scholarly journals Repeatability and Reproducibility of MRI-based Radiomic Features in Rectal Cancer

2021 ◽  
Author(s):  
Robba Rai ◽  
Michael B. Barton ◽  
Phillip Chlap ◽  
Gary P. Liney ◽  
Carsten Brink ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Intraclass Correlation ◽  
Magnetic Resonance Images ◽  
Image Resolution ◽  
Imaging Biomarkers ◽  
Dice Similarity Coefficient ◽  
Imaging Features ◽  
Imaging Protocol ◽  
Repeatability And Reproducibility ◽  
The Impact

Abstract Radiomics of magnetic resonance images (MRI) in rectal cancer can non-invasively characterise tumour heterogeneity with potential to discover new imaging biomarkers. However, for radiomics to be reliable; the imaging features measured must be stable and reproducible. The aim of this study is to quantify the repeatability and reproducibility of MRI-based radiomic features in rectal cancer. An MRI radiomics phantom was used to measure the longitudinal repeatability of radiomic features and the impact of post-processing changes related to image resolution and noise. Repeatability measurements in rectal cancers were also quantified in a cohort of ten patients with test-retest imaging amongst two observers. We found that many radiomic features; particularly from texture classes, were highly sensitive to changes in image resolution and noise. 49% of features had coefficient of variations ≤ 10% in longitudinal phantom measurements. 75% of radiomic features in in vivo test-retest measurements had an intraclass correlation coefficient of ≥ 0.8. We saw excellent interobserver agreement with mean dice similarity coefficient of 0.95 ± 0.04 for test and retest scans. The results of this study show that even when using a consistent imaging protocol many radiomic features were unstable. Therefore, caution must be taken when selecting features for potential imaging biomarkers.

scholarly journals Effects of interobserver and interdisciplinary segmentation variabilities on CT-based radiomics for pancreatic cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jeffrey Wong ◽  
Michael Baine ◽  
Sarah Wisnoskie ◽  
Nathan Bennion ◽  
Dechun Zheng ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Radiation Oncology ◽  
Quantitative Imaging ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Dice Similarity Coefficient ◽  
Imaging Features ◽  
Oncology Group ◽  
Radiation Oncology Group ◽  
And Performance

AbstractRadiomics is a method to mine large numbers of quantitative imaging features and develop predictive models. It has shown exciting promise for improved cancer decision support from early detection to personalized precision treatment, and therefore offers a desirable new direction for pancreatic cancer where the mortality remains high despite the current care and intense research. For radiomics, interobserver segmentation variability and its effect on radiomic feature stability is a crucial consideration. While investigations have been reported for high-contrast cancer sites such as lung cancer, no studies to date have investigated it on CT-based radiomics for pancreatic cancer. With three radiation oncology observers and three radiology observers independently contouring on the contrast CT of 21 pancreatic cancer patients, we conducted the first interobserver segmentation variability study on CT-based radiomics for pancreatic cancer. Moreover, our novel investigation assessed whether there exists an interdisciplinary difference between the two disciplines. For each patient, a consensus tumor volume was generated using the simultaneous truth and performance level expectation algorithm, using the dice similarity coefficient (DSC) to assess each observer’s delineation against the consensus volume. Radiation oncology observers showed a higher average DSC of 0.81 ± 0.06 than the radiology observers at 0.69 ± 0.16 (p = 0.002). On a panel of 1277 radiomic features, the intraclass correlation coefficients (ICC) was calculated for all observers and those of each discipline. Large variations of ICCs were observed for different radiomic features, but ICCs were generally higher for the radiation oncology group than for the radiology group. Applying a threshold of ICC > 0.75 for considering a feature as stable, 448 features (35%) were found stable for the radiation oncology group and 214 features (16%) were stable from the radiology group. Among them, 205 features were found stable for both groups. Our results provide information for interobserver segmentation variability and its effect on CT-based radiomics for pancreatic cancer. An interesting interdisciplinary variability found in this study also introduces new considerations for the deployment of radiomics models.

