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Mohamed KS, Desai K, El-Habashy D, Liu S. Pathological Extramural Venous Invasion in High-stage Urothelial Carcinoma of the Bladder has Shorter Locoregional Recurrence-free Survival. Int J Surg Pathol 2024:10668969241253209. [PMID: 38803228 DOI: 10.1177/10668969241253209] [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: 05/29/2024]
Abstract
Extramural venous invasion is an independent prognostic factor in colorectal cancers; the pathological identification of extramural venous invasion in bladder cancer remains unclear. By focusing on high-stage urothelial carcinoma of the bladder, we provide insights into the pathological identification of extramural venous invasion in this particular clinical context. Clinical and demographic details and pathological reports were extracted from electronic medical records. Histological sections were reviewed for the pathological identification of extramural venous invasion. Statistical analysis was done using SPSS version 23 software. Survival analysis was done using Kaplan-Meier method. In patients with available follow-up data, 62% (n = 21) exhibited pathologically evidenced extramural venous invasion, whereas 38% (n = 13) did not. The extramural venous invasion positive group showed trends toward more advanced and pathological staging and a higher occurrence of extra-nodal extension. Positive margins were more frequent in the extramural venous invasion positive group (33%) compared to the extramural venous invasion negative group (8%). However, these differences were not statistically significant. Notably, all instances of recurrence were in the extramural venous invasion positive group of patients. The extramural venous invasion positive group of patients showed a significantly shorter locoregional recurrence-free survival (P-value of 0.045). However, extramural venous invasion did not emerge as a significant factor in univariate analyses for recurrence-free survival. These findings highlight the potential role of extramural venous invasion as a prognostic factor in bladder cancer but underscore the need for further research with larger cohorts to confirm its significance.
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Affiliation(s)
- Khaled S Mohamed
- Department of Pathology, University of Florida College of Medicine- Jacksonville, Jacksonville, FL, USA
| | - Ketav Desai
- Department of Pathology, University of Florida College of Medicine- Jacksonville, Jacksonville, FL, USA
| | - Dina El-Habashy
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Shiguang Liu
- Department of Pathology, University of Florida College of Medicine- Jacksonville, Jacksonville, FL, USA
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Wang Z, He W, Ying Y, Wang M, Chen Q, Zhang Z, Zeng S, Xu C. Patients With Muscle-Invasive Bladder Cancer With Lymphovascular Invasion in Transurethral Resection Specimen Benefits Most From Platinum-Based Neoadjuvant Chemotherapy. Clin Genitourin Cancer 2024; 22:201-209.e7. [PMID: 37989709 DOI: 10.1016/j.clgc.2023.10.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 10/23/2023] [Accepted: 10/29/2023] [Indexed: 11/23/2023]
Abstract
PURPOSE The survival benefit of neoadjuvant chemotherapy (NAC) before definitive radical cystectomy (RC) varied among patients, suggesting proper selection of patients for NAC to maximize the survival benefit. This study aimed to investigate the role of lymphovascular invasion (LVI) in transurethral resection (TUR) specimens in selecting patients with MIBC for NAC. METHODS Two retrospective cohorts of patients with cT2-4aN0 MIBC who underwent RC from 2004 to 2015 provided by Lund University were included. Inverse probability weighting was applied to make the NAC-treated (NAC) and untreated (non-NAC) cohorts comparable. Survival benefits were estimated with Kaplan-Meier curves and Cox proportional hazards models. The primary endpoint was cancer-specific survival (CSS). LVI in TUR specimens and molecular taxonomies (BASE47, UNC, and LundTax) were examined, and bulk RNA-seq datasets were explored for LVI-relevant signatures. RESULTS A total of 341 patients with cT2-4aN0 MIBC were included. The NAC cohort included 125 patients, whereas the non-NAC cohort included 216 patients. The 3-year CSS benefit of NAC was 7.1%. For patients with positive LVI in TUR specimens, the 3-year CSS benefit of NAC was 26.2% (48.1% vs. 74.3%), with a risk reduction of 56% (HR = 0.44, P = .03). A sensitivity analysis confirmed a significant interaction between LVI and NAC. This study failed to identify the molecular subtypes that maximized the survival benefit of NAC. Exploration of LVI-relevant signatures remains inconclusive. CONCLUSIONS LVI in TUR specimens could help identify patients with MIBC who would derive maximal survival benefit from NAC. Further prospective validation is necessary.
