Current applications of ex-vivo fluorescent confocal microscope in urological practice: a systematic review of literature
Highlight box
Key findings
• The review included 17 studies focusing on three urological issues: prostate cancer [15], bladder cancer [1], and renal biopsy [1].
• Fluorescent confocal microscopy (FCM) exhibited potential in distinguishing cancerous and non-cancerous prostate tissues (accuracy: 85.33–95.1%), assessing margins during cystectomy, and discerning normal renal parenchyma from cancerous tissue.
What is known and what is new?
• Histopathology, dating back to 1838, relies on hematoxylin & eosin (H&E) stains, which, while effective, are time-consuming. Technological advances demand a practical ‘real-time’ examination technique.
• FCM provides a ‘real-time’ examination technique without traditional processing. Successfully applied in dermatology, FCM is now being explored in urology for potential ‘real-time’ analysis.
• This systematic review aimed to provide an update on the applications of FCM in the urological field.
What is the implication, and what should change now?
• FCM's success in urology, especially in prostate and bladder cancer, indicates a possible move toward its clinical use for real-time pathological exams.
• Combining FCM with artificial intelligence (AI) for automated diagnosis, showcased in prostate cancer studies, offers efficient and time-saving pathological assessments.
• FCM’s value needs further confirmation as many studies are still in the experimental phase.
Introduction
The science of histopathology dates back to 1838, when Professor Johannes Müller of the University of Berlin published the first book about the utilization of microscopes in the pathological characterization of cancerous tissues (1). Similarly, specimen’s staining with hematoxylin & eosin (H&E) was first described during the second half of the 1800s (2). Despite conventional microscopic examination with H&E stains has successfully stood in the face of time preserving its position as the mainstay of histopathological examination for approximately 200 years, they are not devoid of limitations such as being a lengthy process that requires at least two-days turnaround time for surgical pathology reports at the highest quality pathological laboratories (3).
This time-consuming histopathological process does not cope with the technological advances in the medical and surgical fields that prioritize a patient-tailored management approach with improved surgical precision (4). These findings created a fundamental gap in the histopathological practice and set an urgent need for a practical ‘real-time’ pathological examination technique (5). Urology was not an exception, where ‘real-time’ pathological examination can be a game changing player as it may aid the surgical margins’ control in cancer surgeries (4), relieve the waiting-time related psychological stress (6), and achieve a ‘real-time’ diagnosis (7). In these settings, several options have been proposed to close this gap including -but not limited to- frozen section, confocal laser endomicroscopy, optical spectroscopy, optical coherence microscopy, multiphoton microscopy, and ex-vivo fluorescent confocal microscopy (FCM) (4). Most of these technologies are still in the experimental phase and none of which was actually introduced in real-life clinical practice except for frozen section, which is a relatively old procedure introduced in 1895; however, it was not able to completely close the aforementioned gap as it is still a time-consuming procedure that requires a highly dedicated and trained team in the operative room (8).
FCM (VivaScope 2500M-G4, MAVIG GmbH, Munich, Germany; Caliber I.D.; Rochester, NY, USA) is an optical technology that allows fast ex-vivo examination of freshly excised tissue specimens without conventional processing (9). The ex-vivo FCM system is mainly composed of two sources of laser lights with two different wavelengths: 488 nm (blue) and 785 nm (infrared) that allow the fusion of fluorescent and reflectance modes, respectively. The blue laser is mainly used for the excitation of the Acridine Orange dye (in which the specimen were soaked for 30 seconds before examination) to highlight cellular microstructures including the nucleus, while the reflectance mode is based on the light reflection from the different subcellular structures based on their refractive indices (7). The FCM includes an integrated software algorithm that creates digital images similar to the conventional histopathology slides (H&E like images) (10). Technically, the FCM is characterized by a vertical resolution of 4 µm with a maximum penetration depth of 200 µm. It allows a maximum magnification power of 550× with a resolution of 1,024×1,024 pixels and a maximum scan area of 25×25 mm (8). Another FCM is the Histolog® Scanner (SamanTree Medical SPA, Lausanne, Switzerland), which is a Conformité Européene (CE) approved wide field fluorescent confocal laser scanning microscope for superficial examination of large biological specimens up to 48×36 mm with 2 µm lateral resolution and maximum penetration depth of 30 µm. The device uses laser of wavelength 488 nm for fluorescent excitation and subsequently fluorescent emission is collected at wavelength above 500 nm). The device is integrated with touch screen for navigation of the digital images and an algorithm that allows purpule coloration of the black and white images (11). The FCM has been successfully applied mainly in the dermatological field for different purposes including skin cancers, inflammatory skin diseases, and cutaneous infections (12). Furthermore, its potential applications have been explored in other disciplines including the intraoperative evaluation in laryngeal lesions (13), the analysis of breast tissues (14), the evaluation of different tissues such as lung, liver, adrenal gland, kidney, bone, pleura, and lymph nodes (15), and the urological field (9).