scholarly journals Image Contrast, Image Pre-Processing, and T1 Mapping Affect MRI Radiomic Feature Repeatability in Patients with Colorectal Cancer Liver Metastases

Cancers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 240
Author(s):  
Damien J. McHugh ◽  
Nuria Porta ◽  
Ross A. Little ◽  
Susan Cheung ◽  
Yvonne Watson ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Liver Metastases ◽  
Intraclass Correlation ◽  
Imaging Biomarkers ◽  
Sequence Comparisons ◽  
Colorectal Cancer Liver Metastases ◽  
T1 And T2 ◽  
Non Gaussian ◽  
The Impact ◽  
T2 Weighted Images

Imaging biomarkers require technical, biological, and clinical validation to be translated into robust tools in research or clinical settings. This study contributes to the technical validation of radiomic features from magnetic resonance imaging (MRI) by evaluating the repeatability of features from four MR sequences: pre-contrast T1- and T2-weighted images, pre-contrast quantitative T1 maps (qT1), and contrast-enhanced T1-weighted images. Fifty-one patients with colorectal cancer liver metastases were scanned twice, up to 7 days apart. Repeatability was quantified using the intraclass correlation coefficient (ICC) and repeatability coefficient (RC), and the impact of non-Gaussian feature distributions and image normalisation was evaluated. Most radiomic features had non-Gaussian distributions, but Box–Cox transformations enabled ICCs and RCs to be calculated appropriately for an average of 97% of features across sequences. ICCs ranged from 0.30 to 0.99, with volume and other shape features tending to be most repeatable; volume ICC > 0.98 for all sequences. 19% of features from non-normalised images exhibited significantly different ICCs in pair-wise sequence comparisons. Normalisation tended to increase ICCs for pre-contrast T1- and T2-weighted images, and decrease ICCs for qT1 maps. RCs tended to vary more between sequences than ICCs, showing that evaluations of feature performance depend on the chosen metric. This work suggests that feature-specific repeatability, from specific combinations of MR sequence and pre-processing steps, should be evaluated to select robust radiomic features as biomarkers in specific studies. In addition, as different repeatability metrics can provide different insights into a specific feature, consideration of the appropriate metric should be taken in a study-specific context.

Standardization of hippocampus volumetry using automated brain structure volumetry tool for an initial Alzheimer’s disease imaging biomarker

2018 ◽  
Vol 60 (6) ◽  
pp. 769-776 ◽  
Author(s):  
Jill Abrigo ◽  
Lin Shi ◽  
Yishan Luo ◽  
Qianyun Chen ◽  
Winnie Chiu Wing Chu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Intraclass Correlation ◽  
Area Under The Curve ◽  
Imaging Biomarker ◽  
Imaging Biomarkers ◽  
Dice Similarity Coefficient ◽  
Reference Dataset ◽  
Magnetic Resonance Imaging Mri ◽  
Hippocampus Segmentation

Background One significant barrier to incorporate Alzheimer’s disease (AD) imaging biomarkers into diagnostic criteria is the lack of standardized methods for biomarker quantification. The European Alzheimer’s Disease Consortium-Alzheimer’s Disease Neuroimaging Initiative (EADC-ADNI) Harmonization Protocol project provides the most authoritative guideline for hippocampal definition and has produced a manually segmented reference dataset for validation of automated methods. Purpose To validate automated hippocampal volumetry using AccuBrain™, against the EADC-ADNI dataset, and assess its diagnostic performance for differentiating AD and normal aging in an independent cohort. Material and Methods The EADC-ADNI reference dataset comprise of manually segmented hippocampal labels from 135 volumetric T1-weighted scans from various scanners. Dice similarity coefficient (DSC), intraclass correlation coefficient (ICC), and Pearson’s r were obtained for AccuBrain™ and FreeSurfer. The magnetic resonance imaging (MRI) of a separate cohort of 299 individuals (150 normal controls, 149 with AD) were obtained from the ADNI database and processed with AccuBrain™ to assess its diagnostic accuracy. Area under the curve (AUC) for total hippocampal volumes (HV) and hippocampal fraction (HF) were determined. Results Compared with EADC-ADNI dataset ground truths, AccuBrain™ had a mean DSC of 0.89/0.89/0.89, ICC of 0.94/0.96/0.95, and r of 0.95/0.96/0.95 for right/left/total HV. AccuBrain™ HV and HF had AUC of 0.76 and 0.80, respectively. Thresholds of ≤ 5.71 mL and ≤ 0.38% afforded 80% sensitivity for AD detection. Conclusion AccuBrain™ provides accurate automated hippocampus segmentation in accordance with the EADC-ADNI standard, with great potential value in assisting clinical diagnosis of AD.

