Correlation of ultra-high field MRI with histopathology for evaluation of rectal cancer heterogeneity

Prognostic prediction value of the clinical-radiomics tumour-stroma ratio in locally advanced rectal cancer

PURPOSE

To develop and validate a radiomics model based on high-resolution T2WI and a clinical-radiomics model for tumour-stroma ratio (TSR) evaluation with a gold standard of TSR evaluated by rectal specimens without therapeutic interference and further apply them in prognosis prediction of locally advanced rectal cancer (LARC) patients who received neoadjuvant chemoradiotherapy.

METHODS

A total of 178 patients (mean age: 59.35, range 20-85 years; 65 women and 113 men) with rectal cancer who received surgery alone from January 2016 to October 2020 were enrolled and randomly separated at a ratio of 7:3 into training and validation sets. A senior radiologist reviewed after 2 readers manually delineated the whole tumour in consensus on preoperative high-resolution T2WI in the training set. A total of 1046 features were then extracted, and recursive feature elimination embedded with leave-one-out cross validation was applied to select features, with which an MR-TSR evaluation model was built containing 6 filtered features via a support vector machine classifier trained by comparing patients' pathological TSR. Stepwise logistic regression was employed to integrate clinical factors with the radiomics model (Fusion-TSR) in the training set. Later, the MR-TSR and Fusion-TSR models were replicated in the validation set for diagnostic effectiveness evaluation. Subsequently, 243 patients (mean age: 53.74, range 23-74 years; 63 women and 180 men) with LARC from October 2012 to September 2017 who were treated with NCRT prior to surgery and underwent standard pretreatment rectal MR examination were enrolled. The MR-TSR and Fusion-TSR were applied, and the Kaplan-Meier method and log-rank test were used to compare the survival of patients with different MR-TSR and Fusion-TSR. Cox proportional hazards regression was used to calculate the hazard ratio (HR).

RESULTS

Both the MR-TSR and Fusion-TSR models were validated with favourable diagnostic power: the AUC of the MR-TSR was 0.77 (p = 0.01; accuracy = 69.8 %, sensitivity = 88.9 %, specificity = 65.9 %, PPV = 34.8 %, NPV = 96.7 %), while the AUC of the Fusion-TSR was 0.76 (p = 0.014; accuracy = 67.9 %, sensitivity = 88.9 %, specificity = 63.6 %, PPV = 33.3 %, NPV = 96.6 %), outperforming their effectiveness in the training set: the AUC of the MR-TSR was 0.65 (p = 0.035; accuracy = 66.4 %, sensitivity = 61.9 %, specificity = 67.3 %, PPV = 27.7 %, NPV = 90.0 %), while the AUC of the Fusion-TSR was 0.73 (p = 0.001; accuracy = 73.6 %, sensitivity = 71.4 %, specificity = 74.0 %, PPV = 35.73 %, NPV = 92.8 %). With further prognostic analysis, the MR-TSR was validated as a significant prognostic factor for DFS in LARC patients treated with NCRT (p = 0.020, HR = 1.662, 95 % CI = 1.077-2.565), while the Fusion-TSR was a significant prognostic factor for OS (p = 0.005, HR = 2.373, 95 % CI = 1.281-4.396).

CONCLUSIONS

We developed and validated a radiomics TSR and a clinical-radiomics TSR model and successfully applied them to better risk stratification for LARC patients receiving NCRT and for better decision making.

Prognostication of overall survival in patients with brain metastases using diffusion tensor imaging and dynamic susceptibility contrast-enhanced MRI

OBJECTIVES

To investigate the prognostic utility of DTI and DSC-PWI perfusion-derived parameters in brain metastases patients.

METHODS

Retrospective analyses of DTI-derived parameters (MD, FA, CL, CP, and CS) and DSC-perfusion PWI-derived rCBVmax from 101 patients diagnosed with brain metastases prior to treatment were performed. Using semi-automated segmentation, DTI metrics and rCBVmax were quantified from enhancing areas of the dominant metastatic lesion. For each metric, patients were classified as short- and long-term survivors based on analysis of the best coefficient for each parameter and percentile to separate the groups. Kaplan-Meier analysis was used to compare mOS between these groups. Multivariate survival analysis was subsequently conducted. A correlative histopathologic analysis was performed in a subcohort (n = 10) with DTI metrics and rCBVmax on opposite ends of the spectrum.

