Histogram analysis of apparent diffusion coefficient for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy

The history of magnetic resonance imaging and its reflections in Acta Radiologica

The first reports in Acta Radiologica on magnetic resonance imaging (MRI) were published in 1984, four years after the first commercial MR scanners became available. For the first two years, all MR papers originated from the USA. Nordic contributions started in 1986, and until 2020, authors from 44 different countries have published MR papers in Acta Radiologica. Papers on MRI have constituted, on average, 30%-40% of all published original articles in Acta Radiologica, with a high of 49% in 2019. The MR papers published since 1984 document tremendous progress in several areas such as magnet and coil design, motion compensation techniques, faster image acquisitions, new image contrast, contrast-enhanced MRI, functional MRI, and image analysis. In this historical review, all of these aspects of MRI are discussed and related to Acta Radiologica papers.

Association between IVIM parameters and treatment response in locally advanced squamous cell cervical cancer treated by chemoradiotherapy

OBJECTIVE

To examine the associations of intravoxel incoherent motion (IVIM) parameters with treatment response in cervical cancer following concurrent chemoradiotherapy (CCRT).

MATERIALS AND METHODS

Forty-five patients, median age of 58 years (range: 28-82), with pre-CCRT and post-CCRT MRI, were retrospectively analysed. The IVIM parameters pure diffusion coefficient (D) and perfusion fraction (f) were estimated using the full b-value distribution (BVD) as well as an optimised subsample BVD. Dice similarity coefficient (DSC) and intraclass correlation coefficient (ICC) were used to measure observer repeatability in tumour delineation at both time points. Treatment response was determined by the response evaluation criteria in solid tumour (RECIST) 1.1 between MRI examinations. Mann-Whitney U tests were used to test for significant differences in IVIM parameters between treatment response groups.

RESULTS

Pre-CCRT tumour delineation repeatability was good (DSC = 0.81) while post-CCRT delineation repeatability was moderate (DSC = 0.67). Values of D and f had good repeatability at both time points (ICC > 0.80). Pre-CCRT f estimated using the full BVD and optimised subsample BVD were found to be significantly higher in patients with partial response compared to those with stable disease or disease progression (p = 0.01 and 95% CI = -0.02-0.00 for both cases).

CONCLUSION

Pre-CCRT f was associated with treatment response in cervical cancer with good observer repeatability. Similar discriminative ability was also observed in estimated pre-CCRT f from an optimised subsample BVD.

KEY POINTS

• Pre-treatment tumour delineation and IVIM parameters had good observer repeatability. • Post-treatment tumour delineation was worse than at pre-treatment, but IVIM parameters retained good ICC. • Pre-treatment perfusion fraction estimated from all b-values and an optimised subsample of b-values were associated with treatment response.

Quantitative Magnetic Resonance Imaging for Biological Image-Guided Adaptive Radiotherapy

MRI-guided radiotherapy systems have the potential to bring two important concepts in modern radiotherapy together: adaptive radiotherapy and biological targeting. Based on frequent anatomical and functional imaging, monitoring the changes that occur in volume, shape as well as biological characteristics, a treatment plan can be updated regularly to accommodate the observed treatment response. For this purpose, quantitative imaging biomarkers need to be identified that show changes early during treatment and predict treatment outcome. This review provides an overview of the current evidence on quantitative MRI measurements during radiotherapy and their potential as an imaging biomarker on MRI-guided radiotherapy systems.

Association between MRI histogram features and treatment response in locally advanced cervical cancer treated by chemoradiotherapy

OBJECTIVE

To examine the associations of histogram features of T2-weighted (T2W) images and apparent diffusion coefficient (ADC) with treatment response in locally advanced cervical cancer (LACC) following concurrent chemoradiotherapy (CCRT).

