Sapienza, University of Rome Department of Surgical and Medical Sciences and Translational Medicine
Sapienza, University of Rome
Department of Surgical and Medical Sciences and Translational Medicine

Author of 3 Presentations

SS 2.4 - Low-volume reduced bowel preparation for CTC: a randomised controlled trial

Presentation Number
SS 2.4
Channel
On-demand channel 6

Abstract

Purpose

To investigate the feasibility and patient tolerance of a reduced bowel preparation for CTC.

Material and methods

Asymptomatic and symptomatic patients were enrolled in this multicentric randomised trial. All patients were randomly assigned (1:1 ratio, blocks of ten) to receive a reduced (52.5 g of Macrogol dissolved in 500 mL of water, RBP) or full (105 g of Macrogol in 1000 mL, FBP) bowel preparation and faecal tagging. Five readers performed a blinded subjective image analysis, by means of four-point Likert scales from 0 (highest score) to 3 (worst score). Endpoints were the quality of large bowel cleansing and tolerance to the assigned bowel preparation regimen.

Results

Seventy-eight patients were randomly allocated to treatments (44 in FBP group, 34 in RBP group). Both groups resulted in optimal colon cleansing. Homogeneity of fluid tagging (median score 0 vs 0, p=0.075), volume of residual stools (median score 0 vs 0, p=0.082), and colonic distension (median score 0 vs 0, p=0.073) were similar for both groups. RBP resulted in better patient tolerance.

Conclusion

Reduced bowel preparation may provide better tolerance for patients undergoing CTC without affecting colon cleansing and image quality.

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SS 2.8 - Prediction value of CT texture analysis to differentiate V-Ki-ras-2 Kirsten rat sarcoma viral oncogene homolog mutation status in colorectal cancer

Presentation Number
SS 2.8
Channel
On-demand channel 6

Abstract

Purpose

To investigate the value of CT texture analysis in the prediction of V-Ki-ras-2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation status in patients with lung metastases from colorectal cancer.

Material and methods

Eighteen patients with pathologically proven lung metastases from colorectal cancer were retrospectively enrolled. All patients underwent contrast-enhanced CT before the resection of metastases and KRAS mutation testing was performed on surgical specimen. Each metastasis was manually segmented from portal venous-phase CT images by an expert radiologist and analyzed with a dedicated software (TexRAD Ltd, Somerset, UK), which extrapolated the following texture parameters: mean, standard deviation of the pixel histogram (SD), skewness, kurtosis, mean value of positive pixel (MPP) and entropy. Mean value of texture parameters was calculated for each spatial spacing factor (SSF 0-6) and compared with KRAS mutation status. P values <0.05 were considered statistically significant.

Results

Nine patients (50%) had mutant KRAS and nine patients (50%) had wild-type KRAS. SD, entropy, MPP and kurtosis resulted significantly different (SD: p = 0.0016; entropy: p = 0.042; MPP, p = 0.0025; kurtosis, p = 0.05) between mutant and wild-type patients at medium and high filter levels (SSF 4-6). Mean and skewness showed no significant differences between the two groups of patients.

Conclusion

Texture parameters are significantly different between mutant and wild-type patients; texture analysis, providing a quantitative assessment of tumor microenvironment, may represent a non-invasive tool in the early prediction of KRAS mutation status in patients with metastatic colorectal cancer, allowing to customize treatment according to the predicted outcome.

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SS 5.9 - Influence of different adaptive statistical iterative reconstruction levels on CT radiomic features

Presentation Number
SS 5.9
Channel
On-demand channel 4

Abstract

Purpose

To evaluate the influence of different levels of adaptive statistical iterative reconstruction (ASIR) on CT radiomic features.

Material and methods

38 patients who underwent unenhanced CT scans of the abdomen with the same scanner (Revolution Evo, GE Healthcare, USA) were analyzed. Subsequently, raw data of filtered backprojection (FBP) were reconstructed with 10 levels of ASIR (from 10 to 100). Two radiologists analyzed texture features of liver and kidney tissues using two different regions of interest (ROIs) that were cloned for all eleven different iteration level datasets. Data were elaborated with TexRad Medical Imaging Software. Six different radiomic features (mean, sd, entropy, mpp, skewness, kurtosis) were extrapolated and compared between FBP and all ASIR levels.