The current systematic review of literature aims to provide an update of the available evidence on the current applications of FCM in the urological field. We present this article in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) reporting checklist (available at https://cco.amegroups.com/article/view/10.21037/cco-23-150/rc).
Methods
Search strategy
This systematic review of literature was conducted following the PRISMA statement (16). Two databases (PubMed and SCOPUS) were initially searched on the 3rd of October 2022 to identify all the records concerned with the use of FCM in the urological field. The only filter applied during the search process was the date filter to include articles published after the 1st of January 2018 as the first publication about the use of FCM in the urological field was published during early 2019 (8). The following keywords were used for the search process (“confocal laser microscope” OR “Fluorescent confocal microscope” OR “Fluorescent confocal microscopy” OR “Confocal laser microscopy” OR “Vivascope” OR “Fluorescence laser microscope” OR “confocal microscope”) AND (“prostate” OR “bladder” OR “renal” OR “kidney” OR “urothelial”).
Search criteria
The inclusion criteria for the current review consisted of all original articles discussing the potential applications of FCM in the urological field. Considering the exclusion criteria, study design and publication type were not considered as an exclusion parameter except for review articles. Furthermore, the articles were excluded if they were published before the 1st of January 2018, non-English, or if the authors were not able to retrieve the full text of the manuscript.
Screening and article selection
Initially, the list of articles retrieved from both databases were combined in Mendeley reference manager (Elsevier Ltd., Netherlands), where de-duplication was performed using the “check for duplicates” option followed by manual revision of the results. Thereafter, two independent authors (A.E. and N.R.P.) conducted the initial screening process of all the identified records by the title and the abstract to exclude all irrelevant manuscripts. Subsequently, the two authors performed a full-text assessment of the remaining articles to identify the manuscripts that will be included in the current systematic review. Any disagreement that arises during the search process was resolved by a third author (S.P.). Finally, the cited references of the included articles were reviewed manually to determine any relevant articles that might be missing.
Data extraction
The following data were extracted from the included articles in an Excel sheet; reference, country of study, study period, number of specimens in the study, the sensitivity, specificity, and accuracy of the FCM in comparison to the gold standard H&E examination. Similar to the search process, data extraction was independently conducted by the same two authors.
Quality assessment
Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to assess the quality of the included studies (17). The assessment of the risk of bias was carried out by two authors separately (N.R.P. and S.P.) and any discrepancies were resolved.
Results
Search results
The systematic search resulted in 192 reports, of which 64 were duplicate and were excluded. The remaining 128 records were initially screened by the title and abstract, which resulted in the further exclusion of 107 records as they were not relevant to the aim of the current review. Subsequently, 21 records qualified for the full text review, of which five records were excluded for different reasons. Finally, 17 manuscripts met our inclusion criteria and were included in the current review (due to the small number of articles we decided to include also the research correspondence about the use of FCM in urology) (7,8,10,18-31). Figure 1 shows the PRISMA flow diagram of the search process. Table 1 summarizes the included studies.