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Affiliation(s)
- Ziwei Wang
- Department of Urology, Changhai Hospital, Shanghai, China
| | - Wei He
- Department of Clinical Medicine, Naval Medical University, Shanghai, China
| | - Yidie Ying
- Department of Urology, Changhai Hospital, Shanghai, China
| | - Maoyu Wang
- Department of Urology, Changhai Hospital, Shanghai, China
| | - Qing Chen
- Department of Urology, Changhai Hospital, Shanghai, China
| | | | - Shuxiong Zeng
- Department of Urology, Changhai Hospital, Shanghai, China.
| | - Chuanliang Xu
- Department of Urology, Changhai Hospital, Shanghai, China.
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Ceachi B, Cioplea M, Mustatea P, Gerald Dcruz J, Zurac S, Cauni V, Popp C, Mogodici C, Sticlaru L, Cioroianu A, Busca M, Stefan O, Tudor I, Dumitru C, Vilaia A, Oprisan A, Bastian A, Nichita L. A New Method of Artificial-Intelligence-Based Automatic Identification of Lymphovascular Invasion in Urothelial Carcinomas. Diagnostics (Basel) 2024; 14:432. [PMID: 38396472 PMCID: PMC10888137 DOI: 10.3390/diagnostics14040432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 02/07/2024] [Accepted: 02/14/2024] [Indexed: 02/25/2024] Open
Abstract
The presence of lymphovascular invasion (LVI) in urothelial carcinoma (UC) is a poor prognostic finding. This is difficult to identify on routine hematoxylin-eosin (H&E)-stained slides, but considering the costs and time required for examination, immunohistochemical stains for the endothelium are not the recommended diagnostic protocol. We developed an AI-based automated method for LVI identification on H&E-stained slides. We selected two separate groups of UC patients with transurethral resection specimens. Group A had 105 patients (100 with UC; 5 with cystitis); group B had 55 patients (all with high-grade UC; D2-40 and CD34 immunohistochemical stains performed on each block). All the group A slides and 52 H&E cases from group B showing LVI using immunohistochemistry were scanned using an Aperio GT450 automatic scanner. We performed a pixel-per-pixel semantic segmentation of selected areas, and we trained InternImage to identify several classes. The DiceCoefficient and Intersection-over-Union scores for LVI detection using our method were 0.77 and 0.52, respectively. The pathologists' H&E-based evaluation in group B revealed 89.65% specificity, 42.30% sensitivity, 67.27% accuracy, and an F1 score of 0.55, which is much lower than the algorithm's DCC of 0.77. Our model outlines LVI on H&E-stained-slides more effectively than human examiners; thus, it proves a valuable tool for pathologists.
