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Ongaro L, Rossin G, Biasatti A, Pacini M, Rizzo M, Traunero F, Piasentin A, Perotti A, Trombetta C, Bartoletti R, Zucchi A, Simonato A, Pavan N, Liguori G, Claps F. Fluorescence Confocal Microscopy in Urological Malignancies: Current Applications and Future Perspectives. Life (Basel) 2023; 13:2301. [PMID: 38137902 PMCID: PMC10744992 DOI: 10.3390/life13122301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 11/29/2023] [Accepted: 12/03/2023] [Indexed: 12/24/2023] Open
Abstract
Fluorescence confocal microscopy (FCM) represents a novel diagnostic technique able to provide real-time histological images from non-fixed specimens. As a consequence of its recent developments, FCM is gaining growing popularity in urological practice. Nevertheless, evidence is still sparse, and, at the moment, its applications are heterogeneous. We performed a narrative review of the current literature on this topic. Papers were selected from the Pubmed, Embase, and Medline archives. We focused on FCM applications in prostate cancer (PCa), urothelial carcinoma (UC), and renal cell carcinoma (RCC). Articles investigating both office and intraoperative settings were included. The review of the literature showed that FCM displays promising accuracy as compared to conventional histopathology. These results represent significant steps along the path of FCM's formal validation as an innovative ready-to-use diagnostic support in urological practice. Instant access to a reliable histological evaluation may indeed significantly influence physicians' decision-making process. In this regard, FCM addresses this still unmet clinical need and introduces intriguing perspectives into future diagnostic pathways. Further studies are required to thoroughly assess the whole potential of this technique.
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Affiliation(s)
- Luca Ongaro
- Urological Clinic, Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy; (L.O.); (G.R.); (A.B.); (M.R.); (F.T.); (A.P.); (C.T.); (G.L.)
| | - Giulio Rossin
- Urological Clinic, Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy; (L.O.); (G.R.); (A.B.); (M.R.); (F.T.); (A.P.); (C.T.); (G.L.)
| | - Arianna Biasatti
- Urological Clinic, Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy; (L.O.); (G.R.); (A.B.); (M.R.); (F.T.); (A.P.); (C.T.); (G.L.)
| | - Matteo Pacini
- Urology Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy; (M.P.); (A.P.); (R.B.); (A.Z.)
| | - Michele Rizzo
- Urological Clinic, Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy; (L.O.); (G.R.); (A.B.); (M.R.); (F.T.); (A.P.); (C.T.); (G.L.)
| | - Fabio Traunero
- Urological Clinic, Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy; (L.O.); (G.R.); (A.B.); (M.R.); (F.T.); (A.P.); (C.T.); (G.L.)
| | - Andrea Piasentin
- Urological Clinic, Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy; (L.O.); (G.R.); (A.B.); (M.R.); (F.T.); (A.P.); (C.T.); (G.L.)
| | - Alessandro Perotti
- Urology Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy; (M.P.); (A.P.); (R.B.); (A.Z.)
| | - Carlo Trombetta
- Urological Clinic, Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy; (L.O.); (G.R.); (A.B.); (M.R.); (F.T.); (A.P.); (C.T.); (G.L.)
| | - Riccardo Bartoletti
- Urology Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy; (M.P.); (A.P.); (R.B.); (A.Z.)
| | - Alessandro Zucchi
- Urology Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy; (M.P.); (A.P.); (R.B.); (A.Z.)
| | - Alchiede Simonato
- Urology Clinic, Department of Surgical, Oncological and Stomatological Sciences, University of Palermo, 90127 Palermo, Italy; (A.S.); (N.P.)
| | - Nicola Pavan
- Urology Clinic, Department of Surgical, Oncological and Stomatological Sciences, University of Palermo, 90127 Palermo, Italy; (A.S.); (N.P.)
| | - Giovanni Liguori
- Urological Clinic, Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy; (L.O.); (G.R.); (A.B.); (M.R.); (F.T.); (A.P.); (C.T.); (G.L.)
| | - Francesco Claps
- Urological Clinic, Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy; (L.O.); (G.R.); (A.B.); (M.R.); (F.T.); (A.P.); (C.T.); (G.L.)
