Tumour response prediction by diffusion-weighted MR imaging: ready for clinical use?

Apparent diffusion coefficient in intrahepatic cholangiocarcinoma diffusion-weighted magnetic resonance imaging noninvasively predicts Ki-67 expression

AIM

Tumor Ki-67 expression reflects prognosis and cancer grade, and biopsy-based preoperative assessment of Ki-67 expression is key to treatment. Apparent diffusion coefficient (ADC) values obtained with this imaging may noninvasively predict Ki-67 by reflecting tumor cell density and limited water molecule movement from irregular alignment. This study aimed to investigate the ability of ADC values to predict Ki-67 expression in intrahepatic cholangiocarcinoma (ICC).

METHOD

We retrospectively analyzed 39 cases of ICC confirmed by surgical pathology. All patients had undergone magnetic resonance imaging, and ADC values (mean, minimum, and maximum) were calculated. Ki-67 expression was assessed by immunohistochemistry, and patients were divided into groups of high (n = 18) and low (n = 21) Ki-67 expression. To assess the diagnostic performance of the ADC values for Ki-67 expression, we used the receiver operating characteristic curve and compared the areas under the curve (AUC).

RESULTS

The mean and minimum ADC values were significantly lower in the group with high Ki-67 expression. For predicting high Ki-67 expression, the AUC values were 0.701 for mean ADC, 0.818 for minimum ADC, and 0.571 for maximum ADC. The diagnostic sensitivity and specificity of the minimum ADC values were 88.9% and 76.2%, respectively. In addition, with ADC values combined, the AUC increased to 0.831. Apparent diffusion coefficient is a useful predictor of Ki-67 expression level in ICC.

CONCLUSION

Apparent diffusion coefficient values, especially minimum ADC values, can noninvasively predict ICC associated with high Ki-67 expression.

Imaging advances in efficacy assessment of gastric cancer neoadjuvant chemotherapy

Effective neoadjuvant chemotherapy (NAC) can improve the survival of patients with locally progressive gastric cancer, but chemotherapeutics do not always exhibit good efficacy in all patients. Therefore, accurate preoperative evaluation of the effect of neoadjuvant therapy and the appropriate selection of surgery time to minimize toxicity and complications while prolonging patient survival are key issues that need to be addressed. This paper reviews the role of three imaging methods, morphological, functional, radiomics, and artificial intelligence (AI)-based imaging, in evaluating NAC pathological reactions for gastric cancer. In addition, the advantages and disadvantages of each method and the future application prospects are discussed.

Diffusion-weighted Imaging of the Chest: A Primer for Radiologists

Diffusion-weighted imaging (DWI) is a fundamental sequence not only in neuroimaging but also in oncologic imaging and has emerging applications for MRI evaluation of the chest. DWI can be used in clinical practice to enhance lesion conspicuity, tissue characterization, and treatment response. While the spatial resolution of DWI is in the order of millimeters, changes in diffusion can be measured on the micrometer scale. As such, DWI sequences can provide important functional information to MRI evaluation of the chest but require careful optimization of acquisition parameters, notably selection of b values, application of parallel imaging, fat saturation, and motion correction techniques. Along with assessment of morphologic and other functional features, evaluation of DWI signal attenuation and apparent diffusion coefficient maps can aid in tissue characterization. DWI is a noninvasive noncontrast acquisition with an inherent quantitative nature and excellent reproducibility. The outstanding contrast-to-noise ratio provided by DWI can be used to improve detection of pulmonary, mediastinal, and pleural lesions, to identify the benign nature of complex cysts, to characterize the solid portions of cystic lesions, and to classify chest lesions as benign or malignant. DWI has several advantages over fluorine 18 (18F)-fluorodeoxyglucose PET/CT in the assessment, TNM staging, and treatment monitoring of lung cancer and other thoracic neoplasms with conventional or more recently developed therapies. © RSNA, 2023 Quiz questions for this article are available in the supplemental material. Supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article.

