Imaging-based tumor treatment response evaluation: review of conventional, new, and emerging concepts

Variability of HCC Tumor Diameter and Density Measurements on Dynamic Contrast-Enhanced Computed Tomography

PURPOSE

In cancers imaged using contrast-enhanced protocols, such as hepatocellular carcinoma (HCC), formal guidelines rely on measurements of lesion size (in mm) and radiographic density (in Hounsfield units [HU]) to evaluate response to treatment. However, the variability of these measurements across different contrast enhancement phases remains poorly understood. This limits the ability of clinicians to discern whether measurement changes are accurate.

METHODS

In this study, we investigated the variability of maximal lesion diameter and mean lesion density of HCC lesions on CT scans across four different contrast enhancement phases: non-contrast-enhanced phase (NCE), early arterial phase (E-AP), late arterial phase (L-AP), and portal venous phase (PVP). HCC lesions were independently segmented by two expert radiologists. For each pair of a lesion's scan timepoints, one was selected randomly as the baseline measurement and the other as the repeat measurement. Both absolute and relative differences in measurements were calculated, as were the coefficients of variance (CVs). Analysis was further stratified by both contrast enhancement phase and lesion diameter.

RESULTS

Lesion diameter was found to have a CV of 5.11% (95% CI: 4.20-6.01%). About a fifth of the measurement's relative changes were greater than 10%. Although there was no significant difference in diameter measurements across different phases, there was a significant negative correlation (R = -0.303, p-value = 0.030) between lesion diameter and percent difference in diameter measurement. Lesion density measurements varied significantly across all phases, with the greatest relative difference of 47% in the late arterial phase and a CV of 22.84% (21.48-24.20%). The overall CV for lesion density measurements was 26.19% (24.66-27.72%).

CONCLUSIONS

Changes in tumor diameter measurements within 10% may simply be due to variability, and lesion density is highly sensitive to contrast timing. This highlights the importance of paying attention to these two variables when evaluating tumor response in both clinical trials and practice.

Commentary: Volumetry for Lung Nodule Assessment

See Article page 51.

Integration of Next-Generation Sequencing in the Surgical Management of Colorectal Liver Metastasis

Hepatic resection remains the treatment of choice for colorectal liver metastases. The advancement of surgical technique and use of perioperative systemic therapy has expanded the number and complexity of patients eligible for surgical resection. In recent years, investigation into gene mutations, such as RAS/RAF pathway, have led to targeted therapies that have significantly improved outcomes. Next-generation sequencing allows analysis of large number of genes that may have potential prognostic relevance in the clinical setting. This review summarizes the current applications of next-generation sequencing technology in metastatic colorectal cancer, focusing on its prognostic implications on patient management.

Prediction of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer by using a deep learning model with 18F-FDG PET/CT

OBJECTIVES

The aim of the study is 18F-FDG PET/CT imaging by using deep learning method are predictive for pathological complete response pCR after Neoadjuvant chemotherapy (NAC) in locally advanced breast cancer (LABC).

INTRODUCTION

NAC is the standard treatment for locally advanced breast cancer (LABC). Pathological complete response (pCR) after NAC is considered a good predictor of disease-free survival (DFS) and overall survival (OS).Therefore, there is a need to develop methods that can predict the pCR at the time of diagnosis.

METHODS

This article was designed as a retrospective chart study.For the convolutional neural network model, a total of 355 PET/CT images of 31 patients were used. All patients had primary breast surgery after completing NAC.

RESULTS

Pathological complete response was obtained in a total of 9 patients. The study results show that our proposed deep convolutional neural networks model achieved a remarkable success with an accuracy of 84.79% to predict pathological complete response.

CONCLUSION

It was concluded that deep learning methods can predict breast cancer treatment.

Compression OCT-elastography combined with speckle-contrast analysis as an approach to the morphological assessment of breast cancer tissue

Currently, optical biopsy technologies are being developed for rapid and label-free visualization of biological tissue with micrometer-level resolution. They can play an important role in breast-conserving surgery guidance, detection of residual cancer cells, and targeted histological analysis. For solving these problems, compression optical coherence elastography (C-OCE) demonstrated impressive results based on differences in the elasticity of different tissue constituents. However, sometimes straightforward C-OCE-based differentiation is insufficient because of the similar stiffness of certain tissue components. We present a new automated approach to the rapid morphological assessment of human breast cancer based on the combined usage of C-OCE and speckle-contrast (SC) analysis. Using the SC analysis of structural OCT images, the threshold value of the SC coefficient was established to enable the separation of areas of adipose cells from necrotic cancer cells, even if they are highly similar in elastic properties. Consequently, the boundaries of the tumor bed can be reliably identified. The joint analysis of structural and elastographic images enables automated morphological segmentation based on the characteristic ranges of stiffness (Young's modulus) and SC coefficient established for four morphological structures of breast-cancer samples from patients post neoadjuvant chemotherapy (residual cancer cells, cancer stroma, necrotic cancer cells, and mammary adipose cells). This enabled precise automated detection of residual cancer-cell zones within the tumor bed for grading cancer response to chemotherapy. The results of C-OCE/SC morphometry highly correlated with the histology-based results (r =0.96-0.98). The combined C-OCE/SC approach has the potential to be used intraoperatively for achieving clean resection margins in breast cancer surgery and for performing targeted histological analysis of samples, including the evaluation of the efficacy of cancer chemotherapy.

Evaluation of response to stereotactic body radiation therapy for nonsmall cell lung cancer: PET response criteria in solid tumors versus response evaluation criteria in solid tumors

OBJECTIVE

Recommendations for surveillance after stereotactic body radiation therapy (SBRT) for early-stage nonsmall cell lung cancer (NSCLC) are not well defined. Recently, PET response criteria in solid tumors (PERCIST) have been proposed as a new standardized method to assess radiotherapeutic response both quantitatively and metabolically. The aim of this study was to evaluate therapeutic response following SBRT in early-stage NSCLC patients by comparing PERCIST with the currently widely used RECIST.

MATERIALS AND METHODS

Forty-nine patients with early-stage NSCLC who had been prescribed SBRT were studied. Responses of lesion were evaluated using CT and 18F-FDG PET according to the RECIST and PERCIST methods. PET-CT scans were obtained before SBRT and 3-6 months after SBRT. Associations between overall survival (OS) and clinicopathologic results (histology, tumor location, tumor size, lymphatic invasion, clinical stage, and radiotherapeutic responses in RECIST and PERCIST) were statistically analyzed. The median patient follow-up was 30 months.

RESULTS

Thirteen patients had stage IA, 9 stage IB, 10 stage IIA, and 17 stage IIB biopsy-proven NSCLC. Three-year OS was 79.6%. CT scans indicated three regional recurrences. PET-CT/chest indicated three regional recurrences and distant metastasis. Significant differences were observed in response classification between RECIST and PERCIST (Wilcoxon signed-rank test, P = 0.0041). Univariate analysis showed that clinical stage, RECIST, and PERCIST were significant factors associated with OS, whereas by multivariate analysis PERCIST was the only predictor of OS. SMD, PMD/PMR, and CMR in PERCIST criteria were indicative of a 9.900-fold increase in the risk of OS in early NSCLC patients [risk ratio, 9.900 (95% CI, 1.040-21.591); P = 0.001].

CONCLUSION

RECIST based on the anatomic size reduction rate did not demonstrate the correlation between radiotherapeutic response and prognosis in patients with early-stage NSCLC receiving SBRT. However, PERCIST was shown as the strongest independent predictor of outcomes. PERCIST might be considered more suitable for the evaluation of NSCLC tumor response to SBRT than RECIST.

Quantifying invasiveness of clinical stage IA lung adenocarcinoma with computed tomography texture features

OBJECTIVES

The study objectives were to establish and validate a nomogram for pathological invasiveness prediction in clinical stage IA lung adenocarcinoma and to help identify those potentially unsuitable for sublobar resection-based computed tomography texture features.