Table 1
Reference | Number of specimens | Application | Time (min) | Accuracy (Cohen’s Kappa) | AUC | Sensitivity | Specificity | PPV | NPV | Inter-rater reliability |
---|---|---|---|---|---|---|---|---|---|---|
Gobbo, 2023 (10) | Overall (75) | Prostate biopsy | 9 | 85.33% | NA | NA | NA | 100% | 100% | 0.95 |
69 specimens from prostate biopsy | ||||||||||
3 specimens from prostatectomy | ||||||||||
3 specimens from transplant donor | ||||||||||
Bianchi, 2023 (19) | Overall (506) | Prostate biopsy (AI & FCM for detection of malignancy) | NA | 86% | 0.93 | 80% | 88% | NA | NA | NA |
Prata, 2023 (25) | Overall (138) | Radical cystectomy | <5 | 83.3% (k=0.691) | NA | 66.7% | 97.5% | 80% | 95.1% | NA |
46 urethral specimens | ||||||||||
46 left ureter | 77.8% (k=0.481) | NA | 53.8% | 90.9% | 70% | 83.3% | ||||
46 right ureter | ||||||||||
Sighinolfi, 2023 (22) | NA | En-bloc TURBT (to confirm presence of muscle layer) | NA | 100% | NA | NA | NA | NA | NA | NA |
TURBT (to confirm presence of muscle layer) | 100% | |||||||||
Renal biopsy | NA | |||||||||
Radical prostatectomy (surgical margins control) | 100% | |||||||||
Sievert, 2022 (29) | Overall (438) | Prostate biopsy (identifying patients requiring intervention) | NA | (k=0.88) | NA | 93% | 95% | 93% | 95% | NA |
Titze, 2022 (30) | Overall (127) | Radical prostatectomy (prostate cancer biobanking) | 4–5 | 90.5% (k=0.84) | NA | NA | NA | NA | NA | NA |
Titze, 2021 (27) | Overall (438) | Prostate biopsy | NA | Pathologist 1: (k=0.90) | NA | 85.3% | 100% | 100% | 97.1% | NA |
Pathologist 2: (k=0.85) | 89.3% | 98.6% | 93.1% | 96.5% | ||||||
Rocco, 2021 (31) | Overall (427) | Prostate biopsy | 2 | 95.1% (k=0.84) | 0.92 | 86.3% | 97.2% | 88.5% | 96.7% | 0.95 |
Selvaggio, 2021 (20) | Overall (76) | Prostate biopsy (for margins assessment after cryoablation) | 2 | NA | NA | NA | NA | NA | NA | NA |
Baas, 2023 (21)* | Overall (96) | Radical prostatectomy (for surgical margins control) | 8 | (k=0.80) | NA | 86% | 96% | 80% | 98% | NA |
Bertoni, 2020 (28) | Overall (80) | Radical prostatectomy | 5 | Pathologist 1: 86% (k=0.68) | 0.87 | 90% | 85% | NA | NA | NA |
Pathologist 2: 92% (k=0.79) | 0.87 | 76% | 98% | |||||||
Rocco, 2020 (26) | Overall (41) | Radical prostatectomy (surgical margins assessment) | 1–2 | NA | NA | NA | NA | NA | NA | NA |
Marenco, 2021 (7) | Overall (182) | Prostate biopsy | 5 | 90.66% (k=0.81) | NA | 93.15% | 88.99% | 85% | 95.1% | NA |
Rocco, 2020 (24) | Overall (36) | Radical prostatectomy (Mohs technique for margins control) | NA | 100% | NA | NA | NA | NA | NA | NA |
Titze, 2021 (18) | Overall (121) | Prostate biopsy | 5 | Pathologist 1: (k=0.86) | NA | 79% | 100% | NA | NA | NA |
Pathologist 2: (k=0.79) | 68% | 100% | ||||||||
Mir, 2020 (23) | Overall (8) | Renal biopsy cores | 1–2 | NA | NA | NA | NA | NA | NA | NA |
Puliatti, 2019 (8) | Overall (89) | Radical prostatectomy specimen | 5 | 91% (k=0.75) | 0.884 | 83.33% | 93.53% | NA | NA | 0.808 |
*, Histolog® Scanner was used. AUC, area under the curve; PPV, positive predictive value; NPV, negative predictive value; NA, not applicable; AI, artificial intelligence; FCM, fluorescent confocal microscopy; TURBT, transurethral resection of bladder tumor.