MATERIALS AND METHODS

Fifty-eight patients who underwent a 4-week CCRT regimen with MRI prior to treatment (pre-CCRT) and after treatment (post-CCRT) were retrospectively analysed. Histogram features were calculated from volumes of interest (VOIs) from one radiologist on T2W images and ADC maps. VOIs from two radiologists were used to assess observer repeatability in delineation and feature values at both time-points with the Dice similarity coefficient (DSC) and intraclass correlation coefficient (ICC). Treatment response was defined as a 90% reduction in tumour volume. Paired Mann-Whitney U tests were used to determine if features changed significantly between examinations. Two-sample Mann-Whitney U tests were used to identify features that were significantly different between response groups. Receiver operating characteristic (ROC) analysis was done on significantly different MRI features between treatment response groups.

RESULTS

Pre-CCRT delineation and feature repeatability were generally good (DSC > 0.700; ICC > 0.750). Post-CCRT repeatability was low (DSC < 0.700; ICC < 0.750), but ADC mean and percentiles retained good ICC scores. All features, except for T2W_Kurtosis, significantly changed between examinations. Post-CCRT ADC₅₀ was the only feature that demonstrated both good observer variability and significant differences between treatment response groups (p = 0.036) and had an AUC of 0.701 with a cut-off of 1.357 × 10^-6 mm²/s.

CONCLUSION

ADC and T2W histogram features could be used to track changes in LACC tumours undergoing CCRT. Post-CCRT ADC₅₀ was associated with treatment response with good observer repeatability.

KEY POINTS

• Pre-treatment tumour delineation and histogram feature values had good observer repeatability, while these were less repeatable at post-treatment. • MRI histogram analysis could be used to track changes in the tumour as it undergoes concurrent chemoradiotherapy. • Post-treatment median ADC was associated with treatment response and had good repeatability.

Diagnosis of Cervical Cancer With Parametrial Invasion on Whole-Tumor Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined With Whole-Lesion Texture Analysis Based on T2- Weighted Images

Purpose: To evaluate the diagnostic value of the combination of whole-tumor dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and whole-lesion texture features based on T2-weighted images for cervical cancer with parametrial invasion. Materials and Methods: Sixty-two patients with cervical cancer (27 with parametrial invasion and 35 without invasion) preoperatively underwent routine MRI and DCE-MRI examinations. DCE-MRI parameters (K^trans, K_ep, and V_e) and texture features (mean, skewness, kurtosis, uniformity, energy, and entropy) based on T2-weighted images were acquired by two observers. All parameters of parametrial invasion and non-invasion were analyzed by one-way analysis of variance. The diagnostic efficiency of significant variables was assessed using receiver operating characteristic analysis. Results: The invasion group of cervical cancer demonstrated significantly higher K^trans (0.335 ± 0.050 vs. 0.269 ± 0.079; p < 0.001), lower energy values (0.503 ± 0.093 vs. 0.602 ± 0.087; p < 0.001), and higher entropy values (1.391 ± 0.193 vs. 1.24 ± 0.129; p < 0.001) than those in the non-invasion group. Optimal diagnostic performance [area under curve [AUC], 0.925; sensitivity, 0.935; specificity, 0.829] could be obtained by the combination of K^trans, energy, and entropy values. The AUC values of K^trans (0.788), energy (0.761), entropy (0.749), the combination of K^trans and energy (0.814), the combination of K^trans and entropy (0.727), and the combination of energy and entropy (0.619) were lower than those of the combination of K^trans, energy, and entropy values. Conclusion: The combination of DCE-MRI and texture analysis is a promising method for diagnosis cervical cancer with parametrial infiltration. Moreover, the combination of K^trans, energy, and entropy is more valuable than any one alone, especially in improving diagnostic sensitivity.

Impact of different b-value combinations on radiomics features of apparent diffusion coefficient in cervical cancer

Background

The impact of variable b-value combinations on apparent diffusion coefficient (ADC)-based radiomics features has not been fully addressed in literature.

Purpose

To investigate the correlation between radiomics features extracted from ADC maps and various b-value combinations in cervical cancer.

Material and Methods

Diffusion-weighted images (b-values: 0, 600, 800, and 1000 s/mm2) of 20 patients with cervical cancer were included. Tumors were identified with the largest transversal cross-section and manually segmented by radiologist. For each b-value combination, 92 radiomics features were extracted and coefficient of variance (CV) was used to evaluate the robustness of radiomics features with different b-value combinations. Features with CV > 5% were normalized by the mean feature variation across the group.