METHOD

Patients with clinical stage IA lung adenocarcinoma who underwent surgery at Guangdong Provincial People's Hospital between January 2015 and October 2018 were retrospectively reviewed. All surgically resected nodules were pathologically classified into less-invasive and invasive cohorts. Each nodule was manually segmented, and its computerized texture features were extracted. Clinicopathological and computed tomographic texture features were compared between 2 cohorts. A nomogram for distinguishing the pathological invasiveness was established and validated.

RESULTS

Among 428 enrolled patients, 249 were diagnosed with invasive pathological subtypes. Smoking status (odds ratio, 2.906; 95% confidence interval, 1.285-6.579; P = .011), mean computed tomography attenuation value (odds ratio, 1.005, 95% confidence interval, 1.002-1.007; P < .001), and entropy (odds ratio, 8.536, 95% confidence interval, 3.478-20.951; P < .001) were identified as independent predictors for pathological invasiveness by multivariate logistics regression analysis. The nomogram showed good calibration (P = .182) with an area under the curve of 0.849 when validated with testing set data. Decision curve analysis indicated the potentially clinical usefulness of the model with respect to treat-all or treat-none scenario. Compared with intraoperative frozen-section, the nomogram performed better in pathological invasiveness diagnosis (area under the curve, 0.815 vs 0.670; P = .00095).

CONCLUSIONS

We established and validated a nomogram to compute the probability of invasiveness of clinical stage IA lung adenocarcinoma with great calibration, which may contribute to decisions related to resection extent.

Evaluation of Response to Immune Checkpoint Inhibitors Using a Radiomics, Lesion-Level Approach

Conventional methods to determine the response to immune checkpoint inhibitors (ICIs) are limited by the unique responses to an ICI. We performed a radiomics approach for all measurable lesions to identify radiomic variables that could distinguish hyperprogressive disease (HPD) on baseline CT scans and classify a dissociated response (DR). One hundred and ninety-six patients with advanced lung cancer, treated with ICI monotherapy, who underwent at least three CT scans, were retrospectively enrolled. For all 621 measurable lesions, HPDv was determined from baseline CT scans using the tumor growth kinetics (TGK) ratio, and radiomics features were extracted. Multivariable logistic regression analysis of radiomics features was performed to discriminate DR. Radiomics features that significantly discriminated HPDv on baseline CT differed according to organ. Of the 196 patients, 54 (27.6%) had a DR and 142 (72.4%) did not have a DR. Overall survival in the group with a DR was significantly inferior to that in the group without a DR (log rank test, p = 0.04). Our study shows that lesion-level analysis using radiomics features has great potential for discriminating HPDv and understanding heterogeneous tumor progression, including a DR, after ICI treatment.

Role of the alpha-fetoprotein response in immune checkpoint inhibitor-based treatment of patients with hepatocellular carcinoma

PURPOSE

The dynamics of serum alpha-fetoprotein (AFP) level have been found to be a useful predictor of therapeutic responsiveness in patients with hepatocellular carcinoma (HCC). We evaluated whether AFP changes were able to accurately reflect imaging-based responses and predict prognosis in patients receiving therapies including immune-checkpoint inhibitors (ICIs).

METHODS

A total of 108 HCC patients with baseline serum AFP ≥ 20 ng/mL who received ICI-based treatment were included. We evaluated AFP-based responses, coupled with radiographic responses by RECIST, at 6-10 (time-point 1, TP1) and 14-18 weeks (time-point 2, TP2) of therapy in terms of the change of AFP from baseline, with a > 20% decrease or increase in level corresponding to the AFP response and progression, respectively. We examined the correlations between AFP and imaging-based responses, and the prognostic implications of the AFP-based measure.

RESULTS

Based on AFP change, there were 24 and 20 responders and 74 and 24 progressors at TP1 and TP2, respectively. The AFP responders yielded radiological objective responses in 90.9% (10/11) and 93.8% (15/16) of the cases at TP1 and TP2, respectively, compared with only 1.4% and none, respectively, of the AFP progressors at the corresponding times. The agreement between progression by RECIST and increased AFP level at the two time-points was 93.8% and 95.0%, respectively. The accuracy of the AFP-based criterion for predicting radiologic response/progression was comparable at TP1 and TP2. Both "AFP responder" and "AFP progressor" at TP1 or TP2 independently predicted the overall survival of patients (adjusted hazard ratios [95% confidence intervals], 0.360 [0.174-0.743] and 0.315 [0.117-0.850]; and 2.525 [1.362-4.679] and 3.908 [1.563-9.769], respectively).

CONCLUSION

Our study suggests that on-treatment AFP changes can complement imaging findings and provide prognostic information for evaluating patients with AFP-producing HCC treated with ICI-based regimens.

Imaging biomarkers for evaluating tumor response: RECIST and beyond

Response Evaluation Criteria in Solid Tumors (RECIST) is the gold standard for assessment of treatment response in solid tumors. Morphologic change of tumor size evaluated by RECIST is often correlated with survival length and has been considered as a surrogate endpoint of therapeutic efficacy. However, the detection of morphologic change alone may not be sufficient for assessing response to new anti-cancer medication in all solid tumors. During the past fifteen years, several molecular-targeted therapies and immunotherapies have emerged in cancer treatment which work by disrupting signaling pathways and inhibited cell growth. Tumor necrosis or lack of tumor progression is associated with a good therapeutic response even in the absence of tumor shrinkage. Therefore, the use of unmodified RECIST criteria to estimate morphological changes of tumor alone may not be sufficient to estimate tumor response for these new anti-cancer drugs. Several studies have reported the low reliability of RECIST in evaluating treatment response in different tumors such as hepatocellular carcinoma, lung cancer, prostate cancer, brain glioma, bone metastasis, and lymphoma. There is an increased need for new medical imaging biomarkers, considering the changes in tumor viability, metabolic activity, and attenuation, which are related to early tumor response. Promising imaging techniques, beyond RECIST, include dynamic contrast-enhanced computed tomography (CT) or magnetic resonance imaging (MRI), diffusion-weight imaging (DWI), magnetic resonance spectroscopy (MRS), and ¹⁸ F-fluorodeoxyglucose (FDG) positron emission tomography (PET). This review outlines the current RECIST with their limitations and the new emerging concepts of imaging biomarkers in oncology.

Imaging Beyond Seeing: Early Prognosis of Cancer Treatment

Assessing cancer response to therapeutic interventions has been realized as an important course to early predict curative efficacy and treatment outcomes due to tumor heterogeneity. Compared to the traditional invasive tissue biopsy method, molecular imaging techniques have fundamentally revolutionized the ability to evaluate cancer response in a spatiotemporal manner. The past few years has witnessed a paradigm shift on the efforts from manufacturing functional molecular imaging probes for seeing a tumor to a vantage stage of interpreting the tumor response during different treatments. This review is to stand by the current development of advanced imaging technologies aiming to predict the treatment response in cancer therapy. Special interest is placed on the systems that are able to provide rapid and noninvasive assessment of pharmacokinetic drug fates (e.g., drug distribution, release, and activation) and tumor microenvironment heterogeneity (e.g., tumor cells, macrophages, dendritic cells (DCs), T cells, and inflammatory cells). The current status, practical significance, and future challenges of the emerging artificial intelligence (AI) technology and machine learning in the applications of medical imaging fields is overviewed. Ultimately, the authors hope that this review is timely to spur research interest in molecular imaging and precision medicine.

Quantitative imaging decision support (QIDSTM) tool consistency evaluation and radiomic analysis by means of 594 metrics in lung carcinoma on chest CT scan

Objective:

To evaluate the consistency of the quantitative imaging decision support (QIDS^TM) tool and radiomic analysis using 594 metrics in lung carcinoma on chest CT scan.

Materials and Methods:

We included, retrospectively, 150 patients with histologically confirmed lung cancer who underwent chemotherapy and baseline and follow-ups CT scans. Using the QIDS^TM platform, 3 radiologists segmented each lesion and automatically collected the longest diameter and the density mean value. Inter-observer variability, Bland Altman analysis and Spearman’s correlation coefficient were performed. QIDS^TM tool consistency was assessed in terms of agreement rate in the treatment response classification. Kruskal Wallis test and the least absolute shrinkage and selection operator (LASSO) method with 10-fold cross validation were used to identify radiomic metrics correlated with lesion size change.