Results

Texture analysis of the liver revealed significant differences between FBP and all ASIR reconstructions for mean (all p<0.002), sd (all p<0.0001), entropy (all p<0.0001) and mpp (all p<0.0001), while no significant differences were observed for skewness and kurtosis between FBP and all ASIR reconstructions (all p>0.45 and all p>0.58, respectively). Similar results were obtained for kidney analysis with no significant differences for skewness and kurtosis (all p>0.053 and all p>0.176, respectively) and significant changes for mean (all p<0.0001), sd (all p<0.0001), entropy (all p<0.0036) and mpp (all p<0.0001).

Conclusion

No influence of iterative reconstruction algorithm was reported for skewness and kurtosis compared to FBP in liver and kidney analysis whereas mean, sd, entropy and mpp were significantly affected by ASIR. Skewness and kurtosis may be reliable quantitative parameters.

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CS 1.2 - An Italian experience

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Moderator of 1 Session

School of ESGAR On-demand channel 5 Level II Miscellaneous
Moderators
Date
Thu, 21.05.2020
Time
09:00 - 10:30
Session Level
Level II
Topic
Miscellaneous

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Poster Author of 3 e-Posters

Author of 3 Presentations

AI, Machine Learning, Radiomics Poster presentation - Scientific

SE-010 - CT texture analysis of gastric cancer without synchronous peritoneal carcinomatosis (NPCGC) versus gastric cancer with synchronous peritoneal carcinomatosis (PCGC).

Abstract

Purpose

To compare CT texture analysis and CT features of gastric cancer with synchronous peritoneal carcinomatosis (PCGC) versus features of gastric cancer without synchronous peritoneal carcinomatosis (NPCGC) at the moment of diagnosis.

Material and methods

Contrast-enhanced CT images of 24 patients with gastric cancer without synchronous peritoneal carcinomatosis and 24 patients with synchronous peritoneal carcinomatosis were analysed with 3D CT texture analysis (performed by TexRAD) in portal phase. The Region of Interest (ROI) was manually drawn along the margin of the lesion for each image. The following parameters have been evaluated: "Mean Attenuation", "Standard Deviation", "Skewness", "Kurtosis", "Entropy" and "Mean of Positive Pixel". The CT exams were performed before the beginning of any medical treatment or surgery. Data were analysed with Mann-Whitney test. Radiomics results have been correlated with size, histologic specimen and oncologic grading.

Results

Concerning histologic type, all patients have been demonstrated to have a gastric adenocarcinoma. At least oncologic grade 3 was found in 31 out of 48 patients. Among CT texture analysis, in a comprehensive comparison between PCGC and NPCGC, the parameter "Mean" was significantly higher in PCGC (p value<0.05) for all the Spatial Scaling Factors (SSF). The parameter “Skewness” was significantly higher in PCGC (p value<0.05), moreover for SSF3. The parameter “Entropy” was significantly higher in PCGC (p value<0.05) for SSF0, SSF5 e SSF6.

Conclusion

The results of our study demonstrate significant differences between CT texture parameters of gastric tumoral lesions in PCGCs and NPCGCs, and highlight the diversity of the two groups, for at least three parameters.

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Liver - Focal Liver Lesions Poster presentation - Scientific

SE-080 - CT-Texture Analysis of liver metastases in PNETs versus NPNETs: correlation with histopathological findings

Abstract

Purpose

To compare CT Texture Analysis and CT features (necrosis and delta enhancement) of liver metastases in pancreatic Neuroendocrine Tumors (PNETs) and in non-pancreatic Neuroendocrine Tumors (NPNETs) according to tumor grading and risk of dying.

Material and methods

We assessed baseline CT images of 23 patients with liver metastases in PNETs and 25 patients with liver metastases in NPETs. The lesions were G1 and G2 according to WHO classification. Texture parameters (Mean, Standard Deviation, Entropy, Kurtosis, Skewness, Mean of Positive Pixel and Tx_sigma) at different spatial scale image filtration (SSF) were evaluated in CT arterial and portal phase using a dedicated software for volumetric analysis. CT images were scanned before the beginning of medical treatment.

Results

The following significant results (P< 0,05) were found: value of Skewness in arterial phase between PNETs G2 versus NPNETs G2; in portal phase between PNETs versus NPNETs, PNETs G1 versus NPNETs G1, PNETs G2 versus NPNETs G2; value of Mean in portal phase in PNETs vs NPNETs. Evaluating PNETs, P< 0,05 was found in: Kurtosis and high risk of dying; Skewness and low risk of dying. Evaluating NPNETs, P< 0,05 was found in: Entropy and high risk of dying.

Conclusion

This study shows that CT Texture features are significantly different in PNETs from NPNETs. Moreover, we highlight that some textural features have a significantly correlation with high risk of dying. The evidence of various expressions in term of textural parameters could help the physicians to plan appropriate follow-up programs, therapeutic strategies and to evaluate the response to therapy.