Results

Out of a total of 92 radiomics features, 18 were classified as robust features with CV ≤5%. Among the rest (CV > 5%), 11, 23, and 40 features demonstrated 5%< CV ≤10%, 10%< CV ≤20%, and CV > 20%, respectively. A subset of features in each category (CV > 5%) showed strong correlation with the b-value combination variation, including 44% (7/16) features in gray level co-occurrence matrix, 62% (8/13) features in gray level dependence matrix, 64% (9/14) features in first order, 50% (8/16) features in gray level run length matrix, 57% (8/14) features in gray level size matrix, and 20% (1/5) features in neighborhood gray-tone difference matrix.

Conclusions

Variations in b-value combinations demonstrated impact on radiomics features extracted from ADC maps for cervical cancer. The radiomics features with CV <5% can be considered as robust features and are recommended to be used in multicenter radiomics studies.

Evaluation of diffusion-weighted MRI and (18F) fluorothymidine-PET biomarkers for early response assessment in patients with operable non-small cell lung cancer treated with neoadjuvant chemotherapy

Objective:

To correlate changes in the apparent diffusion coefficient (ADC) from diffusion-weighted (DW)-MRI and standardised uptake value (SUV) from fluorothymidine (¹⁸FLT)-PET/CT with histopathological estimates of response in patients with non-small cell lung cancer (NSCLC) treated with neoadjuvant chemotherapy and track longitudinal changes in these biomarkers in a multicentre, multivendor setting.

Methods:

14 patients with operable NSCLC recruited to a prospective, multicentre imaging trial (EORTC-1217) were treated with platinum-based neoadjuvant chemotherapy. 13 patients had DW-MRI and FLT-PET/CT at baseline (10 had both), 12 were re-imaged at Day 14 (eight dual-modality) and nine after completing chemotherapy, immediately before surgery (six dual-modality). Surgical specimens (haematoxylin-eosin and Ki67 stained) estimated the percentage of residual viable tumour/necrosis and proliferation index.

Results:

Despite the small numbers,significant findings were possible. ADC_median increased (p < 0.001) and SUV_mean decreased (p < 0.001) significantly between baseline and Day 14; changes between Day 14 and surgery were less marked. All responding tumours (>30% reduction in unidimensional measurement pre-surgery), showed an increase at Day 14 in ADC75^th centile and reduction in total lesion proliferation (SUV_mean x proliferative volume) greater than established measurement variability. Change in imaging biomarkers did not correlate with histological response (residual viable tumour, necrosis).

Conclusion:

Changes in ADC and FLT-SUV following neoadjuvant chemotherapy in NSCLC were measurable by Day 14 and preceded changes in unidimensional size but did not correlate with histopathological response. However, the magnitude of the changes and their utility in predicting (non-) response (tumour size/clinical outcome) remains to be established.

Advances in knowledge:

During treatment, ADC increase precedes size reductions, but does not reflect histopathological necrosis.

Whole-Volume ADC Histogram Analysis in Parotid Glands to Identify Patients with Sjögren's Syndrome

At present, no gold standard for diagnosing Sjögren’s syndrome (SS) is available in clinical practice. The 2002 American–European Consensus Group classification criteria are used to diagnose SS. Clinically, it is challenging to distinguish patients with SS from suspected patients undergoing different therapies. A total of 52 patients with SS and 24 patients suspected of having the disease prospectively underwent 3.0-T magnetic resonance (MR) scanning, including diffusion-weighted imaging (b = 0 and 1000 s/mm²). The whole-volume apparent diffusion coefficient (ADC) histogram analysis generated ADC_mean, skewness, kurtosis, and entropy values from bilateral parotid glands. Continuous variables were compared using an independent two-sample t test, and categorical variable compared using the Fisher’s test between the two groups. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of the indexes. Fisher’s tests demonstrated that some clinical indexes and MR morphology grades differed significantly between patients with SS and patients suspected of having the disease (all P ≤ 0.001). The parotid entropy value of patients with SS was significantly higher than that of patients suspected of having the disease (P < 0.001). Among MR parameters, entropy combined with kurtosis performed the best in differentiating patients with SS from those suspected of having SS (area under the ROC curve = 0.955). A whole-volume ADC histogram analysis might provide a series of parameters that reflect tissue characteristics.