scholarly journals Imaging Manifestations and Evaluation of Postoperative Complications of Bone and Joint Infections under Deep Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Wei Mao ◽  
Xiantao Chen ◽  
Fengyuan Man
Keyword(s):  
Deep Learning ◽  
Postoperative Complications ◽  
Sensitivity And Specificity ◽  
Image Resolution ◽  
Dice Similarity Coefficient ◽  
Imaging Features ◽  
Imaging Methods ◽  
X Ray ◽  
Joint Infections ◽  
Bone And Joint Infections

To explore and evaluate the imaging manifestations of postoperative complications of bone and joint infections based on deep learning, a retrospective study was performed on 40 patients with bone and joint infections in the Department of Orthopedics of Orthopedics Hospital of Henan Province of Luoyang City. Sensitivity and Dice similarity coefficient (DSC) were used to evaluate the image results by convolutional neural network (CNN) algorithm. Imaging features of postoperative complications in 40 patients were analyzed. Then, three imaging methods were used to diagnose the features. Sensitivity and specificity were used to evaluate the diagnostic performance of three imaging methods for imaging features. Compared with professional doctors and biomarker algorithms, the sensitivity of CNN algorithm proposed was 90.6%, and DSC was 84.1%. Compared with traditional methods, the CNN algorithm has higher image resolution and wider and more accurate lesion area recognition and division. The three manifestations of soft tissue abscess, periosteum swelling, and bone damage were postoperative imaging features of bone and joint infections. In addition, compared with X-ray, CT examination and MRI examination were better for the examination of imaging characteristics. CT and MRI had higher sensitivity and specificity than X-ray. The experimental results show that CNN algorithm can effectively identify and divide pathological images and assist doctors to diagnose the images more efficiently in clinic.

scholarly journals Structured Reporting of Rectal Cancer Staging and Restaging: A Consensus Proposal

Cancers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 2135
Author(s):  
Vincenza Granata ◽  
Damiano Caruso ◽  
Roberto Grassi ◽  
Salvatore Cappabianca ◽  
Alfonso Reginelli ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Correlation Coefficient ◽  
Clinical Decision Making ◽  
Intraclass Correlation ◽  
Clinical Decision ◽  
Cancer Staging ◽  
Structured Reporting ◽  
Quality Analysis ◽  
Promising Tool ◽  
Structured Reports

Background: Structured reporting (SR) in oncologic imaging is becoming necessary and has recently been recognized by major scientific societies. The aim of this study was to build MRI-based structured reports for rectal cancer (RC) staging and restaging in order to provide clinicians all critical tumor information. Materials and Methods: A panel of radiologist experts in abdominal imaging, called the members of the Italian Society of Medical and Interventional Radiology, was established. The modified Delphi process was used to build the SR and to assess the level of agreement in all sections. The Cronbach’s alpha (Cα) correlation coefficient was used to assess the internal consistency of each section and to measure the quality analysis according to the average inter-item correlation. The intraclass correlation coefficient (ICC) was also evaluated. Results: After the second Delphi round of the SR RC staging, the panelists’ single scores and sum of scores were 3.8 (range 2–4) and 169, and the SR RC restaging panelists’ single scores and sum of scores were 3.7 (range 2–4) and 148, respectively. The Cα correlation coefficient was 0.79 for SR staging and 0.81 for SR restaging. The ICCs for the SR RC staging and restaging were 0.78 (p < 0.01) and 0.82 (p < 0.01), respectively. The final SR version was built and included 53 items for RC staging and 50 items for RC restaging. Conclusions: The final version of the structured reports of MRI-based RC staging and restaging should be a helpful and promising tool for clinicians in managing cancer patients properly. Structured reports collect all Patient Clinical Data, Clinical Evaluations and relevant key findings of Rectal Cancer, both in staging and restaging, and can facilitate clinical decision-making.

