Variation in apparent diffusion coefficient measurements among women with locally advanced cervical cancer

Gladwish, Adam; Han, Kathy; Foltz, Warren D.

doi:10.1016/j.radonc.2015.09.010

Cited by 4 publications

(5 citation statements)

References 29 publications

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“…Stacks of 2D T2-weighted images and ADC maps covering the cervical tumor were acquired on Siemens MRI systems [15]. The ADC maps were acquired according to the parameter sets in Table E1 (Supplementary Material).…”

Section: Mri Methodologymentioning

confidence: 99%

“…Normalization was applied to the whole image (not only within the ROI), by subtracting mean intensity centring it and dividing by the standard deviation. An additional biological-based normalization was considered by drawing a circular ROI of 10 mm diameter in the middle of the bladder, where the urine signal was maximum for each patient [15]. Each intensity level was then normalized by dividing original values by the median intensity of the ROI.…”

Section: Normalizationmentioning

confidence: 99%

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Sensitivity of radiomic features to inter-observer variability and image pre-processing in Apparent Diffusion Coefficient (ADC) maps of cervix cancer patients

Traverso

Kazmierski

Welch

et al. 2020

Radiotherapy and Oncology

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a b s t r a c tPurpose: The aims of this study are to evaluate the stability of radiomic features from Apparent Diffusion Coefficient (ADC) maps of cervical cancer with respect to: (1) reproducibility in inter-observer delineation, and (2) image pre-processing (normalization/quantization) prior to feature extraction. Materials and methods: Two observers manually delineated the tumor on ADC maps derived from pretreatment diffusion-weighted Magnetic Resonance imaging of 81 patients with FIGO stage IB-IVA cervical cancer. First-order, shape, and texture features were extracted from the original and filtered images considering 5 different normalizations (four taken from the available literature, and one based on urine ADC) and two different quantization techniques (fixed-bin widths from 0.05 to 25, and fixed-bin count). Stability of radiomic features was assessed using intraclass correlation coefficient (ICC): poor (ICC < 0.75); good (0.75 ICC 0.89), and excellent (ICC ! 0.90). Dependencies of the features with tumor volume were assessed using Spearman's correlation coefficient (q). Results: The approach using urine-normalized values together with a smaller bin width (0.05) was the most reproducible (428/552, 78% features with ICC ! 0.75); the fixed-bin count approach was the least (215/552, 39% with ICC ! 0.75). Without normalization, using a fixed bin width of 25, 348/552 (63%) of features had an ICC ! 0.75. Overall, 26% (range 25-30%) of the features were volume-dependent (q ! 0.6). None of the volume-independent shape features were found to be reproducible. Conclusion: Applying normalization prior to features extraction increases the reproducibility of ADCbased radiomics features. When normalization is applied, a fixed-bin width approach with smaller widths is suggested. Ó 2019 The Author(s). Published by Elsevier B.V. Radiotherapy and Oncology 143 (2020) 88-94 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Cervical cancer is the fourth most frequent cancer in women, with an estimated 570,000 new cases in 2018, representing 6.6% of all female cancers worldwide. Cervical cancer still represents a significant burden for middle-and low-income countries [1]. Standard treatment for locally advanced (stage IB2-IVA) cervical cancer is concurrent chemoradiation.Computed Tomography (CT) and Magnetic Resonance (MR) are the standard imaging modalities for cervical cancer staging and evaluation of treatment response. Through appropriate choice of pulse sequences MR imaging provides greater soft tissue contrast than CT and enables assessment of physiological parameters and biochemical function. Diffusion-weighted imaging (DWI) in MR enables measurement of water diffusivity via generation of Apparent Diffusion Coefficient (ADC) maps, and ADC is an established biomarker of tumor cell density and related changes posttherapy [2]. DWI is increasing acquired in addition to T2weighted MRI to detect cervical tumor [3], and pre-treatment tumor ADC has been shown to be p...

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Section: Mri Methodologymentioning

confidence: 99%

Section: Normalizationmentioning

confidence: 99%

Sensitivity of radiomic features to inter-observer variability and image pre-processing in Apparent Diffusion Coefficient (ADC) maps of cervix cancer patients

Traverso

Kazmierski

Welch

et al. 2020

Radiotherapy and Oncology

Self Cite

View full text Add to dashboard Cite

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“…Higher B-values are preferred as the ratio of tumour signalesurroundings is less; however, differences were <10% even for quantitative ADC analyses. 32 Therefore, due to the qualitative nature and the relatively small difference in B-value, the present results are not expected to be hampered due to the change in protocol. Changes in imaging protocol are common and reflect general practice.…”

Section: Discussionmentioning

confidence: 82%

Assessment of parametrial invasion of cervical carcinoma, the role of T2-weighted MRI and diffusion weighted imaging with or without fusion

et al. 2019

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“…Gladwish et al evaluated ADC prior to radiation treatment and found a difference of 10% between 2D and 3D techniques, with good interobserver variability. [28] The size of a circle-like ROI is important in this respect [29], with breast and rectal carcinoma studies suggesting that a small ROI contributes to greater variability in ADC in comparison with a freehand ROI delineating as much as possible of the visible tumor. [19,22,30] To date, the correlation between lymph node metastases and ADC Mean shows a substantial variety in different retrospective studies [14]; however, the majority of studies found a correlation [13,16].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of various apparent diffusion coefficient measurement techniques in pre-operative staging of early cervical carcinoma

Mongula

Bakers

Slangen

et al. 2019

European Journal of Radiology

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Variation in apparent diffusion coefficient measurements among women with locally advanced cervical cancer

Cited by 4 publications

References 29 publications

Sensitivity of radiomic features to inter-observer variability and image pre-processing in Apparent Diffusion Coefficient (ADC) maps of cervix cancer patients

Sensitivity of radiomic features to inter-observer variability and image pre-processing in Apparent Diffusion Coefficient (ADC) maps of cervix cancer patients

Assessment of parametrial invasion of cervical carcinoma, the role of T2-weighted MRI and diffusion weighted imaging with or without fusion

Evaluation of various apparent diffusion coefficient measurement techniques in pre-operative staging of early cervical carcinoma

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