Whole-lesion ADC histogram analysis and the spondyloarthritis research consortium of canada (SPARCC) MRI index in evaluating the disease activity of ankylosing spondylitis

BACKGROUND

Conventional MRI is limited in quantitative evaluation of ankylosing spondylitis (AS) activity states. A comparison of the effectiveness of the whole-lesion apparent diffusion coefficient (ADC) histogram analysis with the Spondyloarthritis Research Consortium of Canada (SPARCC) MRI index in evaluating the disease activity of AS might aid in this assessment.

PURPOSE

To compare the effectiveness of the whole-lesion ADC histogram analysis with the SPARCC MRI index in evaluating the disease activity states of AS.

STUDY TYPE

Prospective.

POPULATION

A total of 57 AS patients and 27 healthy matched volunteers were included.

FIELD STRENGTH/SEQUENCE

3.0T MR including a diffusion-weighted imaging (DWI) sequence (b = 0, 1000 s/mm² ).

STATISTICAL TESTS

One-way analysis of variance (ANOVA) and Scheffe's post-hoc was used to compare the parameters among different groups. A receiver operating characteristic (ROC) analysis and the Spearman rank correlation were performed to test the diagnostic performance of all parameters in distinguishing different disease activity states and determining the correlations between them.

ASSESSMENT

AS disease activity states was evaluated according to the Ankylosing Spondylitis Disease Activity Score (ASDAS). Initial DWI images and corresponding ADC maps were imported into our in-house software. Regions of interest (ROIs) were drawn in all slices and the relevant parameters were derived simultaneously. The SPARCC MRI index scores were counted artificially based on T₂ -PDW-SPAIR images.

RESULTS

The ADC_mean , ADC percentiles, and SPARCC MRI index of the active group were significantly higher than the inactive and control groups (all P < 0.001). The 90th percentile could differentiate the inactive from the control group and the low disease activity group from the inactive group (P = 0.011 and 0.006, respectively). The 50th percentile of the high disease activity group was significantly higher than the low group (P = 0.004), while the SPARCC MRI index of the very high disease activity group was higher than the high group (P < 0.001).

DATA CONCLUSION

The whole-volume ADC histogram analysis was superior to the SPARCC MRI index in assessing AS activity states.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:114-126.

Associations between whole tumor histogram analysis parameters derived from ADC maps and expression of EGFR, VEGF, Hif 1-alpha, Her-2 and Histone 3 in uterine cervical cancer

OBJECTIVE

Diffusion weighted imaging (DWI) can be quantified by apparent diffusion coefficient (ADC) and can predict tissue microstructure. The aim of the present study was to analyze possible associations between ADC histogram based parameters with different histopathological parameters in cervical squamous cell carcinoma.

MATERIALS AND METHODS

18 female patients (age range 32-79 years) with squamous cell cervical carcinoma were retrospectively enrolled. In all cases, pelvic MRI was performed with a DWI (b-values 0 and 1000 s/mm²). Histogram analysis was performed as a whole lesion measurement. Histopathological parameters included expression of EGFR, VEGF, Hif1-alpha, Her2 and Histone 3. Spearman's correlation coefficient was used to analyze associations between investigated parameters.

RESULTS

Analyze of the investigated ADC histogram parameters showed a good interreader variability, ranging from 0.705 for entropy to 0.959 for ADCmedian. EGFR expression correlated statistically significant with several histogram parameters. The highest correlation was observed for p75 (p = -0.562, P = 0.015). There were several correlations with histone 3, the highest with p25 (p = -0.610, P = 0.007). None of the ADC related parameters correlated statistically significant with expression of VEGF, Hif1-alpha and Her2.