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Liver - Focal Liver Lesions Poster presentation - Scientific

SE-090 - CT and MR texture analyses of liver metastases from neuroendocrine tumour(NET): evaluation of the ability to predict the tumour aggressiveness based on PET evaluation (Octreo-PET and fdg-PET) and histological evaluation.

Abstract

Purpose

The aim of the study is to evaluate the capability of texture analysis(TA) metrics calculated for NET liver metastases on CT and MR in discriminating the tumour aggressiveness based on PET-evaluation and on histological tumour grade.

Material and methods

This retrospective study included patients with liver metastases from NET previously investigated with FDG-PET/CT and Octreo-PET/CT. TA metrics were obtained by drawing a ROI including all liver lesion volume using a semi-automated tool(3D slicer) on contrast-enhanced CT or on ADCmaps. Patients inclusion criteria were: 1)NET histologically proven;2) liver metastases(dimension≥2cm) assessed on contrast-enhanced CT or DWI-MR, Octreo-PET/CT and FDG-PET/CT before any treatment. Patients were divided into two groups according to the aggressiveness based on PET-CT (high aggressiveness=positivity on fdg-PET, low aggressiveness=positivity on Octreo-PET and negative on FDG-PET/CVT) and on histological grade (high aggressiveness=G3, low aggressiveness=G1-G2). Association between TA with the tumour aggressiveness measured on PET and on histological grade were assessed using a logistic regression model (software Weka).

Results

Final study population consisted of 50 patients. The CT-TA discriminates the aggressiveness based on PET-CT with a AUC=0,8 and 0,6 and on histological grade with a AUC=0,9 and 0,5 for the less aggressive and more aggressive respectively. The MR-TA discriminates the aggressiveness based on PET-CT with a AUC=0,8 and 0,5 and on histological grade with a AUC=0,8 and 0,5 for the less aggressive and more aggressive respectively.

Conclusion

TA on both CT and MR showed good accuracy to identify less aggressive compared to more aggressive tumours according to the PET- and histological evaluation.

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Presenter of 1 Presentation

CS 1.2 - An Italian experience

Presentation Number
CS 1.2
Speakers:

Author of 4 Presentations

SS 2.4 - Low-volume reduced bowel preparation for CTC: a randomised controlled trial (ID 951)

Abstract

Purpose

To investigate the feasibility and patient tolerance of a reduced bowel preparation for CTC.

Material and methods

Asymptomatic and symptomatic patients were enrolled in this multicentric randomised trial. All patients were randomly assigned (1:1 ratio, blocks of ten) to receive a reduced (52.5 g of Macrogol dissolved in 500 mL of water, RBP) or full (105 g of Macrogol in 1000 mL, FBP) bowel preparation and faecal tagging. Five readers performed a blinded subjective image analysis, by means of four-point Likert scales from 0 (highest score) to 3 (worst score). Endpoints were the quality of large bowel cleansing and tolerance to the assigned bowel preparation regimen.

Results

Seventy-eight patients were randomly allocated to treatments (44 in FBP group, 34 in RBP group). Both groups resulted in optimal colon cleansing. Homogeneity of fluid tagging (median score 0 vs 0, p=0.075), volume of residual stools (median score 0 vs 0, p=0.082), and colonic distension (median score 0 vs 0, p=0.073) were similar for both groups. RBP resulted in better patient tolerance.

Conclusion

Reduced bowel preparation may provide better tolerance for patients undergoing CTC without affecting colon cleansing and image quality.

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Slides

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Video-on-demand

[session]
[presentation]
[presenter]
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SS 2.8 - Prediction value of CT texture analysis to differentiate V-Ki-ras-2 Kirsten rat sarcoma viral oncogene homolog mutation status in colorectal cancer (ID 992)

Abstract

Purpose

To investigate the value of CT texture analysis in the prediction of V-Ki-ras-2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation status in patients with lung metastases from colorectal cancer.

Material and methods

Eighteen patients with pathologically proven lung metastases from colorectal cancer were retrospectively enrolled. All patients underwent contrast-enhanced CT before the resection of metastases and KRAS mutation testing was performed on surgical specimen. Each metastasis was manually segmented from portal venous-phase CT images by an expert radiologist and analyzed with a dedicated software (TexRAD Ltd, Somerset, UK), which extrapolated the following texture parameters: mean, standard deviation of the pixel histogram (SD), skewness, kurtosis, mean value of positive pixel (MPP) and entropy. Mean value of texture parameters was calculated for each spatial spacing factor (SSF 0-6) and compared with KRAS mutation status. P values <0.05 were considered statistically significant.

