Quantitative CT perfusion imaging in patients with pancreatic cancer: a systematic review

Utilization of relative evaluation of pancreatic perfusion CT parameters to support appropriate pancreatic adenocarcinoma diagnosis

OBJECTIVES

To investigate the effect of relative evaluation of perfusion computed tomography (PCT) parameters in the diagnosis of pancreatic adenocarcinoma (PAC).

METHODS

Of the 117 patients in which PCT was performed (May 2019 to June 2023), 99 patients with mass lesions (MLs), including 50 PAC and 11 patients with mass-forming pancreatitis (MFP), and 15 patients without MLs but with main pancreatic duct (MPD) abnormalities, including 6 PAC and 7 no diagnosis of malignancy (NDM) cases were enrolled in this study. Parameter values were obtained from parametric maps of blood flow (BF), blood volume (BV), and mean transit time (MTT) for the ML and abnormal MPD part (AMP), pancreas and spleen. Diagnostic performance was evaluated based on receiver operating characteristic analysis for absolute values and relative values for pancreas and spleen.

RESULTS

BFML, BVML, BFML/Pancreas, BFML/Spleen, BVML/Pancreas and BVML/Spleen were significantly lower in PAC than MFP cases. Areas under the curve (AUCs) for BFML, BFML/Pancreas, BFML/Spleen were 0.71 (sensitivity, 54 %; specificity, 91 %), 0.80 (sensitivity, 74 %; specificity, 82 %) and 0.79 (sensitivity, 68 %; specificity. 91 %), respectively. The AUCs for BVML, BVML/Pancreas, BVML/Spleen were 0.72 (sensitivity, 48 %; specificity, 100 %), 0.85 (sensitivity, 76 %; specificity, 91 %) and 0.87 (sensitivity, 76 %; specificity, 91 %), respectively, with significantly better diagnostic performance on relative evaluation (P < 0.05). BVAMP/Spleen and MTTAMP/Spleen were significantly higher in PAC than NDM cases, with AUCs of 1 (100 % sensitivity and specificity) and 0.91 (sensitivity, 86 %; specificity, 100 %), respectively.

CONCLUSIONS

Relative evaluation of PCT parameters is expected to contribute to more appropriate diagnosis of PAC.

Performance of different CT enhancement quantification methods as predictors of pancreatic cancer recurrence after upfront surgery

The prognosis of pancreatic cancer (PDAC) after tumor resection remains poor, mostly due to a high but variable risk of recurrence. A promising tool for improved prognostication is the quantification of CT tumor enhancement. For this, various enhancement formulas have been used in previous studies. However, a systematic comparison of these formulas is lacking. In the present study, we applied twenty-three previously published CT enhancement formulas to our cohort of 92 PDAC patients who underwent upfront surgery. We identified seven formulas that could reliably predict tumor recurrence. Using these formulas, weak tumor enhancement was associated with tumor recurrence at one and two years after surgery (p ≤ 0.030). Enhancement was inversely associated with adverse clinicopathological features. Low enhancement values were predictive of a high recurrence risk (Hazard Ratio ≥ 1.659, p ≤ 0.028, Cox regression) and a short time to recurrence (TTR) (p ≤ 0.027, log-rank test). Some formulas were independent predictors of TTR in multivariate models. Strikingly, almost all of the best-performing formulas measure solely tumor tissue, suggesting that normalization to non-tumor structures might be unnecessary. Among the top performers were also the absolute arterial/portal venous tumor attenuation values. These can be easily implemented in clinical practice for better recurrence prediction, thus potentially improving patient management.

Qualitative flow metabolic phenotype of pancreatic cancer. A new prognostic biomarker?

BACKGROUND

Retrospective analysis to investigate the relationship between the flow-metabolic phenotype and overall survival (OS) of pancreatic ductal adenocarcinoma (PDAC) and its potential clinical utility.

METHODS

Patients with histopathologically proven PDAC between 2005 and 2014 using tumor attenuation on routine pre-operative CECT as a surrogate for the vascularity and [18F]FDG-uptake as a surrogate for metabolic activity on [18F]FDG-PET.

RESULTS

In total, 93 patients (50 male, 43 female, median age 63) were included. Hypoattenuating PDAC with high [18F]FDG-uptake has the poorest prognosis (median OS 7 ± 1 months), compared to hypoattenuating PDAC with low [18F]FDG-uptake (median OS 11 ± 3 months; p = 0.176), iso- or hyperattenuating PDAC with high [18F]FDG-uptake (median OS 15 ± 5 months; p = 0.004) and iso- or hyperattenuating PDAC with low [18F]FDG-uptake (median OS 23 ± 4 months; p = 0.035). In multivariate analysis, surgery combined with tumor differentiation, tumor stage, systemic therapy and flow metabolic phenotype remained independent predictors for overall survival.

DISCUSSION

The novel qualitative flow-metabolic phenotype of PDAC using a combination of CECT and [18F]FDG-PET features, predicted significantly worse survival for hypoattenuating-high uptake pancreatic cancers compared to the other phenotypes.