CONCLUSION

Histogram analysis showed a good interreader agreement. ADC histogram parameters might be able to reflect expression of EGFR and histone 3 in cervical squamous cell carcinomas, but not expression of VEGF, Hif1-alpha and Her2.

Whole-volume ADC Histogram and Texture Analyses of Parotid Glands as an Image Biomarker in Evaluating Disease Activity of Primary Sjögren's Syndrome

Diffusion weighted imaging (DWI) has proven to be sensitive for detecting early injury to the parotid gland in pSS (primary Sjögren’s syndrome). Here, we explored the application of ADC histogram and texture analyses for evaluating the disease activity of pSS. A total of 55 patients with pSS who met the classification criteria of the 2002 AECG criteria prospectively underwent 3.0-T magnetic resonance imaging (MRI) including DWI (b = 0 and 1000 s/mm²). According to the ESSDAI score, 35 patients were categorized into the low-activity group (ESSDAI < 5) and 20 into the moderate-high-activity group (ESSDAI ≥ 5). Via analysis of the whole-volume ADC histogram, the ADC_mean, skewness, kurtosis, and entropy values of the bilateral parotid glands were determined. Multivariate analysis was used to identify independent risk factors for predicting disease activity. The diagnostic performance of the indexes was evaluated via receiver operating characteristic (ROC) analysis. ROC analysis showed that the anti-SSB, lip biopsy, MRI morphology, ADC, ADC_mean, and entropy values were able to categorize the disease into two groups, particularly the entropy values. The multivariate model, which included anti-SSB, MRI morphology and entropy, had an area under the ROC curve of 0.923 (P < 0.001). The parotid entropy value distinguished disease activity in patients with pSS, especially combined with anti-SSB and MRI morphology.

Radiomics analysis of apparent diffusion coefficient in cervical cancer: A preliminary study on histological grade evaluation

BACKGROUND

The role of apparent diffusion coefficient (ADC)-based radiomics features in evaluating histopathological grade of cervical cancer is unresolved.

PURPOSE

To determine if there is a difference between radiomics features derived from center-slice 2D versus whole-tumor volumetric 3D for ADC measurements in patients with cervical cancer regarding tumor histopathological grade, and systematically assess the impact of the b value on radiomics analysis in ADC quantifications.

STUDY TYPE

Prospective.

SUBJECTS

In all, 160 patients with histopathologically confirmed squamous cell carcinoma of uterine cervix.

FIELD STRENGTH/SEQUENCE

Conventional and diffusion-weighted MR images (b values = 0, 800, 1000 s/mm² ) were acquired on a 3.0T MR scanner.

ASSESSMENT

Regions of interest (ROIs) were drawn manually along the margin of tumor on each slice, and then the center slice of the tumor was selected with naked eyes in the course of whole-tumor segmentation. A total of 624 radiomics features were derived from T₂ -weighted images and ADC maps. We randomly selected 50 cases and did the reproducibility analysis.

STATISTICAL TESTS

Parameters were compared using Wilcoxon signed rank test, Bland-Altman analysis, t-test, and least absolute shrinkage and selection operator (LASSO) regression with crossvalidation.

RESULTS

In all, 95 radiomics features were insensitive to ROI variation among T₂ images, ADC map of b800, and ADC map of b1000 (P > 0.0002). There was a significant statistical difference between the performances of 2D center-slice and 3D whole-tumor radiomics models in both ADC feature sets of b800 and b1000 (P < 0.0001, P < 0.0001). Compared with ADC features of b800 (0.3758 ± 0.0118), the model of b1000 ADC features appeared to be slightly lower in overall misclassification error (0.3642 ± 0.0162) (P = 0.0076).

DATA CONCLUSION

Several radiomics features extracted from T₂ images and ADC maps were highly reproducible. Whole-tumor volumetric 3D radiomics analysis had a better performance than using the 2D center-slice of tumor in stratifying the histological grade of cervical cancer. A b value of 1000 s/mm² is suggested as the optimal parameter in pelvic DWI scans.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:280-290.