- Urology Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy; (M.P.); (A.P.); (R.B.); (A.Z.)
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Rodriguez Peñaranda N, Eissa A, Ferretti S, Bianchi G, Di Bari S, Farinha R, Piazza P, Checcucci E, Belenchón IR, Veccia A, Gomez Rivas J, Taratkin M, Kowalewski KF, Rodler S, De Backer P, Cacciamani GE, De Groote R, Gallagher AG, Mottrie A, Micali S, Puliatti S. Artificial Intelligence in Surgical Training for Kidney Cancer: A Systematic Review of the Literature. Diagnostics (Basel) 2023; 13:3070. [PMID: 37835812 PMCID: PMC10572445 DOI: 10.3390/diagnostics13193070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 09/17/2023] [Accepted: 09/24/2023] [Indexed: 10/15/2023] Open
Abstract
The prevalence of renal cell carcinoma (RCC) is increasing due to advanced imaging techniques. Surgical resection is the standard treatment, involving complex radical and partial nephrectomy procedures that demand extensive training and planning. Furthermore, artificial intelligence (AI) can potentially aid the training process in the field of kidney cancer. This review explores how artificial intelligence (AI) can create a framework for kidney cancer surgery to address training difficulties. Following PRISMA 2020 criteria, an exhaustive search of PubMed and SCOPUS databases was conducted without any filters or restrictions. Inclusion criteria encompassed original English articles focusing on AI's role in kidney cancer surgical training. On the other hand, all non-original articles and articles published in any language other than English were excluded. Two independent reviewers assessed the articles, with a third party settling any disagreement. Study specifics, AI tools, methodologies, endpoints, and outcomes were extracted by the same authors. The Oxford Center for Evidence-Based Medicine's evidence levels were employed to assess the studies. Out of 468 identified records, 14 eligible studies were selected. Potential AI applications in kidney cancer surgical training include analyzing surgical workflow, annotating instruments, identifying tissues, and 3D reconstruction. AI is capable of appraising surgical skills, including the identification of procedural steps and instrument tracking. While AI and augmented reality (AR) enhance training, challenges persist in real-time tracking and registration. The utilization of AI-driven 3D reconstruction proves beneficial for intraoperative guidance and preoperative preparation. Artificial intelligence (AI) shows potential for advancing surgical training by providing unbiased evaluations, personalized feedback, and enhanced learning processes. Yet challenges such as consistent metric measurement, ethical concerns, and data privacy must be addressed. The integration of AI into kidney cancer surgical training offers solutions to training difficulties and a boost to surgical education. However, to fully harness its potential, additional studies are imperative.
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Affiliation(s)
- Natali Rodriguez Peñaranda
- Department of Urology, Azienda Ospedaliero-Universitaria di Modena, Via Pietro Giardini, 1355, 41126 Baggiovara, Italy; (N.R.P.); (A.E.); (S.F.); (G.B.); (S.D.B.); (S.M.)
| | - Ahmed Eissa
- Department of Urology, Azienda Ospedaliero-Universitaria di Modena, Via Pietro Giardini, 1355, 41126 Baggiovara, Italy; (N.R.P.); (A.E.); (S.F.); (G.B.); (S.D.B.); (S.M.)