RESULTS

Significant differences in mOS were observed for MDmin (p < 0.05), FA (p < 0.01), CL (p < 0.05), and CP (p < 0.01) and trend toward significance for rCBVmax (p = 0.07) between the two risk groups, in the univariate analysis. On multivariate analysis, the best predictive survival model was comprised of MDmin (p = 0.05), rCBVmax (p < 0.05), RPA (p < 0.0001), and number of lesions (p = 0.07). On histopathology, metastatic tumors showed significant differences in the amount of stroma depending on the combination of DTI metrics and rCBVmax values. Patients with high stromal content demonstrated poorer mOS.

CONCLUSION

Pretreatment DTI-derived parameters, notably MDmin and rCBVmax, are promising imaging markers for prognostication of OS in patients with brain metastases. Stromal cellularity may be a contributing factor to these differences.

ADVANCES IN KNOWLEDGE

The correlation of DTI-derived metrics and perfusion MRI with patient outcomes has not been investigated in patients with treatment naïve brain metastasis. DTI and DSC-PWI can aid in therapeutic decision-making by providing additional clinical guidance.

Nanoscale biomaterials for terahertz imaging: A non-invasive approach for early cancer detection

Terahertz (THz) technology is developing a non-invasive imaging system for biosensing and clinical diagnosis. THz medical imaging mainly benefits from great sensitivity in detecting changes in water content and structural variations in diseased cells versus normal tissues. Compared to healthy tissues, cancerous tumors contain a higher level of water molecules and show structural changes, resulting in different THz absorption. Here we described the principle of THz imaging and advancement in the field of translational biomedicine and early detection of pathologic tissue, with a particular focus on oncology. In addition, although the main forte of THz imaging relies on detecting differences in water content to distinguish the exact margin of tumor, THz displays limited contrast in living tissue for in-vivo clinical imaging. In the last few years, nanotechnology has attracted attention to aid THz medical imaging and various nanoparticles have been investigated as contrast enhancements to improve the accuracy, sensitivity, and specificity of THz images. Most of these multimodal contrast agents take advantage of the temperature-dependent of THz spectrum to the conformational variation of the water molecule. We discuss advances in developing THz contrast agents to accelerate the advancement of non-invasive THz imaging with improved sensitivity and specificity for translational clinical oncology.

Predicting neoadjuvant chemoradiotherapy response with functional imaging and liquid biomarkers in locally advanced rectal cancer

INTRODUCTION

Non-invasive predictive quantitative biomarkers are required to guide treatment individualization in patients with locally advanced rectal cancer (LARC) in order to maximise therapeutic outcomes and minimise treatment toxicity. Magnetic resonance imaging (MRI), positron emission tomography (PET) and blood biomarkers have the potential to predict chemoradiotherapy (CRT) response in LARC.

AREAS COVERED

This review examines the value of functional imaging (MRI and PET) and liquid biomarkers (circulating tumor cells (CTCs) and circulating tumor nucleic acid (ctNA)) in the prediction of CRT response in LARC. Selected imaging and liquid biomarker studies are presented and the current status of the most promising imaging (apparent diffusion co-efficient (ADC), K^trans, SUV_max, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) and liquid biomarkers (circulating tumor cells (CTCs), circulating tumor nucleic acid (ctNA)) is discussed. The potential applications of imaging and liquid biomarkers for treatment stratification and a pathway to clinical translation are presented.

EXPERT OPINION

Functional imaging and liquid biomarkers provide novel ways of predicting CRT response. The clinical and technical validation of the most promising imaging and liquid biopsy biomarkers in multi-centre studies with harmonised acquisition techniques is required. This will enable clinical trials to investigate treatment escalation or de-escalation pathways in rectal cancer.

