4D perfusion CT of prostate cancer for image-guided radiotherapy planning: A proof of concept study

Contrast Agent Dynamics Determine Radiomics Profiles in Oncologic Imaging

BACKGROUND

The reproducibility of radiomics features extracted from CT and MRI examinations depends on several physiological and technical factors. The aim was to evaluate the impact of contrast agent timing on the stability of radiomics features using dynamic contrast-enhanced perfusion CT (dceCT) or MRI (dceMRI) in prostate and lung cancers.

METHODS

Radiomics features were extracted from dceCT or dceMRI images in patients with biopsy-proven peripheral prostate cancer (pzPC) or biopsy-proven non-small cell lung cancer (NSCLC), respectively. Features that showed significant differences between contrast phases were identified using linear mixed models. An L2-penalized logistic regression classifier was used to predict class labels for pzPC and unaffected prostate regions-of-interest (ROIs).

RESULTS

Nine pzPC and 28 NSCLC patients, who were imaged with dceCT and/or dceMRI, were included in this study. After normalizing for individual enhancement patterns by defining seven individual phases based on a reference vessel, 19, 467 and 128 out of 1204 CT features showed significant temporal dynamics in healthy prostate parenchyma, prostate tumors and lung tumors, respectively. CT radiomics-based classification accuracy of healthy and tumor ROIs was highly dependent on contrast agent phase. For dceMRI, 899 and 1027 out of 1118 features were significantly dependent on time after contrast agent injection for prostate and lung tumors.

CONCLUSIONS

CT and MRI radiomics features in both prostate and lung tumors are significantly affected by interindividual differences in contrast agent dynamics.

Comparison of image quality assessments between interventional radiographers and interventional radiologists using digital subtraction angiography

Purpose

The aim of our study was to compare the image quality assessments of vascular anatomy between interventional radiographers and interventional radiologists using digital subtraction angiography (DSA) runs acquired during an interventional radiology procedure.

Approach

Visual grading characteristics (VGC) analysis was used to assess image quality by comparing two groups of images, where one group consisted of procedures in which radiation dose was optimized (group A, n = 10 ) and one group where dose optimization was not performed (group B, n = 10 ). The radiation dose parameters were optimized based on theoretical and empirical evidence to achieve radiation dose reductions during uterine artery embolization procedures. The two observer groups comprised of interventional radiologists ( n = 4 ) and interventional radiographers ( n = 4 ). Each observer rated the image quality of 20 DSA runs using a five-point rating scale.

Results

The VGC analysis produced an area under the VGC curve (AUC VGC ) of 0.55 for interventional radiographers ( P = 0.61 ) and AUCVGC of 0.52 for interventional radiologists ( P = 0.83 ). The optimization of radiation dose parameters demonstrated a reduction in kerma-area product by 35% ( P = 0.026 , d = 0.5 ) and reference air kerma (Ka, r ) by 43% ( P = 0.042 , d = 0.5 ) between group A and group B.

Conclusions

VGC analysis indicated that the image quality assessments of interventional radiographers were comparable with interventional radiologists, where a reduction in radiation dose revealed no effect on both observer groups regarding their image quality assessment of vascular anatomy.

Rectal preparation significantly improves prostate imaging quality: Assessment of the PI-QUAL score with visual grading characteristics

PURPOSE

To investigate the effects of a rectal preparation regimen, that consisted of a rectal cleansing enema and an endorectal gel filling protocol, on prostate imaging quality (PI-QUAL).

METHODS

Multiparametric MRI (mpMRI) was performed in 150 consecutive patients divided into two groups of 75 patients. One group received a rectal preparation with a cleansing enema and endorectal gel filling (median age 65.3 years, median PSA level 6 ng/ml). The other patient group did not receive such a preparation (median age 64 years, median PSA level 6 ng/ml). Two uroradiologists independently rated general image quality and lesion visibility on diffusion-weighted imaging (DWI), T2-weighted (T2w), and dynamic contrast-enhanced (DCE) images using a five-point ordinal scale. In addition, two uroradiologists assigned PI-QUAL scores, using the dedicated scoring sheet. Data sets were compared using visual grading characteristics (VGC) and receiver operating characteristics (ROC)/ area under the curve (AUC) analysis.

RESULTS

VGC revealed significantly better general image quality for DWI (AUC R1 0.708 (0.628-0.779 CI, p < 0.001; AUC R2 0.687 (0.606-0.760 CI, p < 0.001) and lesion visibility for both readers (AUC R1 0.729 (0.607-0.831 CI, p < 0.001); AUC R2 0.714 (0.590-0.818CI, p < 0.001) in the preparation group. For T2w imaging, rectal preparation resulted in significantly better lesion visibility for both readers (R1 0.663 (0.537-0.774 CI, p = 0.014; R2 0.663 (0.537-0.774 CI, p = 0.014)). Averaged PI-QUAL scores were significantly improved with rectal preparation (AUC R3/R4 0.667, CI 0.581-0.754, p < 0.001).

CONCLUSION

Rectal preparation significantly improved prostate imaging quality (PI-QUAL) and lesion visibility. Hence, a rectal preparation regimen consisting of a rectal cleansing enema and an endorectal gel filling could be considered.

Diagnostic performance of dynamic volume perfusion CT for differentiation of head and neck cancer from healthy tissue and post-therapeutic changes

BACKGROUND

Post-therapeutic tissue is bradytrophic and thus has low perfusion values in PCT. In contrast, malignant tissue is expected to show higher perfusion values as cancer growth partially depends on angiogenesis.

OBJECTIVES

This prospective study investigates perfusion computed tomography (PCT) for the post-therapeutic detection of cancer in the head and neck region.

METHODS

85 patients underwent PCT for 1) initial work-up of head and neck cancer (HNC; n=22) or 2) for follow-up (n=63). Regions of interest (ROIs) were placed in confirmed tumour, a corresponding location of benign tissue, and reference tissue. Perfusion was calculated using a single input maximum slope algorithm. Statistical analysis was performed with the Mann-Whitney U-test.

RESULTS

PCT allowed significant differentiation of malignant tissue from post-therapeutic tissue after treatment for HNC (p=0.018). Significance was even greater after normalization of perfusion values (p=0.007). PCT allowed highly significant differentiation of HNC from reference tissue (p<0.001).

CONCLUSIONS

PCT provides significantly distinct perfusion values for malignant and benign as well as post-therapeutically altered tissue in the head and neck area, thus allowing differentiation of cancer from healthy tissue. Our results show that PCT in conjunction with a standard algorithm is a potentially powerful HNC diagnostic tool.