- Department of Urology, Faculty of Medicine, Tanta University, Tanta 31527, Egypt
| | - Stefania Ferretti
- Department of Urology, Azienda Ospedaliero-Universitaria di Modena, Via Pietro Giardini, 1355, 41126 Baggiovara, Italy; (N.R.P.); (A.E.); (S.F.); (G.B.); (S.D.B.); (S.M.)
| | - Giampaolo Bianchi
- Department of Urology, Azienda Ospedaliero-Universitaria di Modena, Via Pietro Giardini, 1355, 41126 Baggiovara, Italy; (N.R.P.); (A.E.); (S.F.); (G.B.); (S.D.B.); (S.M.)
| | - Stefano Di Bari
- Department of Urology, Azienda Ospedaliero-Universitaria di Modena, Via Pietro Giardini, 1355, 41126 Baggiovara, Italy; (N.R.P.); (A.E.); (S.F.); (G.B.); (S.D.B.); (S.M.)
| | - Rui Farinha
- Orsi Academy, 9090 Melle, Belgium; (R.F.); (P.D.B.); (R.D.G.); (A.G.G.); (A.M.)
- Urology Department, Lusíadas Hospital, 1500-458 Lisbon, Portugal
| | - Pietro Piazza
- Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy;
| | - Enrico Checcucci
- Department of Surgery, FPO-IRCCS Candiolo Cancer Institute, 10060 Turin, Italy;
| | - Inés Rivero Belenchón
- Urology and Nephrology Department, Virgen del Rocío University Hospital, 41013 Seville, Spain;
| | - Alessandro Veccia
- Department of Urology, University of Verona, Azienda Ospedaliera Universitaria Integrata, 37126 Verona, Italy;
| | - Juan Gomez Rivas
- Department of Urology, Hospital Clinico San Carlos, 28040 Madrid, Spain;
| | - Mark Taratkin
- Institute for Urology and Reproductive Health, Sechenov University, 119435 Moscow, Russia;
| | - Karl-Friedrich Kowalewski
- Department of Urology and Urosurgery, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany;
| | - Severin Rodler
- Department of Urology, University Hospital LMU Munich, 80336 Munich, Germany;
| | - Pieter De Backer
- Orsi Academy, 9090 Melle, Belgium; (R.F.); (P.D.B.); (R.D.G.); (A.G.G.); (A.M.)
- Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, 9000 Ghent, Belgium
| | - Giovanni Enrico Cacciamani
- USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA;
- AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, CA 90089, USA
| | - Ruben De Groote
- Orsi Academy, 9090 Melle, Belgium; (R.F.); (P.D.B.); (R.D.G.); (A.G.G.); (A.M.)
| | - Anthony G. Gallagher
- Orsi Academy, 9090 Melle, Belgium; (R.F.); (P.D.B.); (R.D.G.); (A.G.G.); (A.M.)
- Faculty of Life and Health Sciences, Ulster University, Derry BT48 7JL, UK
| | - Alexandre Mottrie
- Orsi Academy, 9090 Melle, Belgium; (R.F.); (P.D.B.); (R.D.G.); (A.G.G.); (A.M.)
| | - Salvatore Micali
- Department of Urology, Azienda Ospedaliero-Universitaria di Modena, Via Pietro Giardini, 1355, 41126 Baggiovara, Italy; (N.R.P.); (A.E.); (S.F.); (G.B.); (S.D.B.); (S.M.)
| | - Stefano Puliatti
- Department of Urology, Azienda Ospedaliero-Universitaria di Modena, Via Pietro Giardini, 1355, 41126 Baggiovara, Italy; (N.R.P.); (A.E.); (S.F.); (G.B.); (S.D.B.); (S.M.)
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Ali SN, Tano Z, Landman J. The Changing Role of Renal Mass Biopsy. Urol Clin North Am 2023; 50:217-225. [PMID: 36948668 DOI: 10.1016/j.ucl.2023.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
The incidence and prevalence of small renal masses (SRMs) continues to rise and with increased detection comes increases in surgical management, although the probability of an SRM being benign is upward of 30%. An extirpative treatment first diagnose-later strategy persists and clinical tools for risk stratification such as renal mass biopsy remain severely underutilized. The overtreatment of SRMs has multiple detrimental effects including surgical complications, psychosocial stress, financial loss, and reduced renal function leading to downstream effects such as the need for dialysis and cardiovascular disease.
