Relationship Between Imaging Biomarkers of Stage I Cervical Cancer and Poor-Prognosis Histologic Features: Quantitative Histogram Analysis of Diffusion-Weighted MR Images

Downey, Kate; Riches, Sophie F.; Morgan, Veronica A.; Giles, Sharon; Attygalle, Ayoma; Ind, Thomas; Barton, Desmond P.J.; Shepherd, John H.; deSouza, Nandita M.

doi:10.2214/ajr.12.9545

Cited by 130 publications

(112 citation statements)

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“…In body imaging, Kyriazi et al (34) showed an increase in ADCs and a later decrease in skewness and kurtosis in response to chemotherapy in patients GENITOURINARY IMAGING: Myometrial and Lymphovascular Invasion and Endometrial Tumor Grade Nougaret et al with metastatic ovarian and primary peritoneal cancer. More recently, ADC histographic analysis has been applied in patients with cervical cancer to the whole tumor volume instead of to selected ROIs to eliminate sampling bias (35). In this study, the authors showed lower mean ADCs in poorly differentiated tumors than those in well or moderately differentiated tumors (35).…”

Section: Author Contributionsmentioning

confidence: 67%

“…More recently, ADC histographic analysis has been applied in patients with cervical cancer to the whole tumor volume instead of to selected ROIs to eliminate sampling bias (35). In this study, the authors showed lower mean ADCs in poorly differentiated tumors than those in well or moderately differentiated tumors (35). The ability to predict high-grade endometrial cancer by using ADC histographic analysis of whole tumor volumes is of clinical interest for two reasons: First, histologic tumor grade is a strong predictor of nodal involvement (36); and second, there is relatively frequent discordance of the preoperative cytologic results with the findings at final surgical pathologic examination due to undersampling (37).…”

Section: Author Contributionsmentioning

confidence: 99%

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Endometrial Cancer: Combined MR Volumetry and Diffusion-weighted Imaging for Assessment of Myometrial and Lymphovascular Invasion and Tumor Grade

Nougaret¹,

Reinhold²,

AlSharif³

et al. 2015

Radiology

140

114

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Purpose:To investigate magnetic resonance (MR) volumetry of endometrial tumors and its association with deep myometrial invasion, tumor grade, and lymphovascular invasion and to assess the value of apparent diffusion coefficient (ADC) histographic analysis of the whole tumor volume for prediction of tumor grade and lymphovascular invasion. Materials and Methods:The institutional review board approved this retrospective study; patient consent was not required. Between May 2010 and May 2012, 70 women (mean age, 64 years; range, 24-91 years) with endometrial cancer underwent preoperative MR imaging, including axial oblique and sagittal T2-weighted, dynamic contrast material-enhanced, and diffusion-weighted imaging. Volumetry of the tumor and uterus was performed during the six sequences, with manual tracing of each section, and the tumor volume ratio (TVR) was calculated. ADC histograms were generated from pixel ADCs from the whole tumor volume. The threshold of TVR associated with myometrial invasion was assessed by using receiver operating characteristic curves. An independent sample Mann Whitney U test was used to compare differences in ADCs, skewness, and kurtosis between tumor grade and the presence of lymphovascular invasion. Results:No significant difference in tumor volume and TVR was found among the six MR imaging sequences (P = .95 and .86, respectively). A TVR greater than or equal to 25% allowed prediction of deep myometrial invasion with sensitivity of 100% and specificity of 93% (area under the curve, 0.96; 95% confidence interval: 0.86, 0.99) at axial oblique diffusion-weighted imaging. A TVR of greater than or equal to 25% was associated with grade 3 tumors (P = .0007) and with lymphovascular invasion (P , .0001).There was no significant difference in the ADCs between grades 1 and 2 tumors (P . .05). The minimum, 10th, 25th, 50th, 75th, and 90th percentile ADCs were significantly lower in grade 3 tumors than in grades 1 and 2 tumors (P , .02). Conclusion:The combination of whole tumor volume and ADC can be used for prediction of tumor grade, lymphovascular invasion, and depth of myometrial invasion.q RSNA, 2015

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Section: Author Contributionsmentioning

confidence: 67%

Section: Author Contributionsmentioning

confidence: 99%

Endometrial Cancer: Combined MR Volumetry and Diffusion-weighted Imaging for Assessment of Myometrial and Lymphovascular Invasion and Tumor Grade

Nougaret¹,

Reinhold²,

AlSharif³

et al. 2015

Radiology

140

114

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“…The histogram approach has been increasingly used for heterogeneous tissues, allowing interpretation of the complex nature and features seen in tumors 17. Previous studies in adults have utilized histogram analysis of ADC and cerebral blood volume (CBV), which has been applied to a variety of scenarios including differentiation of true tumor progression from pseudoprogression,28, 29 response to chemotherapy,30 and grading of tumors 31, 32, 33. Most previous pediatric studies have reported mean or median ADC values based on a single section or slice, which does not address the heterogeneity seen in many abdominal tumors 7, 8…”