Correlation of in-vivo imaging with histopathology: A review

Despite tremendous advancements in in vivo imaging modalities, there remains substantial uncertainty with respect to tumor delineation on in these images. Histopathology remains the gold standard for determining the extent of malignancy, with in vivo imaging to histopathologic correlation enabling spatial comparisons. In this review, the steps necessary for successful imaging to histopathologic correlation are described, including in vivo imaging, resection, fixation, specimen sectioning (sectioning technique, securing technique, orientation matching, slice matching), microtome sectioning and staining, correlation (including image registration) and performance evaluation. The techniques used for each of these steps are also discussed. Hundreds of publications from the past 20 years were surveyed, and 62 selected for detailed analysis. For these 62 publications, each stage of the correlative pathology process (and the sub-steps of specimen sectioning) are listed. A statistical analysis was conducted based on 19 studies that reported target registration error as their performance metric. While some methods promise greater accuracy, they may be expensive. Due to the complexity of the processes involved, correlative pathology studies generally include a small number of subjects, which hinders advanced developments in this field.

Contemporary radiotherapy: present and future

Oncology care is increasingly a multidisciplinary endeavour, and radiation therapy continues to have a key role across the disease spectrum in nearly every cancer. However, the field of radiation oncology is still one of the most poorly understood of the cancer disciplines. In this Review, we attempt to summarise and contextualise developments within the field of radiation oncology for the non-radiation oncologist. We discuss advancements in treatment technologies and imaging, followed by an overview of the interplay with advancements in systemic therapy and surgical techniques. Finally, we review new frontiers in radiation oncology, including advances within the metastatic disease continuum, reirradiation, and emerging types of radiation therapy.

Diffusion tensor imaging of rectal carcinoma: Clinical evaluation and its correlation with histopathological findings

OBJECTIVE

This study sought to assess the feasibility of diffusion tensor imaging (DTI) to noninvasively evaluate histological grade and lymph node metastasis in patients with rectal carcinoma (RC).

METHODS

Thirty-seven consecutive patients with histologically confirmed RC were examined by 1.5-T MRI. DTI was performed using a single-shot echo-planar imaging sequence with b values of 0 and 1000 s/mm² and motion-probing gradients in nine noncollinear directions. Fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) maps were compared with histopathological findings.

RESULTS

The FA values (0.357 ± 0.047) of the RCs were significantly lower than those of the normal rectal wall, muscle, prostate, and uterus (P < 0.001 for all), while the AD, MD, and RD values (1.221 ± 0.131, 0.804 ± 0.075, and 0.667 ± 0.057 × 10^-3 mm²/s, respectively) were also significantly lower than their respective normal values (P < 0.001 for all). The FA, AD, MD, and RD values for RC additionally showed significant inverse correlations with histological grades (r = -0.781, r = -0.750, r = -0.718, and r = -0.682, respectively; P < 0.001 for all). Further, the FA (0.430 vs. 0.611), AD (1.246 vs. 1.608 × 10^-3 mm²/s), MD (0.776 vs. 1.036 × 10^-3 mm²/s), and RD (0.651 vs. 0.824 × 10^-3 mm²/s) (P < 0.001 for all) of the metastatic and nonmetastatic lymph nodes were significantly different.

CONCLUSIONS

DTI may be clinically useful for the noninvasive evaluation of histological grade and lymph node metastasis in patients with RC.

Scanning electron microscopy as a new tool for diagnostic pathology and cell biology

Scanning electron microscopy (SEM) use in the biomedical sciences has traditionally been used for characterisation of cell and tissue surface topography. This paper demonstrates the utility of high-resolution scanning electron microscopy (HRSEM) to diagnostic pathology and cell biology ultrastructural examinations. New SEM applications based on the production of transmission electron microscopy-like (TEM-like) images are now possible with the recent introduction of new technologies such as low kV scanning transmission electron microscopy (STEM) detectors, automated scan generators and high-resolution column configurations capable of sub-nanometre resolution. Typical specimen types traditionally imaged by TEM have been examined including renal, lung, prostate and brain tissues. The specimen preparation workflow was unchanged from that routinely used to prepare TEM tissue, apart from replacing copper grids for section mounting with a silicon substrate. These instruments feature a small footprint with little in the way of ancillary equipment, such as water chillers, and are more cost-effective than traditional TEM columns. Also, a new generation of benchtop SEMs have recently become available and have also been assessed for its utility in the tissue pathology and cell biology settings.