Automated Quantitative Analysis of CT Perfusion to Classify Vascular Phenotypes of Pancreatic Ductal Adenocarcinoma

CT perfusion (CTP) analysis is difficult to implement in clinical practice. Therefore, we investigated a novel semi-automated CTP AI biomarker and applied it to identify vascular phenotypes of pancreatic ductal adenocarcinoma (PDAC) and evaluate their association with overall survival (OS).

METHODS

From January 2018 to November 2022, 107 PDAC patients were prospectively included, who needed to undergo CTP and a diagnostic contrast-enhanced CT (CECT). We developed a semi-automated CTP AI biomarker, through a process that involved deformable image registration, a deep learning segmentation model of tumor and pancreas parenchyma volume, and a trilinear non-parametric CTP curve model to extract the enhancement slope and peak enhancement in segmented tumors and pancreas. The biomarker was validated in terms of its use to predict vascular phenotypes and their association with OS. A receiver operating characteristic (ROC) analysis with five-fold cross-validation was performed. OS was assessed with Kaplan-Meier curves. Differences between phenotypes were tested using the Mann-Whitney U test.

RESULTS

The final analysis included 92 patients, in whom 20 tumors (21%) were visually isovascular. The AI biomarker effectively discriminated tumor types, and isovascular tumors showed higher enhancement slopes (2.9 Hounsfield unit HU/s vs. 2.0 HU/s, p < 0.001) and peak enhancement (70 HU vs. 47 HU, p < 0.001); the AUC was 0.86. The AI biomarker's vascular phenotype significantly differed in OS (p < 0.01).

CONCLUSIONS

The AI biomarker offers a promising tool for robust CTP analysis. In PDAC, it can distinguish vascular phenotypes with significant OS prognostication.

Tumour status prediction by means of carbon-ion beam irradiation: comparison of washout rates between in-beam PET and DCE-MRI in rats

Objective.Tumour response to radiation therapy appears as changes in tumour vascular condition. There are several methods for analysing tumour blood circulatory changes one of which is dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), but there is no method that can observe the tumour vascular condition and physiological changes at the site of radiation therapy. Positron emission tomography (PET) has been applied for treatment verification in charged particle therapy, which is based on the detection of positron emitters produced through nuclear fragmentation reactions in a patient's body. However, the produced positron emitters are washed out biologically depending on the tumour vascular condition. This means that measuring the biological washout rate may allow evaluation of the tumour radiation response, in a similar manner to DCE-MRI. Therefore, this study compared the washout rates in rats between in-beam PET during12C ion beam irradiation and DCE-MRI.Approach.Different vascular conditions of the tumour model were prepared for six nude rats. The tumour of each nude rat was irradiated by a12C ion beam with simultaneous in-beam PET measurement. In 10-12 h, the DCE-MRI experiment was performed for the same six nude rats. The biological washout rate of the produced positron emitters (k2,1st) and the MRI contrast agent (k2a) were derived using the single tissue compartment model.Main results.A linear correlation was observed betweenk2,1standk2a, and they were inversely related to fractional necrotic volume.Significance.This is the first animal study which confirmed the biological washout rate of in-beam PET correlates closely with tumour vascular condition measured with the MRI contrast agent administrated intravenously.

Optimization of laser dosimetry based on patient-specific anatomical models for the ablation of pancreatic ductal adenocarcinoma tumor

Laser-induced thermotherapy has shown promising potential for the treatment of unresectable primary pancreatic ductal adenocarcinoma tumors. Nevertheless, heterogeneous tumor environment and complex thermal interaction phenomena that are established under hyperthermic conditions can lead to under/over estimation of laser thermotherapy efficacy. Using numerical modeling, this paper presents an optimized laser setting for Nd:YAG laser delivered by a bare optical fiber (300 µm in diameter) at 1064 nm working in continuous mode within a power range of 2-10 W. For the thermal analysis, patient-specific 3D models were used, consisting of tumors in different portions of the pancreas. The optimized laser power and time for ablating the tumor completely and producing thermal toxic effects on the possible residual tumor cells beyond the tumor margins were found to be 5 W for 550 s, 7 W for 550 s, and 8 W for 550 s for the pancreatic tail, body, and head tumors, respectively. Based on the results, during the laser irradiation at the optimized doses, thermal injury was not evident either in the 15 mm lateral distances from the optical fiber or in the nearby healthy organs. The present computational-based predictions are also in line with the previous ex vivo and in vivo studies, hence, they can assist in the estimation of the therapeutic outcome of laser ablation for pancreatic neoplasms prior to clinical trials.