Results:

Good and significant correlation was obtained between the measurements of largest diameter and of density among the QIDS^TM tool and the radiologists measurements. Inter-observer variability values were over 0.85. HealthMyne QIDS^TM tool quantitative volumetric delineation was consistent and matched with each radiologist measurement considering the RECIST classification (80-84%) while a lower concordance among QIDS^TM and the radiologists CHOI classification was observed (58-63%). Among 594 extracted metrics, significant and robust predictors of RECIST response were energy, histogram entropy and uniformity, Kurtosis, coronal long axis, longest planar diameter, surface, Neighborhood Grey-Level Different Matrix (NGLDM) dependence nonuniformity and low dependence emphasis as Volume, entropy of Log(2.5 mm), wavelet energy, deviation and root man squared.

Conclusion:

In conclusion, we demonstrated that HealthMyne quantitative volumetric delineation was consistent and that several radiomic metrics extracted by QIDS^TM were significant and robust predictors of RECIST response.

Long-term progression-free survival in a patient with advanced non-small-cell lung cancer treated with low-dose gefitinib and traditional herbal medicine: A case report

RATIONALE

Gefitinib is a first-line palliative chemotherapy drug used to treat advanced non-small-cell lung cancer (NSCLC) in patients who have an epidermal growth factor receptor (EGFR) mutation. However, approximately two-thirds of NSCLC patients with EGFR-tyrosine kinase inhibitor experience dermatological toxicity. Cutaneous toxicity is usually not life threatening but can necessitate modification or discontinuation of medication in severe cases. In this case, despite a reduction in the dose of gefitinib due to side effects, combined treatment with modified Bojungikki-tang (BJKIT) increased progression-free survival (PFS) in an advanced NSCLC patient.

PATIENT CONCERNS

An 83-year-old Asian woman presented with chief complaints of chronic cough, dyspnea, weight loss, and anorexia.

DIAGNOSES

The patient was diagnosed with stage IV NSCLC (T2aN3M1), adenocarcinoma with metastasis to the lymph node, brain, and bone based on image scan and biopsy. An EGFR deletion was detected in exon 19.

INTERVENTIONS

The patient was treated with gefitinib (250 mg/d) and traditional herbal medicine, modified Bojungikki-tang (BJIKT). However, after 1 year of combination therapy, gefitinib was tapered down to once per week while modified BJIKT was maintained.

OUTCOMES

A partial response was achieved, but after 3 months severe papulopustular skin rashes developed and became aggravated with time. Thus, the gefitinib dose was reduced. However, the PFS has been maintained for approximately 78 months.

LESSONS

Despite the reduction in gefitinib dose due to side effects, the combined treatment of gefitinib and the modified BJIKT has maintained a PFS of over 78 months, indicating that modified BJIKT enhanced the anti-cancer effect of gefitinib in a patient with advanced NSCLC harboring the EFGR mutation, and may have delayed acquired resistance, the main limitation on the efficacy of gefitinib. Further investigations including clinical trials are needed to confirm these effects.

Texture analysis for chemotherapy response evaluation in osteosarcoma using MR imaging

The efficacy of MRI-based statistical texture analysis (TA) in predicting chemotherapy response among patients with osteosarcoma was assessed. Forty patients (male: female = 31:9; age = 17.2 ± 5.7 years) with biopsy-proven osteosarcoma were analyzed in this prospective study. Patients were scheduled for three cycles of neoadjuvant chemotherapy (NACT) and diffusion-weighted MRI acquisition at three time points: at baseline (t0), after the first NACT (t1) and after the third NACT (t2) using a 1.5 T scanner. Eight patients (nonsurvivors) died during NACT while 34 patients (survivors) completed the NACT regimen followed by surgery. Histopathological evaluation was performed in the resected tumor to assess NACT response (responder [≤50% viable tumor] and nonresponder [>50% viable tumor]) and revealed nonresponder: responder = 20:12. Apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) parameters, diffusion coefficient (D), perfusion coefficient (D*) and perfusion fraction (f) were evaluated. A total of 25 textural features were evaluated on ADC, D, D* and f parametric maps and structural T1-weighted (T1W) and T2-weighted (T2W) images in the entire tumor volume using 3D TA methods gray-level cooccurrence matrix (GLCM), neighborhood gray-tone-difference matrix (NGTDM) and run-length matrix (RLM). Receiver-operating-characteristic curve analysis was performed on the selected textural feature set to assess the role of TA features (a) as marker(s) of tumor aggressiveness leading to mortality at baseline and (b) in predicting the NACT response among survivors in the course of treatment. Findings showed that the NGTDM features coarseness, busyness and strength quantifying tumor heterogeneity in D, D* and f maps and T1W and T2W images were useful markers of tumor aggressiveness in identifying the nonsurvivor group (area-under-the-curve [AUC] = 0.82-0.88) at baseline. The GLCM features contrast and correlation, NGTDM features contrast and complexity and RLM feature short-run-low-gray-level-emphasis quantifying homogeneity/terogeneity in tumor were effective markers for predicting chemotherapeutic response using D (AUC = 0.80), D* (AUC = 0.80) and T2W (AUC = 0.70) at t0, and D* (AUC = 0.80) and f (AUC = 0.70) at t1. 3D statistical TA features might be useful as imaging-based markers for characterizing tumor aggressiveness and predicting chemotherapeutic response in patients with osteosarcoma.

Integrating Liquid Biopsy and Radiomics to Monitor Clonal Heterogeneity of EGFR-Positive Non-Small Cell Lung Cancer

Background

EGFR-positive Non-small Cell Lung Cancer (NSCLC) is a dynamic entity and tumor progression and resistance to tyrosine kinase inhibitors (TKIs) arise from the accumulation, over time and across different disease sites, of subclonal genetic mutations. For instance, the occurrence of EGFR T790M is associated with resistance to gefitinib, erlotinib, and afatinib, while EGFR C797S causes osimertinib to lose activity. Sensitive technologies as radiomics and liquid biopsy have great potential to monitor tumor heterogeneity since they are both minimally invasive, easy to perform, and can be repeated over patient’s follow-up, enabling the extraction of valuable information. Yet, to date, there are no reported cases associating liquid biopsy and radiomics during treatment.

Case presentation

In this case series, seven patients with metastatic EGFR-positive NSCLC have been monitored during target therapy. Plasma-derived cell free DNA (cfDNA) was analyzed by a digital droplet PCR (ddPCR), while radiomic analyses were performed using the validated LifeX® software on computed tomography (CT)-images. The dynamics of EGFR mutations in cfDNA was compared with that of radiomic features. Then, for each EGFR mutation, a radiomic signature was defines as the sum of the most predictive features, weighted by their corresponding regression coefficients for the least absolute shrinkage and selection operator (LASSO) model. The receiver operating characteristic (ROC) curves were computed to estimate their diagnostic performance. The signatures achieved promising performance on predicting the presence of EGFR mutations (R² = 0.447, p <0.001 EGFR activating mutations R² = 0.301, p = 0.003 for T790M; and R² = 0.354, p = 0.001 for activating plus resistance mutations), confirmed by ROC analysis.

Conclusion

To our knowledge, these are the first cases to highlight a potentially promising strategy to detect clonal heterogeneity and ultimately identify patients at risk of progression during treatment. Together, radiomics and liquid biopsy could detect the appearance of new mutations and therefore suggest new therapeutic management.

A patent review of anticancer glucocorticoid receptor modulators (2014-present)

Introduction: Natural and synthetic glucocorticoids are widely employed in different diseases, among which are hematological and solid tumors. Their use is however associated with a number of serious side effects and by the occurrence of resistance. With the aim of separating their gene transactivating effect, more linked to side effects, from transrepressive properties, associated with therapeutic efficacy, a number of selective glucocorticoid modulators have been identified.Areas covered: This review summarizes the patent applications from 2014 to present in the field of selective glucocorticoid receptor modulators employed in cancer therapy. Only few patents have been identified, that concern the identification of new molecules or the method of use of already patented compounds. In addition, a discussion of the mechanism of action of these compounds is included.Expert opinion: Only a very limited number of patents have been applied that concern selective glucocorticoid receptor modulators and their use in cancer. Biological information is scarce for most of these patents; more research is necessary in this field in particular concerning clinical data in order to understand whether it is actually possible to improve the efficacy and therapeutic index of these compounds in cancer therapy.