Studies characteristics
Of the 17 articles finally included in the current systematic review, four records were published as research correspondence, editorial, or short communication (19,23,24,26). Ten articles (58.8%) were conducted in a prospective design (7,8,10,18,20,22,26,27,30,31), while five authors (29.4%) did not highlight whether their study were carried out in a prospective or retrospective manner (19,21,23,24,28). The majority of the studies were carried out in Italy (58.8%) (8,10,19,20,22,24-26,28,31), followed by Germany (23.5%) (18,27,29,30), Spain (11.8%) (7,23), and Netherlands (5.9%) (21). Generally, 15 manuscripts (88.2%) of the included articles were concerned with the applications of FCM in the prostate cancer field (7,8,10,18-22,24,26-31), with only two manuscripts highlighting the FCM in patients with bladder cancer (22,25), and two discussing its value in patients undergoing renal biopsies (22,23). All the included studies reported the use of VivaScope® 2500M-G4 (MAVIG GmbH, Munich, Germany; Caliber I.D.; Rochester, NY, USA) except for one study, where the authors reported the use of Histolog® Scanner (SamanTree Medical SPA, Lausanne, Switzerland) (21).
Quality assessment
Figure 2 shows the authors’ assessment of the risk of bias of the included 17 records based on the QUADAS-2 tool. This tool mainly evaluates four domains for risk of bias including; patient selection, index test, the reference test, and the flow and timing and the related applicability of these domains to the question of the current review (17). Since the question of the current review is an open question assessing mainly the potential applications of the FCM in urological patients, there were few concerns regarding the applicability; however, it should be noted that the methodology of most of the included studies was not able to provide a sufficient answer for our review question as most of these studies are still in the initial feasibility phase. Most concerns were related to the patients’ selection in the included studies as the majority of studies did not report a precise inclusion criterion (Table 2). Histopathology was reported as the reference standard in all the included studies; however, there was unclear to high concerns about the timing of the reference and the blinding of pathologists in approximately 35% of the included studies. On the contrary, the flow and timing was satisfactory in most of the included studies (70%) demonstrating a low risk of bias.
![Click on image to zoom](http://cdn.amegroups.cn/journals/amepc/files/journals/12/articles/124342/public/124342-PB7-8168-R1.jpg/w300)
Table 2
Study | Risk of bias | Applicability concerns | ||||||
---|---|---|---|---|---|---|---|---|
Patient selection | Index test | Reference standard | Flow and timing | Patient selection | Index test | Reference standard | ||
Marenco, 2021 | ? | ☺ | ☺ | ☺ | ☺ | ☺ | ☺ | |
Puliatti, 2019 | ? | ? | ? | ☺ | ☺ | ☺ | ☺ | |
Gobbo, 2023 | ? | ☺ | ☺ | ☺ | ? | ☺ | ☺ | |
Titze, 2021 | ? | ? | ☺ | ☺ | ☺ | ☺ | ☺ | |
Bianchi, 2023 | ☹ | ? | ☹ | ? | ☹ | ☹ | ☹ | |
Selvaggio, 2021 | ☺ | ☺ | ☺ | ☺ | ☺ | ☺ | ☺ | |
Baas, 2023 | ☺ | ? | ☹ | ☺ | ☺ | ☺ | ☺ | |
Sighinolfi, 2023 | ? | ☺ | ? | ? | ☺ | ☺ | ☺ | |
Mir, 2020 | ☺ | ? | ? | ? | ☺ | ☺ | ☺ | |
Rocco, 2020 | ? | ? | ☺ | ☺ | ☺ | ☺ | ☺ | |
Prata, 2023 | ☺ | ☺ | ☺ | ☺ | ☺ | ☺ | ☺ | |
Rocco, 2020 | ☺ | ☺ | ? | ☺ | ☺ | ☺ | ☺ | |
Titze, 2021 | ☺ | ☺ | ☺ | ☺ | ☺ | ☺ | ☺ | |
Bertoni, 2020 | ☺ | ☺ | ☺ | ? | ☺ | ☺ | ☺ | |
Sievert, 2022 | ? | ☺ | ☺ | ☺ | ☺ | ☺ | ☺ | |
Titze, 2022 | ☺ | ☺ | ☺ | ? | ☺ | ☺ | ☺ | |
Rocco, 2021 | ☺ | ☺ | ☺ | ☺ | ☺ | ☺ | ☺ |
☺, low risk; ☹, high risk; ?, unclear risk.
