Histological step sectioning of pelvic lymph nodes increases the number of identified lymph node metastases

Engvad, Birte; Poulsen, Mads Hvid; Staun, Pia W; Walter, Steen; Marcussen, Niels

doi:10.1007/s00428-013-1510-5

Cited by 18 publications

(11 citation statements)

References 28 publications

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“…Another finding from Paper II was that the additional sectioning of LNs identified micro-metastases in 1/103 patients (<1%). Our result is in agreement with other published results in this field indicating that the additional sectioning of LNs do not result in a better detection rate of additional LN metastasis and furthermore is both costly and time-consuming (189)(190)(191). A detailed guideline on how to handle the LN specimens at the pathological department is needed.…”

Section: Discussionsupporting

confidence: 83%

Staging and tumor biological mechanisms of lymph node metastasis in invasive urinary bladder cancer

Aljabery¹

2017

Linköping University Medical Dissertations

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Aim: To study the possibility of detecting lymph node metastasis in locally advanced urinary bladder cancer (UBC) treated with radical cystectomy (RC) by using preoperative positron emission tomography/computed tomography (PET/CT) and peroperative sentinel node biopsy (SNB) technique. We also investigate the clinical significance of macrophage traits expression by cancer cells, M2-macrophage infiltration (MI) in tumor stroma and the immunohistochemical expression of biomarkers in cancer cells in relation to clinico-pathologic data. Patients and Methods:We studied prospectively 122 patients with UBC, pathological stage pT1-pT4 treated with RC and pelvic lymph node dissection (PLND) during [2005][2006][2007][2008][2009][2010][2011] at the Department of Urology, Linköping University Hospital. In the first study, we compared the results of preoperative PET/CT and conventional CT with the findings of postoperative histopathological evaluation of lymph nodes (LNs). In the second study we investigated the value of SNB technique for detecting pathological LNs during RC in patients with UBC. We also examined the significance of the primary tumor location in the bladder in predicting the site of LN metastases, and the prognostic significance of lympho-vascular invasion (LVI) and lymph node metastasis density (LNMD) on survival. In the third study, we investigate the clinical significance of macrophage infiltration (MI) in tumor stroma and macrophage-traits expression by tumor cells. In the fourth study, we investigate the cell cycle suppression pro-

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Section: Discussionsupporting

confidence: 83%

Staging and tumor biological mechanisms of lymph node metastasis in invasive urinary bladder cancer

Aljabery¹

2017

Linköping University Medical Dissertations

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“…Arguably, deep histological analyses could detect the micro‐metastases missed by PET/CT. However, performing these analyses on a routine basis would greatly increase the associated costs and time needed, since histopathologic examinations of lymph nodes normally comprise only 1%–2% of the relevant lymphatic tissue (Engvad et al., 2014).…”

Section: Discussionmentioning

confidence: 99%

Artificial intelligence‐based detection of lymph node metastases by PET/CT predicts prostate cancer‐specific survival

Borrelli

Larsson

Ulén³

et al. 2020

Clin Physio Funct Imaging

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Introduction Lymph node metastases are a key prognostic factor in prostate cancer (PCa), but detecting lymph node lesions from PET/CT images is a subjective process resulting in inter‐reader variability. Artificial intelligence (AI)‐based methods can provide an objective image analysis. We aimed at developing and validating an AI‐based tool for detection of lymph node lesions. Methods A group of 399 patients with biopsy‐proven PCa who had undergone 18F‐choline PET/CT for staging prior to treatment were used to train (n = 319) and test (n = 80) the AI‐based tool. The tool consisted of convolutional neural networks using complete PET/CT scans as inputs. In the test set, the AI‐based lymph node detections were compared to those of two independent readers. The association with PCa‐specific survival was investigated. Results The AI‐based tool detected more lymph node lesions than Reader B (98 vs. 87/117; p = .045) using Reader A as reference. AI‐based tool and Reader A showed similar performance (90 vs. 87/111; p = .63) using Reader B as reference. The number of lymph node lesions detected by the AI‐based tool, PSA, and curative treatment was significantly associated with PCa‐specific survival. Conclusion This study shows the feasibility of using an AI‐based tool for automated and objective interpretation of PET/CT images that can provide assessments of lymph node lesions comparable with that of experienced readers and prognostic information in PCa patients.

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“…Interestingly, a significant proportion of participants (42%) also routinely evaluated additional H&E‐stained section(s) from each tissue block, while very few (1%) used cytokeratin immunohistochemistry. Both of these ancillary techniques can aid the detection of metastatic deposits; however, their routine use is generally not recommended due to the significant resource requirement relative to diagnostic yield …”

Section: Discussionmentioning

confidence: 99%

Handling and reporting of pelvic lymphadenectomy specimens in prostate and bladder cancer: a web‐based survey by the European Network of Uropathology

et al. 2019

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Aims: Pathological evaluation of lymphadenectomy specimens plays a pivotal role in accurate lymph node (LN) staging. Guidelines standardising the gross handling and reporting of pelvic LN dissection (PLND) in prostate (PCa) and bladder (BCa) cancer are currently lacking. This study aimed to establish current practice patterns of PLND evaluation among pathologists. Methods and results: A web-based survey was circulated to all members of the European Network of Uropathology (ENUP), comprising 29 questions focusing on the macroscopic handling, LN enumeration and reporting of PLND in PCa and BCa. Two hundred and eighty responses were received from pathologists throughout 23 countries. Only LNs palpable at grossing were submitted by 58%, while 39% routinely embedded the entire specimen. Average LN yield from PLND was ≥10 LNs in 56% and <10 LNs in 44%.Serial section(s) and immunohistochemistry were routinely performed on LN blocks by 42% and <1% of respondents, respectively. To designate a LN microscopically, 91% required a capsule/subcapsular sinus. In pN+ cases, 72% reported the size of the largest metastatic deposit and 94% reported extranodal extension. Isolated tumour cells were interpreted as pN1 by 77%. Deposits identified in fat without associated lymphoid tissue were reported as tumour deposits (pN0) by 36% and replaced LNs (pN+) by 27%. LNs identified in periprostatic fat were included in the PLND LN count by 69%. Conclusion: This study highlights variations in practice with respect to the gross sampling and microscopic evaluation of PLND in urological malignancies. A consensus protocol may provide a framework for more consistent and standardised reporting of PLND specimens.

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Histological step sectioning of pelvic lymph nodes increases the number of identified lymph node metastases

Cited by 18 publications

References 28 publications

Staging and tumor biological mechanisms of lymph node metastasis in invasive urinary bladder cancer

Staging and tumor biological mechanisms of lymph node metastasis in invasive urinary bladder cancer

Artificial intelligence‐based detection of lymph node metastases by PET/CT predicts prostate cancer‐specific survival

Handling and reporting of pelvic lymphadenectomy specimens in prostate and bladder cancer: a web‐based survey by the European Network of Uropathology

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