scholarly journals Sex disparities in vitamin D status and the impact on systemic inflammation and survival in rectal cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hanna Abrahamsson ◽  
Sebastian Meltzer ◽  
Vidar Nyløkken Hagen ◽  
Christin Johansen ◽  
Paula A. Bousquet ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Vitamin D ◽  
Cancer Patients ◽  
Systemic Inflammation ◽  
Elevated Serum ◽  
Metastatic Progression ◽  
Vitamin D Status ◽  
Cancer Specific Survival ◽  
Link Type ◽  
The Impact

Abstract Background We reported previously that rectal cancer patients given curative-intent chemotherapy, radiation, and surgery for non-metastatic disease had enhanced risk of metastatic progression and death if circulating levels of 25-hydroxyvitamin D [25(OH) D] were low. Here we investigated whether the association between the vitamin D status and prognosis pertains to the general, unselected population of rectal cancer patients. Methods Serum 25(OH) D at the time of diagnosis was assessed in 129 patients, enrolled 2013–2017 and representing the entire range of rectal cancer stages, and analyzed with respect to season, sex, systemic inflammation, and survival. Results In the population-based cohort residing at latitude 60°N, 25(OH) D varied according to season in men only, who were overrepresented among the vitamin D-deficient (< 50 nmol/L) patients. Consistent with our previous findings, the individuals presenting with T4 disease had significantly reduced 25(OH) D levels. Low vitamin D was associated with systemic inflammation, albeit with distinct modes of presentation. While men with low vitamin D showed circulating markers typical for the systemic inflammatory response (e.g., elevated erythrocyte sedimentation rate), the corresponding female patients had elevated serum levels of interleukin-6 and the chemokine (C-X-C motif) ligand 7. Despite disparities in vitamin D status and the potential effects on disease attributes, significantly shortened cancer-specific survival was observed in vitamin D-deficient patients irrespective of sex. Conclusion This unselected rectal cancer cohort confirmed the interconnection of low vitamin D, more advanced disease presentation, and poor survival, and further suggested it may be conditional on disparate modes of adverse systemic inflammation in men and women. Trial registration ClinicalTrials.govNCT01816607; registration date: 22 March 2013.

scholarly journals T stage-dependent lymph node and distant metastasis and the accuracy of lymph node assessment in rectal cancer

2021 ◽  
Author(s):  
Henry Ptok ◽  
Frank Meyer ◽  
Roland S. Croner ◽  
Ingo Gastinger ◽  
Benjamin Garlipp
Keyword(s):  
Rectal Cancer ◽  
Overall Survival ◽  
Lymph Node ◽  
Lymph Nodes ◽  
False Negative ◽  
Cumulative Risk ◽  
Distant Metastases ◽  
Number Of Patients ◽  
Tumor Stages ◽  
The Impact

