 patients. The following inclusion criteria were applied: prostate-specific antigen >2 ng/mL and/or detection of a suspicious lesion during digital rectal and/or transrectal ultrasound examination, and PI-RADS (Prostate Imaging Reporting and Data System) v.2.1 score ≥3. At the first stage, “unblinded” urologist performed a transperineal mpMRI/US fusion and saturation biopsies. At the second stage, “blinded” urologist performed standard transrectal biopsy. Clinically significant cancer was defined as ISUP ≥2.Results. Median age was 63 years, prostate volume – 47 cm3, prostate-specific antigen – 6.82 ng/mL. MpMRI/US fusion, standard, and saturation biopsies were comparable in regard to the rate of detection of clinically significant (29, 24, 28 %; p = 0.81) and clinically insignificant (25, 26, 35 %; p = 0.43) cancer. Overall prostate cancer detection rates were also similar: 54, 50, 63 %, respectively (p = 0.59). The percentages of positive cores in mpMRI/US fusion, standard, and saturation biopsies were 33, 10 and 13 %, respectively (p <0.01). The maximal core length in mpMRI/US was 6.4 mm, in standard biopsy – 6.35 mm, in saturation biopsy – 5.1 mm (p = 0.7).Conclusion. Detection rates of clinically significant, clinically insignificant prostate cancer and overall detection rate are comparable between systematic biopsy techniques and mpMRI/US fusion biopsy.

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“…Meanwhile, mpMRI-TRUS fusion imaging has been advocated for clinical application. Xie [ 17 ] analyzed the literature on mpMRI-TRUS fusion imaging from 2012 to 2021 and showed that the fusion imaging-guided TB had a higher detection rate of csPCa. Similarly, we confirmed that TB was higher than SB for detecting csPCa (p < 0.05) but our results included the TB guided by mpUS.…”

Section: Discussionmentioning

confidence: 99%

The combined value of mpUS and mpMRI-TRUS fusion for the diagnosis of clinically significant prostate cancer

2022

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Objective To evaluate the combined efficacy of multiparametric ultrasonography (mpUS) and multiparametric magnetic resonance imaging/transrectal ultrasound (mpMRI-TRUS) fusion for detecting clinically significant prostate cancer (csPCa). Methods From November 2019 to September 2021, biopsy-naïve patients underwent mpMRI-TRUS fusion imaging combined with mpUS-guided targeted biopsies (TB) and systematic biopsies (SB). To further evaluate the additional diagnostic value of mpUS, the imaging features of 202 focus obtained from fusion imaging were assessed. The diagnostic accuracies of mpMRI-TRUS fusion imaging and the combination of mpMRI-TRUS fusion imaging with mpUS for csPCa were comparatively evaluated. Results A total of 202 prostate lesions (160 patients) were included in the final analysis, of which 105 were csPCa, 16 were ciPCa, and 81 were noncancerous. The median patient age was 69 (65–73) years and the median tPSA was 22.07 (11.22–62.80) ng/mL. For csPCa, the detection rate of TB was higher than that of SB (50.0% vs. 45.5%, p < 0.05). The imaging characteristics of mpUS in the PCa and non-PCa groups were significantly different (p < 0.001). When compared with mpMRI-TRUS fusion imaging, the positive predictive value, false positive rate, and area under the curve (AUC) of csPCa diagnosis by mpMRI-TRUS fusion imaging combined with mpUS increased by 11.30%, decreased by 19.58%, and increased from 0.719 to 0.770 (p < 0.05), respectively. Conclusion TB can improve the detection rate of csPCa and hence can be effectively used in the diagnosis and risk assessment of csPCa. The mpUS-enriched valuable diagnostic information for mpMRI-TRUS fusion imaging and their combination showed a higher diagnostic value for csPCa, which can guide subsequent clinical treatment.

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MRI/Transrectal Ultrasound Fusion-Guided Targeted Biopsy and Transrectal Ultrasound-Guided Systematic Biopsy for Diagnosis of Prostate Cancer: A Systematic Review and Meta-analysis

Cited by 17 publications

References 53 publications

Artificial Intelligence for Clinical Diagnosis and Treatment of Prostate Cancer

Artificial Intelligence for Clinical Diagnosis and Treatment of Prostate Cancer

Prospective study of prostate cancer detection using multiparametric magnetic resonance imaging ultrasound-guided fusion, standard, and saturation biopsy

The combined value of mpUS and mpMRI-TRUS fusion for the diagnosis of clinically significant prostate cancer

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