Specimen processing and preparation
All the authors followed the instructions provided by the manufacturer (7,8,10,18-20,22-31). After the specimen is obtained, it is initially placed on tissue foam pads and treated with pure alcohol for approximately 10 seconds to allow protein precipitation and subsequently enhance the contrast. Thereafter, the specimen is incubated in Acridine Orange dye (AO, 0.6 mm; Sigma-Aldrich®, St. Louis, MO, USA) for approximately 30 seconds. This dye acts as a selective intercalating fluorochrome for nucleic-acids (18). However, it should be noted that one study reported incubating the specimen in Acridine Orange for 60 seconds (25). Then excess Acridine orange is washed by rinsing the specimen in normal saline (0.9%). Finally, the specimen is placed on absorbent paper and embedded between two glass slides for examination with FCM (8). Generally, specimen’s processing and scanning ranged from an average 2–9 minutes across the included studies (10,20) (Table 1).
In line with that, specimen processing for the Histolog® Scanner is similar to that of the VivaScope 2500. The specimen is soaked in a fluorescent dye (Histolog Dip, SamanTree Medical SPA) for 10 seconds followed by rinsing with normal saline. Finally, the specimen is placed in the Histolog® dish for scanning (21).
Prostate cancer
In 2019, Puliatti and colleagues from the university of Modena & Reggio Emilia, introduced the FCM technology for the first to the urological field, when they assessed FCM’s diagnostic accuracy in differentiation between cancerous and non-cancerous tissues of the prostate compared to the gold standard histopathological examination. The authors demonstrated substantial agreement of 91% between both techniques with a high sensitivity (83.33%) and specificity (93.53%) (8). Few months later, the same group published their study assessing the learning curve of FCM interpretation for pathologists and providing an atlas for prostatic and periprostatic tissues. The authors showed that interpretation of FCM images is characterized by a short learning curve as a result of the great similarity between the FCM images and the H&E slides (28). Since the publication of these two studies and several authors showed interest in the potential benefits of FCM in the urological field and particularly for patients with prostate cancer (7,10,18-22,24,26,27,29-30).
Urologists have always fascinated about a technology that can provide ‘real-time’ diagnosis of prostate biopsy specimens. Initially, frozen section was considered as the technique that can fulfill this fascination; however, frozen section is not recommended for prostate biopsy cores as its assessment of Gleason grading is unreliable (7). In this setting, Rocco et al. (31), and Marenco et al. (7), included 427 and 182 prostate specimens to assess the potential value of applying the FCM in the setting of prostate biopsy, respectively. Both studies reported high accuracy (95.1% and 90.66%, respectively) with almost perfect inter-rater agreement (k=0.84 and 0.81, respectively), highlighting the reliability of this technology in the ‘real-time’ evaluation of prostate biopsy cores (7,31). Noteworthy, both studies did not evaluate the concordance between FCM and histopathology as regards the Gleason grade as they were not designed for the primary evaluation of this point perse and due to the lack of experience in evaluation of Gleason grading using FCM (7,31); however, Rocco et al. assessed the ability of FCM to discriminate between International Society of Urological Pathology (ISUP) grade 1 and >1 tumors as a secondary outcome reporting a moderate inter-rater agreement of 80.9% with moderate inter-rater reliability (k=0.49) (31). Interestingly, Marenco et al. (7) assessed the diagnostic performance of FCM at the level of region or interests [regions with visible lesions on multiparameteric magnetic resonance imaging (mpMRI) and PIRADS ≥3] demonstrating accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Cohen’s kappa of 84.62%, 88.57%, 80%, 83.78%, 85.71%, and 0.69, respectively.