Imaging and clinical correlates with regorafenib in metastatic colorectal cancer

In colorectal cancer (CRC), imaging is important in determining tumor stage, selecting treatment strategies, and in assessing response to therapy. However, some challenges remain with established imaging techniques, such as computed tomography, and with some commonly used response criteria, such as Response Evaluation Criteria in Solid Tumors, which measures change in size of several target lesions instead of change in tumor morphology or metabolic function. In addition, these assessments are not typically conducted until after 8 weeks of treatment, meaning that potential non-responders are often not identified in a timely manner. Regorafenib, an oral tyrosine kinase inhibitor indicated for the treatment of metastatic CRC, blocks the activity of several protein kinases involved in angiogenesis, oncogenesis, metastasis, and tumor immunity. Timely differentiation of regorafenib responders from non-responders using appropriate imaging techniques that recognize not only changes in tumor size but also changes in tumor density or vasculature, may reduce unnecessary drug-related toxicity in patients who are unlikely to respond to treatment. This review discusses the latest developments in computed tomography, magnetic resonance imaging, and positron emission tomography tumor imaging modalities, and how these aid in identifying patients with metastatic CRC who are responders or non-responders to regorafenib treatment.

Radio-Pathological Correlations in Patients with Liver Metastases for Colorectal Cancer

BACKGROUND

Colorectal cancer (CRC) is the most frequent gastrointestinal cancer. The liver is the organ most commonly affected by CRC metastases. Synchronous CRC liver metastases (CRCLM) are present in 15-25% at diagnosis, and metastases are confined to the liver in 70-80% of these cases. The aim of the present study was to investigate the existence of significant correlations between the pathological features and computed tomography scan morpho-densitometric findings.

SUMMARY

A retrospective study of prospectively collected data has been performed; all patients underwent curative-intent hepatic resection from January 2004 to December 2012 and had histologically confirmed CRCLM. Key Messages: Thirty-four (57%) patients were males; the mean age was 64.4 (±10.2) years. Statistically significant differences have been found with the percentages of intra-tumoral fibrosis (p = 0.038) and necrosis (p = 0.007); the values of fibrosis are higher in the absence of a peri-lesional ring, while those of necrosis are higher in the presence of a peri-lesional ring.There was a correlation between the histopathological response to treatments and the global attenuation levels observed in the computed tomography scan of CRCLM. Furthermore, the presence of a radiologically evidenced peripheral ring was associated with the amount of viable tumor cells in the periphery of the tumor, and with responses predominated by necrosis. More studies are needed to clarify the radiological and histological correlation and to be able to better select patients who are going to undergo surgery.

In vivo assessment of functional and morphological alterations in tumors under treatment using OCT-angiography combined with OCT-elastography

Emerging methods of anti-tumor therapies require new approaches to tumor response evaluation, especially enabling label-free diagnostics and in vivo utilization. Here, to assess the tumor early reaction and predict its long-term response, for the first time we apply in combination the recently developed OCT extensions - optical coherence angiography (OCA) and compressional optical coherence elastography (OCE), thus enabling complementary functional/microstructural tumor characterization. We study two vascular-targeted therapies of different types, (1) anti-angiogenic chemotherapy (ChT) and (2) photodynamic therapy (PDT), aimed to indirectly kill tumor cells through blood supply injury. Despite different mechanisms of anti-angiogenic action for ChT and PDT, in both cases OCA demonstrated high sensitivity to blood perfusion cessation. The new method of OCE-based morphological segmentation revealed very similar histological structure alterations. The OCE results showed high correlation with conventional histology in evaluating percentages of necrotic and viable tumor zones. Such possibilities make OCE an attractive tool enabling previously inaccessible in vivo monitoring of individual tumor response to therapies without taking multiple biopsies.

Diffusion-Weighted MR Imaging of Primary and Secondary Lung Cancer: Predictive Value for Response to Transpulmonary Chemoembolization and Transarterial Chemoperfusion

PURPOSE

To examine predictive value of apparent diffusion coefficient (ADC) in diffusion-weighted imaging (DWI) for response of patients with primary and secondary lung neoplasms undergoing transpulmonary chemoembolization (TPCE) and transarterial chemoperfusion (TACP) treatment.

MATERIALS AND METHODS

Thirty-one patients (mean age ± SD 64 ± 12.4 y) with 42 lung target lesions (13 primary and 29 secondary) underwent DWI and subsequent ADC analysis on a 1.5T MR imaging scanner before and 30.3 days ± 6.4 after first session of TPCE or TACP. After 3.1 treatment sessions ± 1.4 performed in 2- to 4-week intervals, morphologic response was analyzed by comparing tumor diameter and volume before and after treatment on unenhanced T1-weighted MR images. On a per-lesion basis, response was classified according to Response Evaluation Criteria In Solid Tumors.

RESULTS

Threshold ADC increase of 20.7% indicated volume response with 88% sensitivity and 78% specificity (area under the curve [AUC] = 0.84). Differences between ADC changes in volume response groups were significant (P = .002). AUC for volume response predicted by ADC before treatment was 0.77. Median ADC before treatment and mean ADC change were 1.09 × 10-3 mm2/second and 0.36 × 10-3 mm2/second ± 0.23, 1.45 × 10-3 mm2/second and 0.14 × 10-3 mm2/second ± 0.16, and 1.30 × 10-3 mm2/second and 0.06 × 10-3 mm2/second ± 0.19 in partial response, stable disease, and progressive disease groups. In primary lung cancer lesions, strong negative correlation of ADC change with change in diameter (ρ = -.87, P < .001) and volume (ρ = -.66, P = .016) was found. In metastases, respective correlation coefficients were ρ = -.18 (P = .356) and ρ = -.35 (P = .061).

CONCLUSIONS

ADC quantification shows considerable diagnostic value for predicting response and monitoring TPCE and TACP treatment of patients with primary and secondary lung neoplasms.

Measurement Variability in Treatment Response Determination for Non-Small Cell Lung Cancer: Improvements Using Radiomics

Multimodality imaging measurements of treatment response are critical for clinical practice, oncology trials, and the evaluation of new treatment modalities. The current standard for determining treatment response in non-small cell lung cancer (NSCLC) is based on tumor size using the RECIST criteria. Molecular targeted agents and immunotherapies often cause morphological change without reduction of tumor size. Therefore, it is difficult to evaluate therapeutic response by conventional methods. Radiomics is the study of cancer imaging features that are extracted using machine learning and other semantic features. This method can provide comprehensive information on tumor phenotypes and can be used to assess therapeutic response in this new age of immunotherapy. Delta radiomics, which evaluates the longitudinal changes in radiomics features, shows potential in gauging treatment response in NSCLC. It is well known that quantitative measurement methods may be subject to substantial variability due to differences in technical factors and require standardization. In this review, we describe measurement variability in the evaluation of NSCLC and the emerging role of radiomics.

Diffusion-weighted MR imaging diagnostic merits in the post-therapeutic assessment of musculoskeletal soft tissue sarcoma

Background

The purpose of the study is assessing the diagnostic merits of diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping in evaluating tumor response to chemo-radiotherapy. The study included 36 patients with soft tissue sarcoma, who received chemo/radiotherapy. Tumor longest dimension according to response evaluation criteria in solid tumors 1.1 (RECIST 1.1), the longest dimension of the contrast-enhanced portion of the tumor according to modified response evaluation criteria in solid tumors: (mRECIST), the tumor volume (VOL) (cm3), and DWI with ADC values were recorded.