Section: Discussionmentioning

confidence: 99%

Diffusion‐weighted MRI and intravoxel incoherent motion model for diagnosis of pediatric solid abdominal tumors

Meeus

Zarinabad

Manias

et al. 2017

Magnetic Resonance Imaging

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BackgroundPediatric retroperitoneal tumors in the renal bed are often large and heterogeneous, and their diagnosis based on conventional imaging alone is not possible. More advanced imaging methods, such as diffusion‐weighted (DW) MRI and the use of intravoxel incoherent motion (IVIM), have the potential to provide additional biomarkers that could facilitate their noninvasive diagnosis.PurposeTo assess the use of an IVIM model for diagnosis of childhood malignant abdominal tumors and discrimination of benign from malignant lesions.Study TypeRetrospective.PopulationForty‐two pediatric patients with abdominal lesions (n = 32 malignant, n = 10 benign), verified by histopathology.Field Strength/Sequence1.5T MRI system and a DW‐MRI sequence with six b‐values (0, 50, 100, 150, 600, 1000 s/mm2).AssessmentParameter maps of apparent diffusion coefficient (ADC), and IVIM maps of slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion fraction (f) were computed using a segmented fitting model. Histograms were constructed for whole‐tumor regions of each parameter.Statistical TestsComparison of histogram parameters of and their diagnostic performance was determined using Kruskal–Wallis, Mann–Whitney U, and receiver‐operating characteristic (ROC) analysis.ResultsIVIM parameters D* and f were significantly higher in neuroblastoma compared to Wilms' tumors (P < 0.05). The ROC analysis showed that the best diagnostic performance was achieved with D* 90th percentile (area under the curve [AUC] = 0.935; P = 0.002; cutoff value = 32,376 × 10−6 mm2/s) and f mean values (AUC = 1.00; P < 0.001; cutoff value = 14.7) in discriminating between neuroblastoma (n = 11) and Wilms' tumors (n = 8). Discrimination between tumor types was not possible with IVIM D or ADC parameters. Malignant tumors revealed significantly lower ADC, D, and higher D* values than in benign lesions (all P < 0.05).Data ConclusionIVIM perfusion parameters could distinguish between malignant childhood tumor types, providing potential imaging biomarkers for their diagnosis. Level of Evidence: 4 Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2018;47:1475–1486.

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“…Recently, there has been growing interest in the histogram analysis of ADC of the entire tumor volume, as this approach provides quantitative information on the distribution and frequency of ADCs and consequently on the heterogeneity of water molecules diffusivity within the whole tumor [14][15][16][17]. The histogram-based ADC analysis has shown capabilities in differentiating and grading brain tumors [14][15][16], and in the prediction of uterine cervical cancer recurrence [18,19].…”

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confidence: 99%

Pancreatic neuroendocrine tumors: correlation between histogram analysis of apparent diffusion coefficient maps and tumor grade

et al. 2015

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Purpose: To explore the role of histogram analysis of apparent diffusion coefficient (ADC) MRI maps based on entire tumor volume data in determining pancreatic neuroendocrine tumor (PNT) grade. Methods and Materials: Retrospective evaluation of 22 patients with PNTs included low-grade (G1; n = 15), intermediate-grade (G2; n = 4), and high-grade (G3; n = 3) tumors. Regions of interest containing the lesion were drawn on every section of the ADC map containing the tumor and summated to obtain histograms for entire tumor volume. Calculated histographic parameters included mean ADC (mADC), 5th percentile ADC, 10th percentile ADC, 25th percentile ADC, 50th percentile ADC, 75th percentile ADC (ADC75), 90th percentile ADC (ADC90) and 95th percentile ADC (ADC95), skewness and kurtosis. Histogram parameters were correlated with tumor grade by repeated measures analysis of variance with Tukey-Kramer post hoc comparisons. Results: The mADC, ADC75, ADC90, and ADC95 were significantly higher in

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Relationship Between Imaging Biomarkers of Stage I Cervical Cancer and Poor-Prognosis Histologic Features: Quantitative Histogram Analysis of Diffusion-Weighted MR Images

Abstract: Median ADC is lower in poorly compared with well or moderately differentiated tumors, while lower histogram-positive skew in adenocarcinoma compared with squamous cell carcinoma is likely to reflect the glandular content of adenocarcinoma.

Cited by 130 publications

References 36 publications

Endometrial Cancer: Combined MR Volumetry and Diffusion-weighted Imaging for Assessment of Myometrial and Lymphovascular Invasion and Tumor Grade

Endometrial Cancer: Combined MR Volumetry and Diffusion-weighted Imaging for Assessment of Myometrial and Lymphovascular Invasion and Tumor Grade

Diffusion‐weighted MRI and intravoxel incoherent motion model for diagnosis of pediatric solid abdominal tumors

Pancreatic neuroendocrine tumors: correlation between histogram analysis of apparent diffusion coefficient maps and tumor grade

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