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Affiliation(s)
- Bogdan Ceachi
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
- Faculty of Automatic Control and Computer Science, National University of Science and Technology Politehnica Bucharest, 313 Splaiul Independenţei, Sector 6, 060042 Bucharest, Romania
| | - Mirela Cioplea
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
| | - Petronel Mustatea
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
- Department of Surgery, University of Medicine and Pharmacy Carol Davila, 37 Dionisie Lupu Str., Sector 1, 020021 Bucharest, Romania
| | - Julian Gerald Dcruz
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
| | - Sabina Zurac
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
- Department of Pathology, University of Medicine and Pharmacy Carol Davila, 37 Dionisie Lupu Str., Sector 1, 020021 Bucharest, Romania;
| | - Victor Cauni
- Department of Urology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania
| | - Cristiana Popp
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
| | - Cristian Mogodici
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
| | - Liana Sticlaru
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
| | - Alexandra Cioroianu
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
- Department of Pathology, University of Medicine and Pharmacy Carol Davila, 37 Dionisie Lupu Str., Sector 1, 020021 Bucharest, Romania;
| | - Mihai Busca
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
| | - Oana Stefan
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
| | - Irina Tudor
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
| | - Carmen Dumitru
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
| | - Alexandra Vilaia
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
- Department of Pathology, University of Medicine and Pharmacy Carol Davila, 37 Dionisie Lupu Str., Sector 1, 020021 Bucharest, Romania;
| | - Alexandra Oprisan
- Department of Pathology, University of Medicine and Pharmacy Carol Davila, 37 Dionisie Lupu Str., Sector 1, 020021 Bucharest, Romania;
- Department of Neurology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania
| | - Alexandra Bastian
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
- Department of Pathology, University of Medicine and Pharmacy Carol Davila, 37 Dionisie Lupu Str., Sector 1, 020021 Bucharest, Romania;
| | - Luciana Nichita
- Department of Pathology, Colentina University Hospital, 21 Stefan Cel Mare Str., Sector 2, 020125 Bucharest, Romania; (B.C.); (M.C.); (C.P.); (C.M.); (L.S.); (A.C.); (M.B.); (O.S.); (I.T.); (C.D.); (A.V.); (A.B.); (L.N.)
- Zaya Artificial Intelligence, 9A Stefan Cel Mare Str., Voluntari, 077190 Ilfov, Romania; (P.M.); (J.G.D.)
- Department of Pathology, University of Medicine and Pharmacy Carol Davila, 37 Dionisie Lupu Str., Sector 1, 020021 Bucharest, Romania;
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Liu L, Lin H, Shen G, Liu Y, Qin X, Yuan Y, Wang B, Xue L. Prognostic significance of lymphovascular invasion in patients with pT1b esophageal squamous cell carcinoma. BMC Cancer 2023; 23:370. [PMID: 37087442 PMCID: PMC10122816 DOI: 10.1186/s12885-023-10858-7] [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: 10/26/2022] [Accepted: 04/18/2023] [Indexed: 04/24/2023] Open
Abstract
BACKGROUND Lymphovascular invasion (LVI) is a crucial predictor of lymph node metastasis (LNM). However, few studies have investigated the LVI positivity rate and its clinical significance in pT1b esophageal squamous cell carcinoma (ESCC) using immunohistochemistry and elastin staining. METHODS We collected data from158 patients with pT1b ESCC who had undergone radical esophagectomy. All paraffin blocks of invasive carcinoma from each patient were subjected to HE staining, elastin staining + CK (AE1/AE3) immunohistochemistry (E&IHC), and CD31/D2-40 + CK (AE1/AE3) double immunohistochemistry (D-IHC). The LVI was classified into types, i.e., vascular invasion (VI) and lymphatic vessel invasion (LI), and its location, quantity, and clinical significance were explored. RESULTS The positivity rates of VI by E&IHC (E-VI), VI by CD31D-IHC (CD31-VI), and LI by D2-40 D-IHC (D2-40-LI) were significantly higher than those obtained by HE staining (P < 0.001, respectively). CD31-VI and E-VI were independent adverse prognostic factors for recurrence-free survival (RFS), and they were significantly associated with poor distant metastasis-free survival and overall survival in pT1b ESCC. Intratumoral LVI was also crucial in pT1b ESCC, and L2 (the count of D2-40-LI was 5 or more) was the strongest predictor for LNM and RFS in pT1b ESCC. CONCLUSION E&IHC and D-IHC can dramatically improve the detection rate of LVI in pT1b ESCC, and the classification and grading of LVI can help to improve the prediction of LNM and prognosis.
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Affiliation(s)
- Linxiu Liu
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hua Lin
- Department of Medical Record, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Guihua Shen
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yong Liu
- Department of Endoscopy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiumin Qin
- Department of Endoscopy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yanling Yuan
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bingzhi Wang
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Liyan Xue
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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