Results

ADC values in the non-progressive group were higher than those of the progressive group after neoadjuvant treatment (1.63 ± 0.42 vs. 1.24 ± 0.35) with (p < 0.005). ADC variations in the non-progressive group were higher than those of the progressive group (27.09 ± 48.09 vs. − 3.08 ± 23.5)% with (p < 0.05). ADC values after neoadjuvant treatment were negatively related to tumor volume variations (VOL%) after neoadjuvant treatment. ADC variations (ADC%) were inversely correlated with morphologic changes, regardless of the effectiveness of anticancer therapy expressed as changes in tumor size based on (RECIST, mRECIST, and three-dimensional volumetric assessment). An increase in the ADC value was not always associated with a reduction of tumor volume.

Conclusion

Quantitative DW imaging after neoadjuvant therapy provides added value in determining treatment response in soft tissue sarcomas. Therapeutic response to neoadjuvant therapy can be underestimated using RECIST 1.1; therefore, the mRECIST should also be considered.

Clinical impact of variability on CT radiomics and suggestions for suitable feature selection: a focus on lung cancer

BACKGROUND

Radiomics suffers from feature reproducibility. We studied the variability of radiomics features and the relationship of radiomics features with tumor size and shape to determine guidelines for optimal radiomics study.

METHODS

We dealt with 260 lung nodules (180 for training, 80 for testing) limited to 2 cm or less. We quantified how voxel geometry (isotropic/anisotropic) and the number of histogram bins, factors commonly adjusted in multi-center studies, affect reproducibility. First, features showing high reproducibility between the original and isotropic transformed voxel settings were identified. Second, features showing high reproducibility in various binning settings were identified. Two hundred fifty-two features were computed and features with high intra-correlation coefficient were selected. Features that explained nodule status (benign/malignant) were retained using the least absolute shrinkage selector operator. Common features among different settings were identified, and the final features showing high reproducibility correlated with nodule status were identified. The identified features were used for the random forest classifier to validate the effectiveness of the features. The properties of the uncalculated feature were inspected to suggest a tentative guideline for radiomics studies.

RESULTS

Nine features showing high reproducibility for both the original and isotropic voxel settings were selected and used to classify nodule status (AUC 0.659-0.697). Five features showing high reproducibility among different binning settings were selected and used in classification (AUC 0.729-0.748). Some texture features are likely to be successfully computed if a nodule was larger than 1000 mm3.

CONCLUSIONS

Features showing high reproducibility among different settings correlated with nodule status were identified.

Application of computed tomography-based radiomics signature analysis in the prediction of the response of small cell lung cancer patients to first-line chemotherapy

The aim of the present study was to investigate the utility of a computed tomography (CT)-based radiomics signature for the early prediction of the tumor response of small cell lung cancer (SCLC) patients to chemotherapy. A dataset including 92 patients from a clinical trial was retrospectively assembled. All of the patients received the standard first-line regimen of etoposide and cisplatin. According to the Response Evaluation Criteria in Solid Tumors 1.1, the patients were divided into two groups: Response and no response groups. A total of 21 radiomics features were extracted from CT images prior to and after two cycles of chemotherapy and a radiomics signature was constructed via a binary logistic regression model. The area under the receiver operating characteristics curve (AUC) was determined to evaluate the performance of the radiomics signature to predict the response to chemotherapy. The clinicopathological factors associated with chemotherapy in patients with SCLC were also evaluated, and a predictive model was established using a binary logistic regression analysis. The 21 radiological features were used to establish a radiomics signature that was significantly associated with the efficacy of SCLC chemotherapy (P<0.05). The performance of the radiomics signature to predict the chemotherapy efficacy (AUC=0.797) was better than that of the model using clinicopathological parameters (AUC=0.670). Therefore, the present study demonstrated that radiomics features may be promising prognostic imaging biomarkers to predict the response of SCLC patients to chemotherapy and may thus be utilized to guide appropriate treatment planning.

Computed tomography densitometric study of anti-angiogenic effect of regorafenib in colorectal cancer liver metastasis

Aim: Regorafenib induces radiological changes in liver metastasis among patients with metastatic colorectal cancer (mCRC). The standard criteria used to evaluate solid tumor response (Response Evaluation Criteria in Solid Tumors) may be limited in assessing response to biologic agents with anti-angiogenic action. Patients & methods: A total of 67 hepatic lesions in 32 selected patients were analyzed to evaluate tumor attenuation as measured by Hounsfield unit (HU) and size changes. Results: Following two cycles of regorafenib, tumor HU values decreased in the in 73.1% (49/67) of lesions (average HU changes -25.6%) while tumor size increased in 64.2% (43/67) of them (average size changes +25.4%). Conclusion: The computed tomography density changes evaluation may be an additional tool, in combination with tumor sizing, to evaluate tumor response in patients treated with regorafenib.

Intratumor lactate levels reflect HER2 addiction status in HER2-positive breast cancer

Despite different molecular tumor profiles indicate that human epidermal growth factor receptor 2 (HER2) messenger RNA (mRNA) levels mirror HER2 addiction and trastuzumab benefit in HER2-positive breast cancer (BC), the identification of noninvasive clinical predictors of trastuzumab sensitivity remains an unmet clinical need. In the current study, we investigated whether intratumor lactate levels reflect HER2 addiction and, in turn, trastuzumab susceptibility. Accordingly, the gene expression profiles of transgenic murine BC cell lines expressing the human d16HER2 variant (HER2-addicted) or human full-length HER2 (WTHER2; HER2-nonaddicted) revealed a significant enrichment of glycolysis-related gene pathways in HER2-addicted cells. We studied the metabolic content of 22 human HER2-positive BC by quantitative nuclear magnetic resonance spectroscopy and found that those cases with higher lactate levels were characterized by higher HER2 transcript levels. Moreover, gene expression analyses of HER2-positive BC samples from a TCGA data set revealed a significant enrichment in glycolysis-related pathways in high/HER2-addicted tumors. These data were confirmed by metabolic analyses of human HER2-positive BC cell lines with high or low HER2 transcript levels, which revealed significantly more active glycolytic metabolism in high HER2 transcript than in low HER2 transcript cells. Overall, our results provide evidence for noninvasive intratumor lactate detection as a potential metabolic biomarker of HER2 addiction and trastuzumab response suggesting the possibility to use in vivo imaging to assess lactate levels and, in turn, select HER2-positive BC patients who are more likely to benefit from anti-HER2 treatments.

Response evaluation of giant-cell tumor of bone treated by denosumab: Histogram and texture analysis of CT images

BACKGROUND

This study aimed to compare computed tomography (CT) features, including tumor size and textural and histogram measurements, of giant-cell tumors of bone (GCTBs) before and after denosumab treatment and determine their applicability in monitoring GCTB response to denosumab treatment.

METHODS

This retrospective study included eight patients (male, 3; female, 5; mean age, 33.4 years) diagnosed with GCTB, who had received treatment by denosumab and had undergone pre- and post-treatment non-contrast CT between January 2010 and December 2016. This study was approved by the institutional review board. Pre- and post-treatment size, histogram, and textural parameters of GCTBs were compared by the Wilcoxon signed-rank test. Pathological findings of five patients who underwent surgery after denosumab treatment were evaluated for assessment of treatment response.

RESULTS

Relative to the baseline values, the tumor size had decreased, while the mean attenuation, standard deviation, entropy (all, P = 0.017), and skewness (P = 0.036) of the GCTBs had significantly increased post-treatment. Although the difference was statistically insignificant, the tumors also exhibited increased kurtosis, contrast, and inverse difference moment (P = 0.123, 0.327, and 0.575, respectively) post-treatment. Histologic findings revealed new bone formation and complete depletion or decrease in the number of osteoclast-like giant cells.

CONCLUSION

The histogram and textural parameters of GCTBs changed significantly after denosumab treatment. Knowledge of the tendency towards increased mean attenuation and heterogeneity but increased local homogeneity in post-treatment CT histogram and textural features of GCTBs might aid in treatment planning and tumor response evaluation during denosumab treatment.