Results

Nine patients (50%) had mutant KRAS and nine patients (50%) had wild-type KRAS. SD, entropy, MPP and kurtosis resulted significantly different (SD: p = 0.0016; entropy: p = 0.042; MPP, p = 0.0025; kurtosis, p = 0.05) between mutant and wild-type patients at medium and high filter levels (SSF 4-6). Mean and skewness showed no significant differences between the two groups of patients.

Conclusion

Texture parameters are significantly different between mutant and wild-type patients; texture analysis, providing a quantitative assessment of tumor microenvironment, may represent a non-invasive tool in the early prediction of KRAS mutation status in patients with metastatic colorectal cancer, allowing to customize treatment according to the predicted outcome.

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Video-on-demand

[session]
[presentation]
[presenter]
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SS 5.9 - Influence of different adaptive statistical iterative reconstruction levels on CT radiomic features (ID 869)

Abstract

Purpose

To evaluate the influence of different levels of adaptive statistical iterative reconstruction (ASIR) on CT radiomic features.

Material and methods

38 patients who underwent unenhanced CT scans of the abdomen with the same scanner (Revolution Evo, GE Healthcare, USA) were analyzed. Subsequently, raw data of filtered backprojection (FBP) were reconstructed with 10 levels of ASIR (from 10 to 100). Two radiologists analyzed texture features of liver and kidney tissues using two different regions of interest (ROIs) that were cloned for all eleven different iteration level datasets. Data were elaborated with TexRad Medical Imaging Software. Six different radiomic features (mean, sd, entropy, mpp, skewness, kurtosis) were extrapolated and compared between FBP and all ASIR levels.

Results

Texture analysis of the liver revealed significant differences between FBP and all ASIR reconstructions for mean (all p<0.002), sd (all p<0.0001), entropy (all p<0.0001) and mpp (all p<0.0001), while no significant differences were observed for skewness and kurtosis between FBP and all ASIR reconstructions (all p>0.45 and all p>0.58, respectively). Similar results were obtained for kidney analysis with no significant differences for skewness and kurtosis (all p>0.053 and all p>0.176, respectively) and significant changes for mean (all p<0.0001), sd (all p<0.0001), entropy (all p<0.0036) and mpp (all p<0.0001).

Conclusion

No influence of iterative reconstruction algorithm was reported for skewness and kurtosis compared to FBP in liver and kidney analysis whereas mean, sd, entropy and mpp were significantly affected by ASIR. Skewness and kurtosis may be reliable quantitative parameters.

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Slides

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[session]
[presentation]
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SS 13.8 - Prediction of response to trans-arterial chemoembolisation in HCC using a model based on pretreatment CT texture features (ID 441)

Abstract

Purpose

To determine whether texture features on pretreatment contrast material-enhanced CT images can predict treatment response to trans-arterial chemoembolization (TACE) in patients with HCC.

Material and methods

97 patients with HCC treated with TACE, between September 2012 and August 2018, were retrospectively evaluated. Inclusion criteria for this study were available pretreatment laboratory exams and clinical data, pre-treatment CT performed in our hospital, absence of portal vein thrombosis and available post-treatment CT at 1-6 months from the procedure with no other pharmacological or interventional intercorring treatments. 41 pts met the inclusion criteria and were enrolled in the study. CT texture analysis was performed on pretreatment portal venous images and CT texture first-level features at different anatomic scales, ranging from fine to coarse texture, were analyzed. Post-treatment CT images were evaluated using modified RECIST criteria. A univariate analysis was performed via an appropriate test (Chi2, Mann-Whitney U, two-tailed paired T test) to identify those variables which differed significantly (p<0.05) in the two populations of complete responders and partial/non-responders. Optimal cut-off values were defined using ROC curves. Statistical analysis was performed with SPSS 24.

Results

Standard deviation, entropy, mpp, skewness and kurtosis variables resulted statistically significant between the two groups. A prediction model for complete response, using multivariate logistic regression with forward stepwise selection, was efficiently developed (AUC=0.702; p<0.001).

Conclusion

Pretreatment CT texture analysis features alone can help to predict complete responders from partial/non-responder patients to TACE treatment for HCC.

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Moderator of 1 Session

On-demand channel 5 School of ESGAR Level II Miscellaneous
Session Type
School of ESGAR
Date
Thu, 21.05.2020
Time
09:00 - 10:30
Session Level
Level II
Topic
Miscellaneous
On Demand Session
Yes