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Affiliation(s)
| | - Zachary Tano
- Department of Urology, University of California, Irvine, CA, USA
| | - Jaime Landman
- Department of Urology, University of California, Irvine, CA, USA.
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Puliatti S, Eissa A, Checcucci E, Piazza P, Amato M, Scarcella S, Rivas JG, Taratkin M, Marenco J, Rivero IB, Kowalewski KF, Cacciamani G, El-Sherbiny A, Zoeir A, El-Bahnasy AM, De Groote R, Mottrie A, Micali S. New imaging technologies for robotic kidney cancer surgery. Asian J Urol 2022; 9:253-262. [PMID: 36035346 PMCID: PMC9399539 DOI: 10.1016/j.ajur.2022.03.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 01/19/2022] [Accepted: 03/16/2022] [Indexed: 11/21/2022] Open
Abstract
Objective Kidney cancers account for approximately 2% of all newly diagnosed cancer in 2020. Among the primary treatment options for kidney cancer, urologist may choose between radical or partial nephrectomy, or ablative therapies. Nowadays, robotic-assisted partial nephrectomy (RAPN) for the management of renal cancers has gained popularity, up to being considered the gold standard. However, RAPN is a challenging procedure with a steep learning curve. Methods In this narrative review, different imaging technologies used to guide and aid RAPN are discussed. Results Three-dimensional visualization technology has been extensively discussed in RAPN, showing its value in enhancing robotic-surgery training, patient counseling, surgical planning, and intraoperative guidance. Intraoperative imaging technologies such as intracorporeal ultrasound, near-infrared fluorescent imaging, and intraoperative pathological examination can also be used to improve the outcomes following RAPN. Finally, artificial intelligence may play a role in the field of RAPN soon. Conclusion RAPN is a complex surgery; however, many imaging technologies may play an important role in facilitating it.
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Ellebrecht DB, Latus S, Schlaefer A, Keck T, Gessert N. Towards an Optical Biopsy during Visceral Surgical Interventions. Visc Med 2020; 36:70-79. [PMID: 32355663 DOI: 10.1159/000505938] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 01/13/2020] [Indexed: 12/24/2022] Open
Abstract
Background Cancer will replace cardiovascular diseases as the most frequent cause of death. Therefore, the goals of cancer treatment are prevention strategies and early detection by cancer screening and ideal stage therapy. From an oncological point of view, complete tumor resection is a significant prognostic factor. Optical coherence tomography (OCT) and confocal laser microscopy (CLM) are two techniques that have the potential to complement intraoperative frozen section analysis as in vivo and real-time optical biopsies. Summary In this review we present both procedures and review the progress of evaluation for intraoperative application in visceral surgery. For visceral surgery, there are promising studies evaluating OCT and CLM; however, application during routine visceral surgical interventions is still lacking. Key Message OCT and CLM are not competing but complementary approaches of tissue analysis to intraoperative frozen section analysis. Although intraoperative application of OCT and CLM is at an early stage, they are two promising techniques of intraoperative in vivo and real-time tissue examination. Additionally, deep learning strategies provide a significant supplement for automated tissue detection.