Texture analysis of diffusion weighted imaging for the evaluation of glioma heterogeneity based on different regions of interest

The present study aimed to explore the role of texture analysis with apparent diffusion coefficient (ADC) maps based on different regions of interest (ROI) in determining glioma grade. Thirty patients with glioma underwent diffusion-weighted imaging (DWI). ADC values were determined from the following three ROIs: i) whole tumor; ii) solid portion; and iii) peritumoral edema. Texture features were compared between high-grade gliomas (HGGs) and low-grade gliomas (LGGs) using the non-parametric Wilcoxon rank-sum test or the unpaired Student's t-test. Receiver operating characteristic (ROC) curves were constructed to determine the optimum threshold for inhomogeneity values in discrimination of HGGs from LGGs. With a spearman rank correlation model, the aforementioned ADC inhomogeneity values were correlated with the Ki-67 labeling index. With whole tumor ROI, inhomogeneity values proved to be significantly different between HGGs and LGGs (P<0.001). With solid portion ROI, inhomogeneity and median values showed significant difference between HGGs and LGGs (P=0.001 and P=0.043, respectively). With peritumoral edema ROI, entropy and edema volume demonstrated positive results (P=0.016, P<0.001). The whole tumor inhomogeneity parameter performed with better diagnostic accuracy (P=0.048) than selecting the solid portion ROI. The association between inhomogeneity and Ki-67 labeling index was significantly positive in whole tumor and solid portion ROI (R=0.628, P<0.001 and R=0.470, P=0.009). Texture analysis of DWI based on different ROI can provide various significant parameters to evaluate tumor heterogeneity, which were correlated with tumor grade. Particularly, the inhomogeneity value derived from whole tumor ROI provided high diagnostic value and predicting the status of tumor proliferation.

Giant Cell Tumors of the Bone: Changes in Image Features after Denosumab Administration

Purpose:

To assess the clinical importance in the feature change in giant cell tumors of the bone (GCTB) after denosumab treatment, detected by MRI.

Methods:

In 12 patients, MRI and CT of GCTB obtained before and after the treatment retrospectively compared. The tumor size, the signal intensity (SI) ratio between the solid part of the GCTB and muscle, cystic part size, gadolinium enhancement and apparent diffusion coefficient (ADC) value were measured on MRI. The bone formation in the tumor was observed on CT and X-ray.

Results:

The mean number of denosumab injections was 19 ± 10. The follow-up period was up to 2 years. One case showed partial remission, while the other 11 cases were stable. A mean SI ratio on T₂-weighted image statistically significantly decreased from 3.9 to 1.9 after the treatment. A cystic component in the tumor was observed in five cases before the treatment, and the diameter of the cystic part decreased after the treatment in 80% of cases (4/5). All the tumors showed contrast enhancement on T₁-weighted image pre- and post-treatment (11/11). The averaged ADC values were 1.52 × 10⁻³ mm²/s before and 1.44 × 10⁻³ mm²/s after the treatment (P = 0.63). Bone formation in the tumor was observed in 58% of cases (7/12).

Conclusion:

The decrease of SI ratio on T₂-weighted image, shrinkage of cystic part and bone formation should be regarded as the effectiveness of denosumab treatment despite of no substantial change in the tumor size.

Biomarkers and Imaging of Breast Cancer

OBJECTIVE

The goals of this review are to provide background information on the definitions and applications of the general term "biomarker" and to highlight the specific roles of breast imaging biomarkers in research and clinical breast cancer care. A search was conducted of the main electronic biomedical databases (PubMed, Cochrane, Embase, MEDLINE [Ovid], Scopus, and Web of Science). The search was focused on review literature in general radiology and biomedical sciences and on reviews and primary research articles on biomarkers in breast imaging over the 15 years ending in June 2017. The keywords included "biomarker," "trial endpoints," "breast imaging," "breast cancer," "radiomics," and "precision medicine" in the titles and abstracts of the papers.

CONCLUSION

Clinical breast care and breast cancer-related research rely on imaging biomarkers for decision support. In the era of precision medicine and big data, the practice of radiology is likely to change. A closer integration of breast imaging with related biomedical fields and the creation of large integrated and shareable databases of clinical, molecular, and imaging biomarkers should allow the field to continue guiding breast cancer care and research.

Computed tomography perfusion imaging for monitoring transarterial chemoembolization of hepatocellular carcinoma

PURPOSE

To prospectively monitor changes in tumor perfusion of hepatocellular carcinoma (HCC) in response to doxorubicin-eluted bead based transarterial chemoembolization (DEB-TACE) using perfusion-CT (P-CT).

METHODS AND MATERIALS

24 patients (54-79 years) undergoing P-CT before and shortly after DEB-TACE of HCC were prospectively included in this dual-center study. Two readers determined arterial-liver-perfusion (ALP, mL/min/100mL), portal-venous-perfusion (PLP, mL/min/100mL) and the hepatic-perfusion-index (HPI, %) by placing matched regions-of-interests within each HCC before and after DEB-TACE. Imaging follow-up was used to determine treatment response and to distinguish complete from incomplete responders. Performance of P-CT for prediction and early response assessment was determined using receiver-operating-characteristics curve analysis.

RESULTS

Interreader agreement was fair to excellent (ICC, 0.716-0.942). PLP before DEB-TACE was significantly higher in pre-treated vs non-treated lesions (P<0.05). Mean changes of ALP, PLP and HPI from before to after DEB-TACE were -55%, +24% and -27%. ALP and HPI after DEB-TACE were correlating with response-grades (r=0.45/0.48; both, p<0.04), showing an area-under-the-curve (AUC) of 0.74 and 0.80 respectively for identification of complete response.

CONCLUSION

High arterial and low portal-venous perfusion of HCC early after DEB-TACE indicates incomplete response with good diagnostic accuracy.

Cancer Measurement at Ultrasound: State of the Art

Reliable and reproducible tumor measurement is fundamental in the oncologic decision making. In this article, we first highlight the importance of a precise tumor measurement, reviewing the correct modality of measuring tumor lesions at ultrasound. Then we analyze the measurement discrepancies between ultrasound and pathology as well as the discrepancies reported between ultrasound and other imaging modalities. Thereafter, basing on the existent literature and on our experience, we discuss the factors influencing the tumor size measurements at ultrasound. Finally, we illustrate the current strategies to improve the effectiveness of cancer lesions measurement.

Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art

With the development of functional imaging modalities we now have the ability to study the microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use of automated or semi-automated post-processing and analysis of large amounts of quantitative imaging features that can be derived from medical images. The automated generation of these analytical features helps to quantify a number of variables in the imaging assessment of lung malignancy. These imaging features include: tumor spatial complexity, elucidation of the tumor genomic heterogeneity and composition, subregional identification in terms of tumor viability or aggressiveness, and response to chemotherapy and/or radiation. Therefore, a radiomic approach can help to reveal unique information about tumor behavior. Currently available radiomic features can be divided into four major classes: (a) morphological, (b) statistical, (c) regional, and (d) model-based. Each category yields quantitative parameters that reflect specific aspects of a tumor. The major challenge is to integrate radiomic data with clinical, pathological, and genomic information to decode the different types of tissue biology. There are many currently available radiomic studies on lung cancer for which there is a need to summarize the current state of the art.

Imaging in pleural mesothelioma: A review of the 13th International Conference of the International Mesothelioma Interest Group

Imaging plays an important role in the detection, diagnosis, staging, response assessment, and surveillance of malignant pleural mesothelioma. The etiology, biology, and growth pattern of mesothelioma present unique challenges for each modality used to capture various aspects of this disease. Clinical implementation of imaging techniques and information derived from images continue to evolve based on active research in this field worldwide. This paper summarizes the imaging-based research presented orally at the 2016 International Conference of the International Mesothelioma Interest Group (iMig) in Birmingham, United Kingdom, held May 1-4, 2016. Presented topics included intraoperative near-infrared imaging of mesothelioma to aid the assessment of resection completeness, an evaluation of tumor enhancement improvement with increased time delay between contrast injection and image acquisition in standard clinical magnetic resonance imaging (MRI) scans, the potential of early contrast enhancement analysis to provide MRI with a role in mesothelioma detection, the differentiation of short- and long-term survivors based on MRI tumor volume and histogram analysis, the response-assessment potential of hemodynamic parameters derived from dynamic contrast-enhanced computed tomography (DCE-CT) scans, the correlation of CT-based tumor volume with post-surgical tumor specimen weight, and consideration of the need to update the mesothelioma tumor response assessment paradigm.

