scholarly journals Replacement and desmoplastic histopathological growth patterns: A pilot study of prediction of outcome in patients with uveal melanoma liver metastases

2018 ◽  
Vol 4 (4) ◽  
pp. 227-240 ◽  
Author(s):  
Raymond Barnhill ◽  
Peter Vermeulen ◽  
Sofie Daelemans ◽  
Pieter-Jan van Dam ◽  
Sergio Roman-Roman ◽  
...  
Keyword(s):  
Pilot Study ◽  
Liver Metastases ◽  
Uveal Melanoma ◽  
Growth Patterns ◽  
Prediction Of Outcome ◽  
Histopathological Growth Patterns

scholarly journals Histopathological growth patterns as biomarker for adjuvant systemic chemotherapy in patients with resected colorectal liver metastases

2020 ◽  
Vol 37 (5) ◽  
pp. 593-605
Author(s):  
Florian E. Buisman ◽  
Eric P. van der Stok ◽  
Boris Galjart ◽  
Peter B. Vermeulen ◽  
Vinod P. Balachandran ◽  
...  
Keyword(s):  
New York ◽  
Liver Metastases ◽  
Preoperative Chemotherapy ◽  
Colorectal Liver Metastases ◽  
Systemic Chemotherapy ◽  
Disease Free Survival ◽  
Growth Patterns ◽  
Cancer Center ◽  
Pretreated Patients ◽  
Histopathological Growth Patterns

Abstract Adjuvant systemic chemotherapy (CTx) is widely administered in patients with colorectal liver metastases (CRLM). Histopathological growth patterns (HGPs) are an independent prognostic factor for survival after complete resection. This study evaluates whether HGPs can predict the effectiveness of adjuvant CTx in patients with resected CRLM. Two main types of HGPs can be distinguished; the desmoplastic type and the non-desmoplastic type. Uni- and multivariable analyses for overall survival (OS) and disease-free survival (DFS) were performed, in both patients treated with and without preoperative chemotherapy. A total of 1236 patients from two tertiary centers (Memorial Sloan Kettering Cancer Center, New York, USA; Erasmus MC Cancer Institute, Rotterdam, The Netherlands) were included (period 2000–2016). A total of 656 patients (53.1%) patients received preoperative chemotherapy. Adjuvant CTx was only associated with a superior OS in non-desmoplastic patients that had not been pretreated (adjusted hazard ratio (HR) 0.52, 95% confidence interval (CI) 0.37–0.73, p < 0.001), and not in desmoplastic patients (adjusted HR 1.78, 95% CI 0.75–4.21, p = 0.19). In pretreated patients no significant effect of adjuvant CTx was observed, neither in the desmoplastic group (adjusted HR 0.83, 95% CI 0.49–1.42, p = 0.50) nor in the non-desmoplastic group (adjusted HR 0.96, 95% CI 0.71–1.29, p = 0.79). Similar results were found for DFS, with a superior DFS in non-desmoplastic patients treated with adjuvant CTx (HR 0.71, 95% CI 0.55–0.93, p < 0.001) that were not pretreated. Adjuvant CTx seems to improve OS and DFS after resection of non-desmoplastic CRLM. However, this effect was only observed in patients that were not treated with chemotherapy.

scholarly journals Distinguishing pure histopathological growth patterns of colorectal liver metastases on CT using deep learning and radiomics: a pilot study

2021 ◽  
Vol 38 (5) ◽  
pp. 483-494
Author(s):  
Martijn P. A. Starmans ◽  
Florian E. Buisman ◽  
Michel Renckens ◽  
François E. J. A. Willemssen ◽  
Sebastian R. van der Voort ◽  
...  
Keyword(s):  
Liver Metastases ◽  
Colorectal Liver Metastases ◽  
Cross Validation ◽  
Area Under The Curve ◽  
Growth Patterns ◽  
Learning Approaches ◽  
Intra Class Correlation ◽  
Preoperative Prediction ◽  
Intra Class Correlation Coefficient ◽  
Histopathological Growth Patterns

AbstractHistopathological growth patterns (HGPs) are independent prognosticators for colorectal liver metastases (CRLM). Currently, HGPs are determined postoperatively. In this study, we evaluated radiomics for preoperative prediction of HGPs on computed tomography (CT), and its robustness to segmentation and acquisition variations. Patients with pure HGPs [i.e. 100% desmoplastic (dHGP) or 100% replacement (rHGP)] and a CT-scan who were surgically treated at the Erasmus MC between 2003–2015 were included retrospectively. Each lesion was segmented by three clinicians and a convolutional neural network (CNN). A prediction model was created using 564 radiomics features and a combination of machine learning approaches by training on the clinician’s and testing on the unseen CNN segmentations. The intra-class correlation coefficient (ICC) was used to select features robust to segmentation variations; ComBat was used to harmonize for acquisition variations. Evaluation was performed through a 100 × random-split cross-validation. The study included 93 CRLM in 76 patients (48% dHGP; 52% rHGP). Despite substantial differences between the segmentations of the three clinicians and the CNN, the radiomics model had a mean area under the curve of 0.69. ICC-based feature selection or ComBat yielded no improvement. Concluding, the combination of a CNN for segmentation and radiomics for classification has potential for automatically distinguishing dHGPs from rHGP, and is robust to segmentation and acquisition variations. Pending further optimization, including extension to mixed HGPs, our model may serve as a preoperative addition to postoperative HGP assessment, enabling further exploitation of HGPs as a biomarker.

scholarly journals Histopathological growth patterns and positive margins after resection of colorectal liver metastases

HPB ◽  
2018 ◽  
Vol 20 ◽  
pp. S223-S224 ◽  
Author(s):  
P.M.H. Nierop ◽  
E.P. van der Stok ◽  
B. Groot Koerkamp ◽  
P.J. Allen ◽  
W.R. Jarnagin ◽  
...  
Keyword(s):  
Liver Metastases ◽  
Colorectal Liver Metastases ◽  
Growth Patterns ◽  
Positive Margins ◽  
Histopathological Growth Patterns

scholarly journals Salvage treatment for recurrences after first resection of colorectal liver metastases: the impact of histopathological growth patterns

2019 ◽  
Vol 36 (2) ◽  
pp. 109-118 ◽  
Author(s):  
Pieter M. H. Nierop ◽  
Boris Galjart ◽  
Diederik J. Höppener ◽  
Eric P. van der Stok ◽  
Robert R. J. Coebergh van den Braak ◽  
...  
Keyword(s):  
Liver Metastases ◽  
Colorectal Liver Metastases ◽  
Salvage Treatment ◽  
Growth Patterns ◽  
The Impact ◽  
Histopathological Growth Patterns

scholarly journals Histopathological growth patterns and positive margins after resection of colorectal liver metastases

HPB ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 911-919 ◽  
Author(s):  
Pieter M.H. Nierop ◽  
Diederik J. Höppener ◽  
Eric P. van der Stok ◽  
Boris Galjart ◽  
Florian E. Buisman ◽  
...  
Keyword(s):  
Liver Metastases ◽  
Colorectal Liver Metastases ◽  
Growth Patterns ◽  
Positive Margins ◽  
Histopathological Growth Patterns

scholarly journals Differentiation of histopathological growth patterns of colorectal liver metastases by MRI features

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Wen-Hui Li ◽  
Shuai Wang ◽  
Yi Liu ◽  
Xin-Fang Wang ◽  
Yong-Feng Wang ◽  
...  
Keyword(s):  
Liver Metastases ◽  
Colorectal Liver Metastases ◽  
Growth Patterns ◽  
Mri Features ◽  
Histopathological Growth Patterns
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