Summary Objective To analyze data obtained in a representative number of patients with primary rectal cancer with respect to lymph node diagnostics and related tumor stages. Methods In pT2-, pT3-, and pT4 rectal cancer lesions, the impact of investigated lymph nodes on the frequency of pN+ status, the cumulative risk of metachronous distant metastases, and overall survival was studied by means of a prospective multicenter observational study over a defined period of time. Results From 2000 to 2011, the proportion of surgical specimens with ≥ 12 investigated lymph nodes increased significantly, from 73.6% to 93.2% (p < 0.001; the number of investigated lymph nodes from 16.2 to 20.8; p < 0.001). Despite this, the percentage of pN+ rectal cancer lesions varied only non-significantly (39.9% to 45.9%; p = 0.130; median, 44.1%). For pT2-, pT3-, and pT4 rectal cancer lesions, there was an increasing proportion of pN+ findings correlating significantly with the number of investigated lymph nodes up to n = 12 investigated lymph nodes. Only in pT3 rectal cancer was there a significant increase in pN+ findings in case of > 12 lymph nodes (p = 0.001), but not in pT2 (p = 0.655) and pT4 cancer lesions (p = 0.256). For pT3pN0cM0 rectal cancer, the risk of metachronous distant metastases and overall survival did not depend on the number of investigated lymph nodes. Conclusion In rectal cancer, at least n = 12 lymph nodes are to be minimally investigated. The investigation of fewer lymph nodes is associated with a higher risk of false-negative pN0 findings. In particular, in pT3 rectal cancer, the investigation of more than 12 lymph nodes lowers the risk of false-negative pN0 findings. An upstaging effect by the investigation of a possibly maximal number of lymph nodes could not be detected.

scholarly journals EPID-34. THE DETRIMENTAL EFFECT OF BIOPSY PRECEDING RESECTION IN SURGICALLY ACCESSIBLE GLIOBLASTOMAS: RESULTS FROM THE NATIONAL CANCER DATABASE

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii85-ii86
Author(s):  
Ping Zhu ◽  
Xianglin Du ◽  
Angel Blanco ◽  
Leomar Y Ballester ◽  
Nitin Tandon ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Failure Time ◽  
Binary Logistic Regression ◽  
Rank Test ◽  
Imaging Features ◽  
National Cancer Database ◽  
Prolonged Length ◽  
Logistic Regression Models ◽  
Operative Outcomes ◽  
The Impact

Abstract OBJECTIVES To investigate the impact of biopsy preceding resection compared to upfront resection in glioblastoma overall survival (OS) and post-operative outcomes using the National Cancer Database (NCDB). METHODS A total of 17,334 GBM patients diagnosed between 2010 and 2014 were derived from the NCDB. Patients were categorized into two groups: “upfront resection” versus “biopsy followed by resection”. Primary outcome was OS. Post-operative outcomes including 30-day readmission/mortality, 90-day mortality, and prolonged length of inpatient hospital stay (LOS) were secondary endpoints. Kaplan-Meier methods and accelerated failure time (AFT) models with gamma distribution were applied for survival analysis. Multivariable binary logistic regression models were performed to compare differences in the post-operative outcomes between these groups. RESULTS Patients undergoing “upfront resection” experienced superior survival compared to those undergoing “biopsy followed by resection” (median OS: 12.4 versus 11.1 months, log-rank test: P=0.001). In multivariable AFT models, significant survival benefits were observed among patients undergoing “upfront resection” (time ratio [TR]: 0.83, 95% CI: 0.75–0.93, P=0.001). Patients undergoing upfront GTR had the longest survival compared to upfront STR, GTR following STR, or GTR and STR following an initial biopsy (14.4 vs. 10.3, 13.5, 13.3, and 9.1, months), respectively (TR: 1.00 [Ref.], 0.75, 0.82, 0.88, and 0.67). Recent years of diagnosis, higher income and treatment at academic facilities were significantly associated with the likelihood of undergoing upfront resection after adjusting the covariates. Multivariable logistic regression revealed that 30-day mortality and 90-day mortality were decreased by 73% and 44% for patients undergoing “upfront resection” over “biopsy followed by resection”, respectively (both p &lt; 0.001). CONCLUSIONS Pre-operative biopsies for surgically accessible tumors with characteristic imaging features of Glioblastoma lead to worse survival despite subsequent resection compared to patients undergoing upfront resection.

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