Image based modeling of tumor growth

Tumors are a main cause of morbidity and mortality worldwide. Despite the efforts of the clinical and research communities, little has been achieved in the past decades in terms of improving the treatment of aggressive tumors. Understanding the underlying mechanism of tumor growth and evaluating the effects of different therapies are valuable steps in predicting the survival time and improving the patients' quality of life. Several studies have been devoted to tumor growth modeling at different levels to improve the clinical outcome by predicting the results of specific treatments. Recent studies have proposed patient-specific models using clinical data usually obtained from clinical images and evaluating the effects of various therapies. The aim of this review is to highlight the imaging role in tumor growth modeling and provide a worthwhile reference for biomedical and mathematical researchers with respect to tumor modeling using the clinical data to develop personalized models of tumor growth and evaluating the effect of different therapies.

Differentiation of malignant cervical lymphadenopathy by dual-energy CT: a preliminary analysis

The accurate diagnosis of malignant cervical lymphadenopathy remains challenging. In this study, we determined the value of quantitative parameters derived from dual-energy computed tomography (DECT) for differentiating malignant cervical lymphadenopathy caused by thyroid carcinoma (TC), salivary gland carcinoma (SC), squamous cell carcinoma (SCC) and lymphoma. We retrospectively analysed 92 patients with pathologically confirmed cervical lymphadenopathy due to TC, SC, SCC and lymphoma. All patients received a DECT scan before therapy. Using GSI (gemstone spectral imaging) Volume Viewer software, we analysed the enhanced monochromatic data, and the quantitative parameters we acquired included the iodine concentration (IC), water concentration (WC) and the slope of the spectral HU curve (λ_HU). One-way ANOVA showed significant differences in the IC and λ_HU among different groups (P < 0.05). Post-hoc pairwise comparisons demonstrated the IC and λ_HU of TC group were significantly higher than those of SC, SCC and lymphoma groups (P < 0.05). In addition, the IC and λ_HU of SC group were significantly higher than those of the SCC and lymphoma groups (P < 0.05). Other comparisons of IC and λ_HU values showed no significant differences (P > 0.05). The quantitative parameters derived from DECT were useful supplements to conventional computed tomography images and were helpful for distinguishing different malignant cervical lymphadenopathies.

Radiomics Analysis on FLT-PET/MRI for Characterization of Early Treatment Response in Renal Cell Carcinoma: A Proof-of-Concept Study

Studying early response to cancer treatment is significant for patient treatment stratification and follow-up. Although recent advances in positron emission tomography (PET) and magnetic resonance imaging (MRI) allow for evaluation of tumor response, a quantitative objective assessment of treatment-related effects offers localization and quantification of structural and functional changes in the tumor region. Radiomics, the process of computerized extraction of features from radiographic images, is a new strategy for capturing subtle changes in the tumor region that works by quantifying subvisual patterns which might escape human identification. The goal of this study was to demonstrate feasibility for performing radiomics analysis on integrated PET/MRI to characterize early treatment response in metastatic renal cell carcinoma (RCC) undergoing sunitinib therapy. Two patients with advanced RCC were imaged using an integrated PET/MRI scanner. [18 F] fluorothymidine (FLT) was used as the PET radiotracer, which can measure the degree of cell proliferation. Image acquisitions included test/retest scans before sunitinib treatment and one scan 3 weeks into treatment using [18 F] FLT-PET, T2-weighted (T2w), and diffusion-weighted imaging (DWI) protocols, where DWI yielded an apparent diffusion coefficient (ADC) map. Our framework to quantitatively characterize treatment-related changes involved the following analytic steps: 1) intraacquisition and interacquisition registration of protocols to allow voxel-wise comparison of changes in radiomic features, 2) correction and pseudoquantification of T2w images to remove acquisition artifacts and examine tissue-specific response, 3) characterization of information captured by T2w MRI, FLT-PET, and ADC via radiomics, and 4) combining multiparametric information to create a map of integrated changes from PET/MRI radiomic features. Standardized uptake value (from FLT-PET) and ADC textures ranked highest for reproducibility in a test/retest evaluation as well as for capturing treatment response, in comparison to high variability seen in T2w MRI. The highest-ranked radiomic feature yielded a normalized percentage change of 63% within the RCC region and 17% in a spatially distinct normal region relative to its pretreatment value. By comparison, both the original and postprocessed T2w signal intensity appeared to be markedly less sensitive and specific to changes within the tumor. Our preliminary results thus suggest that radiomics analysis could be a powerful tool for characterizing treatment response in integrated PET/MRI.

Imaging genomics in cancer research: limitations and promises

Recently, radiogenomics or imaging genomics has emerged as a novel high-throughput method of associating imaging features with genomic data. Radiogenomics has the potential to provide comprehensive intratumour, intertumour and peritumour information non-invasively. This review article summarizes the current state of radiogenomic research in tumour characterization, discusses some of its limitations and promises and projects its future directions. Semi-radiogenomic studies that relate specific gene expressions to imaging features will also be briefly reviewed.

The dog prostate cancer (DPC-1) model: a reliable tool for molecular imaging of prostate tumors and metastases

Background

Clinical applicability of newly discovered reagents for molecular imaging is hampered by the lack of translational models. As the dog prostate cancer (DPC-1) model recapitulates in dogs the natural history of prostate cancer in man, we tested the feasibility of single-photon emission computed tomography (SPECT)/CT imaging in this model using an anti-prostate-specific membrane antigen (PSMA)/17G1 antibody as the radiotracer.

Methods

Immunoblots and immunohistochemistry (IHC) with 17G1 were performed on canine and human prostate cancer cell lines and tissues. Five dogs with DPC-1 tumors were enrolled for pelvic and, in some instances, thoracic SPECT/CT procedures, also repeated over time. Controls included ¹¹¹indium (In)-17G1 prior to DPC-1 implantation and ¹¹¹In-immunoglobulins (IgGs) prior to imaging with ¹¹¹In-17G1 in dogs bearing prostatic DPC-1 tumors.

Results

17G1 cross-reactivity with canine PSMA (and J591) was confirmed by protein analyses on DPC-1, LNCaP, and PC-3 cell lines and IHC of dog vs. human prostate tissue sections. 17G1 stained luminal cells and DPC-1 cancer cells in dog prostates similarly to human luminal and cancer cells of patients and LNCaP xenografts. SPECT/CT imaging revealed low uptake (≤2.1) of both ¹¹¹In-17G1 in normal dog prostates and ¹¹¹In-IgGs in growing DPC-1 prostate tumors comparatively to ¹¹¹In-17G1 uptake of 3.6 increasing up to 6.5 values in prostate with DPC-1 lesions. Images showed a diffused pattern and, occasionally, a peripheral doughnut-shape-like pattern. Numerous sacro-iliac lymph nodes and lung lesions were detected with contrast ratios of 5.2 and 3.0, respectively. The highest values were observed in pelvic bones (11 and 19) of two dogs, next confirmed as PSMA-positive metastases.

Conclusions

This proof-of-concept PSMA-based SPECT/CT molecular imaging detecting primary prostate tumors and metastases in canines with high cancer burden speaks in favor of this large model’s utility to facilitate technology transfer to the clinic and accelerate applications of new tools and modalities for tumor staging in patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s13550-015-0155-6) contains supplementary material, which is available to authorized users.

Response evaluation in mesothelioma: Beyond RECIST

Malignant pleural mesothelioma (MPM) typically demonstrates a non-spherical growth pattern, so it is often difficult to accurately categorize change in tumour burden using size-based tumour response criteria (e.g., WHO (World Health Organisation), RECIST (Response Evaluation Criteria in Solid Tumours) and modified RECIST). Functional imaging techniques are applied to derive quantitative measurements of tumours, which reflect particular aspects of the tumour pathophysiology. By quantifying how these measurements change with treatment, it is possible to observe treatment effects. In this review, we survey the existing roles of CT and MRI for the management of MPM, including the currently applied size measurement criteria for the assessment of treatment response. New functional imaging techniques, such as positron emission tomography (PET), diffusion-weighted MRI (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) that may potentially improve the assessment of treatment response will be highlighted and discussed.