Tumor therapeutic response monitored by telemetric temperature sensing, a preclinical study on immunotherapy and chemotherapy

Temperature in the body and the tumor reflects physiological and pathological conditions. A reliable, contactless, and simplistic measurement system can be used for long-term monitoring of disease progression and therapy response. In this study, miniaturized battery-free wireless chips implanted into growing tumors on small animals were used to capture both basal and tumor temperature dynamics. Three preclinical models: melanoma (B16), breast cancer (4T1), and colon cancer (MC-38), were treated with adoptive T cell transfer, AC-T chemotherapy, and anti-PD-1 immunotherapy respectively. Each model presents a distinctive pattern of temperature history dependent on the tumor characteristic and influenced by the administered therapy. Certain features are associated with positive therapeutic response, for instance the transient reduction of body and tumor temperature following adaptive T cell transfer, the elevation of tumor temperature following chemotherapy, and a steady decline of body temperature following anti-PD-1 therapy. Tracking in vivo thermal activity by cost-effective telemetric sensing has the potential of offering earlier treatment assessment to patients without requiring complex imaging or lab testing. Multi-parametric on-demand monitoring of tumor microenvironment by permanent implants and its integration into health information systems could further advance cancer management and reduce patient burden.

CT perfusion as a potential biomarker for pancreatic ductal adenocarcinoma during routine staging and restaging

PURPOSE

To evaluate the significance of CT perfusion parameters predicting response to neoadjuvant therapy in patients with pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

Seventy patients with PDAC prospectively had CT perfusion acquisition incorporated into baseline multiphase staging CT. Twenty-eight who were naïve to therapy were retained for further investigation. Perfusion was performed 5-42.5 s after contrast, followed by parenchymal and portal venous phases. Blood flow (BF), blood volume (BV), and permeability surface area product (PS) were calculated using deconvolution algorithms. Patients were categorized as responders or non-responders per RECIST 1.1. Perfusion variables with AUC ≥ 0.70 in differentiating responders from non-responders were retained. Logistic regression was used to assess associations between baseline perfusion variables and response.

RESULTS

18 of 28 patients showed favorable response to therapy. Baseline heterogeneity variables in tumor max ROI were higher in non-responders than responders [median BF coefficient of variation (CV) 0.91 vs. 0.51 respectively, odds ratio (OR) 6.8 per one standard deviation (1-SD) increase, P = 0.047; median PS CV 1.6 vs. 0.68, OR 3.9 per 1-SD increase, P = 0.047; and median BV CV 0.75 vs. 0.54, OR = 4.0 per 1-SD increase, P = 0.047]. Baseline BV mean in tumor center was lower in non-responders than responders (median BV mean: 0.74 vs. 2.9 ml/100 g respectively, OR 0.28 per 1-SD increase, P = 0.047).

CONCLUSION

For patients with PDAC receiving neoadjuvant therapy, lower and more heterogeneous perfusion parameters correlated with an unfavorable response to therapy. Such quantitative information can be acquired utilizing a comprehensive protocol interleaving perfusion CT acquisition with standard of care multiphase CT scans using a single contrast injection, which could be used to identify surgical candidates and predict outcome.

Quantitative CT perfusion imaging in patients with pancreatic cancer: a systematic review

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related death with a 5-year survival rate of 10%. Quantitative CT perfusion (CTP) can provide additional diagnostic information compared to the limited accuracy of the current standard, contrast-enhanced CT (CECT). This systematic review evaluates CTP for diagnosis, grading, and treatment assessment of PDAC. The secondary goal is to provide an overview of scan protocols and perfusion models used for CTP in PDAC. The search strategy combined synonyms for 'CTP' and 'PDAC.' Pubmed, Embase, and Web of Science were systematically searched from January 2000 to December 2020 for studies using CTP to evaluate PDAC. The risk of bias was assessed using QUADAS-2. 607 abstracts were screened, of which 29 were selected for full-text eligibility. 21 studies were included in the final analysis with a total of 760 patients. All studies comparing PDAC with non-tumorous parenchyma found significant CTP-based differences in blood flow (BF) and blood volume (BV). Two studies found significant differences between pathological grades. Two other studies showed that BF could predict neoadjuvant treatment response. A wide variety in kinetic models and acquisition protocol was found among included studies. Quantitative CTP shows a potential benefit in PDAC diagnosis and can serve as a tool for pathological grading and treatment assessment; however, clinical evidence is still limited. To improve clinical use, standardized acquisition and reconstruction parameters are necessary for interchangeability of the perfusion parameters.

Resectable and Borderline Resectable Pancreatic Ductal Adenocarcinoma: Role of the Radiologist and Oncologist in the Era of Precision Medicine

The incidence and mortality of pancreatic ductal adenocarcinoma are growing over time. The management of patients with pancreatic ductal adenocarcinoma involves a multidisciplinary team, ideally involving experts from surgery, diagnostic imaging, interventional endoscopy, medical oncology, radiation oncology, pathology, geriatric medicine, and palliative care. An adequate staging of pancreatic ductal adenocarcinoma and re-assessment of the tumor after neoadjuvant therapy allows the multidisciplinary team to choose the most appropriate treatment for the patient. This review article discusses advancement in the molecular basis of pancreatic ductal adenocarcinoma, diagnostic tools available for staging and tumor response assessment, and management of resectable or borderline resectable pancreatic cancer.