These findings were further confirmed and validated in several studies reporting a diagnostic accuracy of 85.33%, an inter-rater agreement ranging from (k=0.79–0.90), sensitivity ranging from 68–93%, specificity ranging from 95–100%, PPV ranging from 93–100%, and NPV ranging from (95–97.1%) (10,18,27,29). Considering the Gleason grade, Gobbo et al. (10) demonstrated a high agreement among ISUP grades I, IV, and V (k=0.85); however, for ISUP grade II and III the agreement was much lower (k=0.62). Similar to the study of Rocco (31), Titze et al. (18) reported that FCM is characterized by moderate agreement (k=0.46–0.53) as regards the discrimination of ISUP grade 1 and >1 tumors. Interestingly, FCM was able to identify 13/14 prostate cancer patients requiring intervention [ISUP grade >1, >50% infiltration of the biopsy core, and/or prostate-specific antigen (PSA) ≥10 ng/mL] based on the analysis of mpMRI fusion biopsy with a sensitivity of 93%, specificity of 95%, PPV of 93%, and NPV of 95%, reflecting its potential clinical value (29). Furthermore, the group from the University of Modena and Reggio Emilia took a further step forward, when they combined the potentiality of FCM and artificial intelligence (AI) to provide an automated diagnosis of prostate cancer. The authors used 307 high resolution FCM images as a training set for the AI-algorithm and 107 images for testing and validation of the model, reporting an AUC of 0.93, sensitivity of 80%, and specificity of 88%. This could be a time-saving change in the field of pathology as it may guide the pathologist to mainly examine the areas highlighted as neoplastic by the machine (19).
‘Real-time’ intraoperative assessment of surgical margins during radical prostatectomy is crucial to allow nerve-sparing surgery without compromising the oncological outcomes (24). This FCM application was initially proposed in two research correspondence (24,26). The first research correspondence presented the concept of intraoperative surgical margins’ assessment using FCM among 20 patients (26), while the second research correspondence suggested the use of Mohs section of the posterolateral margins of the radical prostatectomy specimen as combination to FCM to enhance surgical margins’ control reporting a 100% agreement among FCM and H&E analysis as regards the differentiation of cancerous and benign peri-prostatic tissues (24). This application can ensure the safety of nerve-sparing approach to radical prostatectomy during the initial phase of the learning curve of trainees (22). In these settings, Baas et al. (21) used the FCM (Histolog® Scanner) for ‘real-time’ assessment of 96 posterolateral prostate margins in 50 patients undergoing nerve sparing robotic assisted radical prostatectomy reporting a sensitivity, specificity, PPV, and NPV of 86%, 96%, 80%, and 98%, respectively. The authors demonstrated a substantial level of agreement (k=0.80) between FCM and frozen section for detection of positive surgical margins (21).
Interestingly, Selvaggio et al. (20) demonstrated that FCM can be effectively applied for the intraoperative digital evaluation of ablation margins in patients undergoing partial prostate cryoablation. Furthermore, VivaScope 2500 permitted microscopic analysis of prostate cancer biobank samples to ensure their tumor capacity before their cryopreservation without compromising their quality rendering this technology a less demanding alternative to frozen section (30).
Bladder cancer
FCM can play an important role in the management of patients with bladder cancer. Initially, it can be used to ensure the presence of detrusor muscle layer in specimens obtained through transurethral resection of bladder tumor (either en-bloc or piecemeal resection) (22). Furthermore, it can be used for the ‘real-time’ analysis of ureteral and urethral margins of the radical cystectomy specimens (25). Recently, Prata et al. (25) compared the diagnostic performance of FCM versus frozen section and histopathological analysis in patients undergoing radical cystectomy. Considering the concordance between FCM and frozen section examination of the urethral margins was substantial with Cohen’s kappa of 0.776, sensitivity of 80%, specificity of 97.8%, PPV of 80%, and NPV of 97.6%, while at the ureteral level the sensitivity was 69.2%, specificity was 97%, PPV was 90%, and NPV was 88.9%. On the other hand, the agreement between FCM and histopathological analysis was substantial for the urethral margins (k=0.691) and moderate for the ureteral margins (k=0.481). The sensitivity, specificity, PPV, and NPV were 66.7%, 97.5%, 80%, and 95.1% for the urethral margins, and 53.8%, 90.9%, 70%, and 83.3% for the ureteral margins, respectively (25).