Volumetric assessment of lymph node metastases in patients with non-seminomatous germ cell tumours treated with chemotherapy

INTRODUCTION

We evaluate volumetry and RECIST (Response Evaluation Criteria In Solid Tumors) as methodologies for response after chemotherapy for non-seminomatous germ cell tumour with retroperitoneal lymph node metastases.

METHODS

We performed a retrospective analysis of non-seminomatous testicular tumours and concurrent retroperitoneal lymph node metastases, which received chemotherapy and had computed tomography scans before and after treatment. Volumetric analysis and RECIST criteria were used to calculate response rates. We included a new category (favourable response) for patients with response rates between <100% and >70%. We calculated the correlation between volumetric and RECIST criteria with histological and clinical variables.

RESULTS

In total, 18 patients met the inclusion criteria. Histopathologic analysis of orchiectomy showed teratoma in 55.5% of patients, and those without teratoma had predominantly embryonal carcinoma. The mean baseline volume of retroperitoneal metastases was 447 cc, the mean post-chemotherapy volume was 33.6 cc, and the response rate was 62.6%. According to RECIST criteria, the mean baseline diameter was 4.93 cm, the mean post-chemotherapy diameter was 2.39 cm, and the response rate was 42.4%. Large post-chemotherapy residual masses correlated in both classifications with teratoma. The response rate was associated with the need for surgical treatment and the volumetric classification correlated with the need for lymphadenectomy.

CONCLUSIONS

This study evaluated volumetry as a way to measure clinical response in lymph node metastases of non-seminomatous germ cell tumours. Volumetric analysis is the next step in the evaluation of response rate; its accuracy remains to be determined. Teratoma had greater residual masses and our classification correlated with the need for lymphadenectomy.

Translation in solid cancer: are size-based response criteria an anachronism?

The purpose of translation is the development of effective medicinal products based on validated science. A parallel objective is to obtain marketing authorization for the translated product. Unfortunately, in solid cancer, these two objectives are not mutually consistent as evidenced by the contrast between major advances in science and the continuing dismal record of pharmaceutical productivity. If the problem is unrelated to science, then the process of translation may require a closer examination, namely, the criteria for regulatory approval. This realization is important because, in this context, the objective of translation is regulatory approval, and science does not passively translate into useful medicinal products. Today, in solid cancer, response criteria related to tumor size are less useful than during the earlier cytotoxic drugs era; advanced imaging and biomarkers now allow for tracking of the natural history of the disease in the laboratory and the clinic. Also, it is difficult to infer clinical benefit from tumor shrinkage since it is rarely sustained. Accordingly, size-based response criteria may represent an anachronism relative to translation in solid cancer and it may be appropriate to align preclinical and clinical effort and shift the focus to local invasion and metastasis. The shift from a cancer cell-centric model to a stroma centric model offers novel opportunities not only to interupt the natural history of the disease, but also to rethink the relevance of outdated criteria of clinical response. Current evidence favors the opinion that, in solid cancer, a different, broader, and contextual approach may lead to interventions that could delay local invasion and metastasis. All elements supporting this shift, especially advanced imaging, are in place.

PET imaging of glucose metabolism, neuroinflammation and demyelination in the lysolecithin rat model for multiple sclerosis

Background:

Injection of lysolecithin in the central nervous system results in demyelination accompanied by local activation of microglia and recruitment of monocytes. Positron-emission tomography (PET) imaging, using specific tracers, may be an adequate technique to monitor these events in vivo and therefore may become a tool for monitoring disease progression in multiple sclerosis (MS) patients.

Objectives:

The objective of this paper is to evaluate the potential of PET imaging in monitoring local lesions, using [11C]MeDAS, [11C]PK11195 and [18F]FDG as PET tracers for myelin density, microglia activation and glucose metabolism, respectively.

Methods:

Sprague-Dawley rats were stereotactically injected with either 1% lysolecithin or saline in the corpus callosum and striatum of the right brain hemisphere. PET imaging was performed three days, one week and four weeks after injection. Animals were terminated after PET imaging and the brains were explanted for (immuno)histochemical analysis.

Results:

PET imaging was able to detect local demyelination induced by lysolecithin in the corpus callosum and striatum with [11C]MeDAS and concomitant microglia activation and monocyte recruitment with [11C]PK11195. [18F]FDG imaging demonstrated that glucose metabolism was maintained in the demyelinated lesions.

Conclusion:

PET imaging with multiple tracers allows simultaneous in vivo monitoring of myelin density, neuroinflammation and brain metabolism in small MS-like lesions, indicating its potential to monitor disease progression in MS patients.

Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy?

Background and Purpose

To correlate changes of various CT parameters after the neoadjuvant treatment in patients with lung adenocarcinoma with pathologic responses, focused on their relationship with different therapeutic options, particularly of EGFR-TKI and concurrent chemoradiation therapy (CCRT) settings.

Materials and Methods

We reviewed pre-operative CT images of primary tumors and surgical specimens obtained after neoadjuvant therapy (TKI, n = 23; CCRT, n = 28) from 51 patients with lung adenocarcinoma. Serial changes in tumor volume, density, mass, skewness/kurtosis, and size-zone variability/intensity variability) were assessed from CT datasets. The changes in CT parameters were correlated with histopathologic responses, and the relationship between CT variables and histopathologic responses was compared between TKI and CCRT groups.

Results

Tumor volume, mass, kurtosis, and skewness were significant predictors of pathologic response in CCRT group in univariate analysis. Using multivariate analysis, kurtosis was found to be independent predictor. In TKI group, intensity variability and size-zone variability were significantly decreased in pathologic responder group. Intensity variability was found to be an independent predictor for pathologic response on multivariate analysis.

Conclusions

Quantitative CT variables including histogram or texture analysis have potential as a predictive tool for response evaluation, and it may better reflect treatment response than standard response criteria based on size changes.

A suspicious breast lesion detected by dynamic contrast-enhanced MRI and pathologically confirmed as capillary hemangioma: a case report and literature review

Breast capillary hemangioma is a type of benign vascular tumor which is rarely seen. Little is known about its presentation on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Here, we describe a case of suspicious breast lesion detected by DCE-MRI and pathologically confirmed as capillary hemangioma. Our case indicates that a small mass with a superficial location, clear boundary, and homogeneous enhancement on DCE-MRI indicates the possible diagnosis of hemangioma, whereby even the lesion presents a washout type curve.

Perfusion parameters of dynamic contrast-enhanced magnetic resonance imaging in patients with rectal cancer: correlation with microvascular density and vascular endothelial growth factor expression

Objective

To determine whether quantitative perfusion parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) correlate with immunohistochemical markers of angiogenesis in rectal cancer.

Materials and Methods

Preoperative DCE-MRI was performed in 63 patients with rectal adenocarcinoma. Transendothelial volume transfer (K^trans) and fractional volume of the extravascular-extracellular space (Ve) were measured by Interactive Data Language software in rectal cancer. After surgery, microvessel density (MVD) and vascular endothelial growth factor (VEGF) expression scores were determined using immunohistochemical staining of rectal cancer specimens. Perfusion parameters (K^trans, Ve) of DCE-MRI in rectal cancer were found to be correlated with MVD and VEGF expression scores by Spearman's rank coefficient analysis. T stage and N stage (negative or positive) were correlated with perfusion parameters and MVD.

Results

Significant correlation was not found between any DCE-MRI perfusion parameters and MVD (rs = -0.056 and p = 0.662 for K^trans; rs = -0.103 and p = 0.416 for Ve), or between any DCE-MRI perfusion parameters and the VEGF expression score (rs = -0.042, p = 0.741 for K^trans; r = 0.086, p = 0.497 for Ve) in rectal cancer. TN stage showed no significant correlation with perfusion parameters or MVD (p > 0.05 for all).

Conclusion

DCE-MRI perfusion parameters, K^trans and Ve, correlated poorly with MVD and VEGF expression scores in rectal cancer, suggesting that these parameters do not simply denote static histological vascular properties.