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Affiliation(s)
- David Benjamin Ellebrecht
- LungenClinic Grosshansdorf, Department of Thoracic Surgery, Grosshansdorf, Germany.,University Medical Center Schleswig-Holstein, Campus Lübeck, Department of Surgery, Lübeck, Germany
| | - Sarah Latus
- Hamburg University of Technology, Institute of Medical Technology, Hamburg, Germany
| | - Alexander Schlaefer
- Hamburg University of Technology, Institute of Medical Technology, Hamburg, Germany
| | - Tobias Keck
- University Medical Center Schleswig-Holstein, Campus Lübeck, Department of Surgery, Lübeck, Germany
| | - Nils Gessert
- Hamburg University of Technology, Institute of Medical Technology, Hamburg, Germany
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Phung MC, Rouse AR, Pangilinan J, Bell RC, Bracamonte ER, Mashi S, Gmitro AF, Lee BR. Investigation of confocal microscopy for differentiation of renal cell carcinoma versus benign tissue. Can an optical biopsy be performed? Asian J Urol 2019; 7:363-368. [PMID: 32995282 PMCID: PMC7498942 DOI: 10.1016/j.ajur.2019.12.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 02/12/2019] [Accepted: 07/17/2019] [Indexed: 01/20/2023] Open
Abstract
Objective Novel optical imaging modalities are under development with the goal of obtaining an “optical biopsy” to efficiently provide pathologic details. One such modality is confocal microscopy which allows in situ visualization of cells within a layer of tissue and imaging of cellular-level structures. The goal of this study is to validate the ability of confocal microscopy to quickly and accurately differentiate between normal renal tissue and cancer. Methods Specimens were obtained from patients who underwent robotic partial nephrectomy for renal mass. Samples of suspected normal and tumor tissue were extracted from the excised portion of the kidney and stained with acridine orange. The stained samples were imaged on a Nikon E600 C1 Confocal Microscope. The samples were then submitted for hematoxylin and eosin processing and read by an expert pathologist to provide a gold-standard diagnosis that can later be compared to the confocal images. Results This study included 11 patients, 17 tissue samples, and 118 confocal images. Of the 17 tissue samples, 10 had a gold-standard diagnosis of cancer and seven were benign. Of 118 confocal images, 66 had a gold-standard diagnosis of cancer and 52 were benign. Six confocal images were used as a training set to train eight observers. The observers were asked to rate the test images on a six point scale and the results were analyzed using a web based receiver operating characteristic curve calculator. The average accuracy, sensitivity, specificity, and area under the empirical receiver operating characteristic curve for this study were 91%, 98%, 81%, and 0.94 respectively. Conclusion This preliminary study suggest that confocal microscopy can be used to distinguish cancer from normal tissue with high sensitivity and specificity. The observers in this study were trained quickly and on only six images. We expect even higher performance as observers become more familiar with the confocal images.
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Affiliation(s)
- Michael C Phung
- Department of Urology, University of Arizona College of Medicine, Arizona, USA
| | - Andrew R Rouse
- Department of Medical Imaging, University of Arizona College of Medicine, Arizona, USA
| | - Jayce Pangilinan
- Department of Pathology, University of Arizona College of Medicine, Arizona, USA
| | - Robert C Bell
- Department of Pathology, University of Arizona College of Medicine, Arizona, USA
| | - Erika R Bracamonte
- Department of Pathology, University of Arizona College of Medicine, Arizona, USA
| | - Sharfuddeen Mashi
- Ringgold Standard Institution, Aminu Kano Teaching Hospital, Kano, Nigeria
| | - Arthur F Gmitro
- Biomedical Engineering, University of Arizona College of Medicine, Arizona, USA
| | - Benjamin R Lee
- Department of Urology, University of Arizona College of Medicine, Arizona, USA
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Shkolyar E, Laurie MA, Mach KE, Trivedi DR, Zlatev DV, Chang TC, Metzner TJ, Leppert JT, Kao CS, Liao JC. Optical biopsy of penile cancer with in vivo confocal laser endomicroscopy. Urol Oncol 2019; 37:809.e1-809.e8. [DOI: 10.1016/j.urolonc.2019.08.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 07/19/2019] [Accepted: 08/20/2019] [Indexed: 12/16/2022]
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Orth A, Ploschner M, Wilson ER, Maksymov IS, Gibson BC. Optical fiber bundles: Ultra-slim light field imaging probes. SCIENCE ADVANCES 2019; 5:eaav1555. [PMID: 31032405 PMCID: PMC6486219 DOI: 10.1126/sciadv.aav1555] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Accepted: 03/06/2019] [Indexed: 05/02/2023]
Abstract
Optical fiber bundle microendoscopes are widely used for visualizing hard-to-reach areas of the human body. These ultrathin devices often forgo tunable focusing optics because of size constraints and are therefore limited to two-dimensional (2D) imaging modalities. Ideally, microendoscopes would record 3D information for accurate clinical and biological interpretation, without bulky optomechanical parts. Here, we demonstrate that the optical fiber bundles commonly used in microendoscopy are inherently sensitive to depth information. We use the mode structure within fiber bundle cores to extract the spatio-angular description of captured light rays-the light field-enabling digital refocusing, stereo visualization, and surface and depth mapping of microscopic scenes at the distal fiber tip. Our work opens a route for minimally invasive clinical microendoscopy using standard bare fiber bundle probes. Unlike coherent 3D multimode fiber imaging techniques, our incoherent approach is single shot and resilient to fiber bending, making it attractive for clinical adoption.