Renal biopsy
Finally, FCM may potentially be used for ‘real-time’ analysis of renal biopsy cores (22). In this setting, Mir et al. (23), used FCM for examination of eight renal biopsy cores obtained from four patients demonstrating that FCM was capable of differentiating normal renal parenchyma from cancerous tissue in 100% of cases.
Discussion
The main concept of different types of confocal microscope is the rejection of out-of-focus light, which was initially presented by Marvin Minsky in the late 1950s (32). This function is obtained through focusing the illumination and detection optics over the same diffraction-field of view, which is subsequently advanced through the tissue specimen to create a complete image on the detector. Thus, in contrast to light microscopy, any out of focus light shares a little to the created image, which reduces the haziness and allows optical sectioning (33). Prostate cancer is the second most common male malignancy rendering it the most common cancer managed by urologists (34). Thus, it was not surprising that ex-vivo FCM was mainly applied to aid the management of prostate cancer. Prostate biopsy is the initial step in the diagnosis and management of prostate cancer (35). The current turnaround time for surgical biopsy is two working days at the highest quality laboratories (36). This delay between the biopsy procedure and the pathological diagnosis is associated with several concerns including psychological distress of the patient and inadequate sampling requiring repeated biopsy (6,37). Additionally, rapid pathological examination of biopsy specimens may be beneficial in preserving fresh specimens for molecular/genomic analysis and research (35). Noteworthy, prostate biopsy cores differ from intraoperative radical prostatectomy specimens as they are smaller and more fragile requiring meticulous handling and processing with accurate Gleason scoring (which may be clinically irrelevant for intraoperative margin assessment) (35). Keeping in mind all these concerns, the search for new technologies providing ‘real-time’ histopathological diagnosis emerged as an urgent need. Ex-vivo FCM has shown promising results for ‘real-time’ pathological examination of prostate biopsy specimen with an accuracy ranging from 85.33% to 95.1% (7,10,18,27,29,31). Other technologies have been proposed to provide a ‘real-time’ diagnosis of prostate biopsy cores such as nonlinear microscopy (35), stimulated Raman histology (37), and open-top light-sheet microscopy (38,39). The Stimulated Raman Histology is the image created using the Stimulated Raman Scattering Microscopy, which utilizes two laser beams (pump beams and stokes beams) to augment the Raman signal of particular chemical bonds in different macromolecules such as lipids, proteins and nucleic acids (40). This technology has been applied for histopathological analysis of prostate biopsy specimens showing a diagnostic accuracy of 95.7%; however, it should be noted that the biopsy was obtained from a radical prostatectomy specimen and not through a prostate biopsy procedure, thus the real implication of this technology is yet to be assessed (37). Furthermore, the stimulated Raman scattering microscopy is usually associated with longer imaging times and lower signal to noise ratio in case of absent physical sectioning in reflectance mode (41). Nonlinear microscopy is another promising technology that can eventually fulfill the need for a ‘real-time’ histopathological assessment technology. This microscope is similar to FCM in that it uses short-pulsed laser beams to excite specimens’ fluorescence with a maximum penetration depth of 100 µm allowing the creation of H&E-like digital images (41). The nonlinear microscopy has been applied to prostate biopsy practice showing a high sensitivity (92%) and specificity (100%) for detection of prostate cancer as compared to conventional histopathological examination (35). In line with these findings, Xie et al. (39) reported the use of open-top light-sheet microscopy for the rapid examination of prostate biopsy cores (in what they call one-hour-to-diagnosis of 12 prostate biopsies set) demonstrating a high accuracy of more than 90%. All these technologies are promising and can be “game-changer” in the field of prostate biopsy; however, the main concern about these technologies is related to high interobserver variability as regards Gleason scoring. It is worth mentioning that this high-grade variability is also present in the conventional H&E analysis (35,42).
Radical prostatectomy is the “gold standard” treatment for patients with clinically localized prostate cancer and life expectancy of more than 10 years (43,44). However, urologists must always use an operative approach to balance between the desirable functional outcomes (continence and erectile function) and the oncological outcomes (avoidance of positive surgical margins). Nerve-sparing approach to radical prostatectomy may provide this balance if surgeons were able to exclude the risk of positive surgical margins and extracapsular extension of prostate cancer (4). Considering that nomograms are unreliable when it comes to extracapsular extension of prostate cancer (45,46), urologists adopted frozen section as the gold standard technique for surgical margins control during radical prostatectomy surgery (4,47,48). Yet, frozen section of the surgical margin is a relatively old technique that was initially described in 1895 and it requires a well-trained and dedicated team in the operative room (4). A recent review of literature highlighted those new technologies such as optical coherence tomography, photodynamic diagnosis with 5-aminolevulinic acid, light reflectance spectroscopy, confocal laser endomicroscopy, and structured illumination microscopy have all been proposed as an alternative for frozen section in surgical margins assessment during radical prostatectomy. However, the authors argued that these technologies will suffer to get implemented in real-life medical practice for different reasons such as the surgical workflow that might hamper the signal, the long processing and scanning time, and the comparisons with H&E analysis (48). Ex-vivo FCM has just taken few steps forward as it has been combined with the NeuroSAFE approach of frozen section (49) to shorten the processing and imaging times, reduce the number of required persons in the operative rooms, and subsequently reduce the cost of surgery (21).
FCM still have a lot of potentials to be explored. Instant digital biopsy provided by ex-vivo FCM can allow patients undergoing prostate biopsy to undergo an immediate focal ablation of cancer in case of small localized unilateral tumor. Furthermore, in the field of benign prostatic hyperplasia it can alleviate the suspicious of malignancy in patients with elevated PSA without the need for postponement of surgery (9).
The workflow of specimen preparation and interpretation using FCM is simple. Particularly, the preparation of the specimen for examination by the FCM can be easily performed by a trained nurse or technician without the need for a pathologist or urologist. Furthermore, the resulting images can be sent electronically to a remote pathologist for interpretation, which limits the need for a pathologist in the operating theater (8). Moreover, the combination between AI and FCM can reduce the time needed for slides interpretation and reduce the human errors (19). In this setting, the introduction of this system in the clinical practice can reduce the hands-on-working-time of pathologists and urologists.
This study is not devoid of limitations. Firstly, the review included research correspondence and short communications (which are usually studies with incomplete data); however, this could be related to the scarcity of data about this topic in the literature. Secondly, there was a great heterogeneity among the included studies which prevented us from performing a meta-analysis for the results. Yet, this review covers a topic of current interest and open the door for further research to evaluate the clinical benefit of FCM in real-life practice.
Conclusions
Ex-vivo fluorescent confocal microscope is a promising technology that can be applied in different aspects of urological practice such as prostate cancer, renal biopsy, and bladder cancer. Particularly, the prostate cancer has been a field of increased publications for the confocal microscope such as its application for prostate biopsy analysis and radical prostatectomy digital margin assessment. However, most of the published studies are still in the experimental phase and further studies are required to confirm its value.
Acknowledgments
Funding: None.
Footnote
Provenance and Peer Review: This article was commissioned by the editorial office, Chinese Clinical Oncology for the series “New Evidence and Advances in Surgical Treatment of Prostate Cancer”. The article has undergone external peer review.
Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://cco.amegroups.com/article/view/10.21037/cco-23-150/rc
Peer Review File: Available at https://cco.amegroups.com/article/view/10.21037/cco-23-150/prf
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://cco.amegroups.com/article/view/10.21037/cco-23-150/coif). The series “New Evidence and Advances in Surgical Treatment of Prostate Cancer” was commissioned by the editorial office without any funding or sponsorship. D.C. served as the unpaid Guest Editor of the series and serves as an unpaid Editorial Board Member of Chinese Clinical Oncology from August 2022 to July 2024. S.P. and S.F. also served as the unpaid Guest Editors of the series. The authors have no other conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
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