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Affiliation(s)
- A. Orth
- ARC Centre of Excellence for Nanoscale BioPhotonics, School of Science, RMIT University, Melbourne, VIC 3000, Australia
- Corresponding author.
| | - M. Ploschner
- ARC Centre of Excellence for Nanoscale BioPhotonics, Department of Physics and Astronomy, Macquarie University, Sydney, NSW 2109, Australia
| | - E. R. Wilson
- ARC Centre of Excellence for Nanoscale BioPhotonics, School of Science, RMIT University, Melbourne, VIC 3000, Australia
| | - I. S. Maksymov
- ARC Centre of Excellence for Nanoscale BioPhotonics, School of Science, RMIT University, Melbourne, VIC 3000, Australia
- Centre for Micro-Photonics, Swinburne University of Technology, Hawthorn, VIC 3122, Australia
| | - B. C. Gibson
- ARC Centre of Excellence for Nanoscale BioPhotonics, School of Science, RMIT University, Melbourne, VIC 3000, Australia
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Wang M, Tulman DB, Sholl AB, Mandava SH, Maddox MM, Lee BR, Brown JQ. Partial nephrectomy margin imaging using structured illumination microscopy. JOURNAL OF BIOPHOTONICS 2018; 11:10.1002/jbio.201600328. [PMID: 28834287 PMCID: PMC5821599 DOI: 10.1002/jbio.201600328] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2016] [Revised: 05/19/2017] [Accepted: 08/17/2017] [Indexed: 06/07/2023]
Abstract
Partial nephrectomy (PN) is the recommended procedure over radical nephrectomy (RN) for patients with renal masses less than 4 cm in diameter (Stage T1a). Patients with less than 4 cm renal masses can also be treated with PN, but have a higher risk for positive surgical margins (PSM). PSM, when present, are indicative of poor clinical outcomes. The current gold-standard histopathology method is not well-suited for the identification of PSM intraoperatively due to processing time and destructive nature. Here, video-rate structured illumination microscopy (VR-SIM) was investigated as a potential tool for PSM detection during PN. A clinical image atlas assembled from ex vivo renal biopsies provided diagnostically useful images of benign and malignant kidney, similar to permanent histopathology. VR-SIM was then used to image entire parenchymal margins of tumor resection covering up to >1800× more margin surface area than standard histology. Aided by the image atlas, the study pathologist correctly classified all parenchymal margins as negative for PSM with VR-SIM, compared to standard postoperative pathology. The ability to evaluate large surgical margins in a short time frame with VR-SIM may allow it to be used intraoperatively as a "safety net" for PSM detection, allowing more patients to undergo PN over RN.
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Affiliation(s)
- Mei Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA 70118
| | - David B. Tulman
- Bioinnovation Program, Tulane University, New Orleans, LA 70118
| | - Andrew B. Sholl
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, New Orleans, LA 70112
| | - Sree H. Mandava
- Department of Urology, Tulane University School of Medicine, New Orleans, LA 70112
| | - Michael M. Maddox
- Department of Urology, Tulane University School of Medicine, New Orleans, LA 70112
| | - Benjamin R. Lee
- Division of Urology, University of Arizona College of Medicine, Tucson, AZ 85724
| | - J. Quincy Brown
- Department of Biomedical Engineering, Tulane University, New Orleans, LA 70118
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An In-vivo Prospective Study of the Diagnostic Yield and Accuracy of Optical Biopsy Compared with Conventional Renal Mass Biopsy for the Diagnosis of Renal Cell Carcinoma: The Interim Analysis. Eur Urol Focus 2017; 4:978-985. [PMID: 29079496 DOI: 10.1016/j.euf.2017.10.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Revised: 09/07/2017] [Accepted: 10/06/2017] [Indexed: 11/22/2022]
Abstract
BACKGROUND Lack of accuracy in preoperative imaging leads to overtreatment of benign renal masses (RMs) or indolent renal cell carcinomas (RCCs). Optical coherence tomography (OCT) is real time and high resolution, enabling quantitative analysis through attenuation coefficient (μOCT, mm-1). OBJECTIVE To determine the accuracy and diagnostic yield of OCT and renal mass biopsy (RMB) for the differentiation of benign RMs versus RCC and oncocytoma versus RCC. DESIGN, SETTING, AND PARTICIPANTS From October 2013 to June 2016, 95 patients with solid enhancing RMs on cross-sectional imaging were prospectively included. All patients underwent subsequent excision or ablation. INTERVENTION Percutaneous, image-guided, needle-based OCT followed by RMB in an outpatient setting under local anaesthesia. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Accuracy and diagnostic yield, μOCT correlated to resection pathology or second biopsy during ablation. Tables (2×2) for RMB, receiver operating characteristic curve for OCT. Mann-Whitney test to differentiate μOCT of RMs. RESULTS AND LIMITATIONS RMB diagnostic yield was 79% with sensitivity, specificity, positive predictive value, and negative predictive value (NPV) of 100%, 89%, 99%, and 100%, respectively. Diagnostic yield and added value of OCT to differentiate RCC from benign was 99% and 15%, respectively. Significant difference was observed in median μOCT between benign RMs (3.2mm-1, interquartile range [IQR]: 2.65-4.35) and RCCs (4.3mm-1, IQR: 3.70-5.00), p=0.0171, and oncocytomas (3.38mm-1, IQR: 2.68-3.95) and RCCs (4.3mm-1, IQR: 3.70-5.00), p=0.0031. OCT showed sensitivity, specificity, positive predictive value. and NPV of 91%, 56%, 91%, and 56%, respectively, to differentiate benign RMs from RCCs and 92%, 67%, 95%, and 55%, respectively, to differentiate oncocytoma from RCC. Limitations include two reference standards and heterogeneity benign RMs. CONCLUSIONS Compared with RMB, OCT has a higher diagnostic yield. OCT accurately distinguishes benign RMs from RCCs, and oncocytoma from RCCs, although specificity and NPV are lower. PATIENT SUMMARY Optical coherence tomography, a new optical scan, exhibits similar sensitivity and positive predictive value than renal mass biopsy, although lower specificity and negative predictive value. Optical coherence tomography has a higher diagnostic yield for diagnosing renal cell carcinoma.
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Abstract
Renal masses are diagnosed with an increasing frequency. However, a significant proportion of these masses are benign, and the majority of malignant tumors are biologically indolent. Furthermore, renal tumors are often harbored by the elderly and comorbid patients. As such, matching of renal tumor biology to appropriate treatment intensity is an urgent clinical need. Renal mass biopsy is currently a very useful clinical tool that can assist with critical clinical decision-making in patients with renal mass. Yet, renal mass biopsy is associated with limitations and, as such, may not be appropriate for all patients.
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Liao JC. Editorial Comment. J Urol 2016; 195:1585. [DOI: 10.1016/j.juro.2015.12.114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- Joseph C. Liao
- Department of Urology, Stanford University School of Medicine, Stanford, California
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