Joint Deformable Image Registration and ADC Map Regularization: Application to DWI-based Lymphoma Classification

The Apparent Diffusion Coefficient (ADC) is considered an important imaging biomarker contributing to the assessment of tissue microstructure and pathophysiology. It is calculated from Diffusion-Weighted Magnetic Resonance Imaging (DWI) by means of a diffusion model, usually without considering any motion during image acquisition. We propose a method to improve the computation of the ADC by coping jointly with both motion artifacts in whole-body DWI (through group-wise registration) and possible instrumental noise in the diffusion model. The proposed deformable registration method yielded on average the lowest ADC reconstruction error on data with simulated motion and diffusion. Moreover, our approach was applied on whole-body diffusion weighted images obtained with five different b-values from a cohort of 38 patients with histologically confirmed lymphomas of three different types (Hodgkin, diffuse large B-cell lymphoma and follicular lymphoma). Evaluation on the real data showed that ADC-based features, extracted using our joint optimization approach classified lymphomas with an accuracy of approximately 78.6\% (yielding a 11\% increase in respect to the standard features extracted from unregistered diffusion-weighted images). Furthermore, the correlation between diffusion characteristics and histopathological findings was higher than any other previous approach of ADC computation.

Treatment Effect of a Vascular-Disrupting Agent Dynamically Monitored by DWI: An Animal Experimental Study

Objective

To investigate the treatment effect of a vascular-disrupting agent, M410, using diffusion-weighted imaging in a rabbit model of hepatic VX2 tumor.

Methods

28 New Zealand white rabbit models with VX2 liver tumors were established and were randomly divided into M410 (intravenous injection of M410 at a dose of 25 mg/kg every three days) and control (intravenous injection of saline every three days) groups. Conventional and diffusion-weighted imaging (DWI) were acquired on a 3.0 T MR unit at baseline, 4 h, d 1, d 4, d 7, and d 14 posttreatment. B-value with 700 (s/mm2) was chosen during DWI examinations. Tumor volume and apparent diffusion coefficient (ADC) values of the entire tumor and solid component of the tumor at every time point were measured. Two randomly chosen rabbits from each group were sacrificed for H&E staining and CD34 immunohistochemical assessments at each time point. An independent sample t-test was used to assess differences in tumor sizes and ADC values of the entire tumor and solid component of tumors between two groups, with P < 0.05 considered statistically significant.

Result

There was no significant difference in tumor volume between the two groups at baseline, 4 h, and d 1. With time, the tumors in the control group grew significantly faster than those in the M410 group, and the average ADC values of the M410 group were lower than those of the control group at d 1 and higher than those of the control group at d 4; as such, there were statistical differences between the two groups at these two time points but not at the other four time points. The following pathological results reflected the underlying morphological changes and vascular alterations.

Conclusions

M410 performed well in inhibiting the growth of the hepatic VX2 tumor which could be noninvasively monitored by DWI metrics.

Phase I/II Study of LDE225 in Combination with Gemcitabine and Nab-Paclitaxel in Patients with Metastatic Pancreatic Cancer

BACKGROUND

Desmoplasia is a central feature of the tumor microenvironment in pancreatic ductal adenocarcinoma (PDAC). LDE225 is a pharmacological Hedgehog signaling pathway inhibitor and is thought to specifically target tumor stroma. We investigated the combined use of LDE225 and chemotherapy to treat PDAC patients.

METHODS

This was a multi-center, phase I/II study for patients with metastatic PDAC establishing the maximum tolerated dose of LDE225 co-administered with gemcitabine and nab-paclitaxel (phase I) and evaluating the efficacy and safety of the treatment combination after prior FOLFIRINOX treatment (phase II). Tumor microenvironment assessment was performed with quantitative MRI using intra-voxel incoherent motion diffusion weighted MRI (IVIM-DWI) and dynamic contrast-enhanced (DCE) MRI.

RESULTS

The MTD of LDE225 was 200 mg once daily co-administered with gemcitabine 1000 mg/m2 and nab-paclitaxel 125 mg/m2. In phase II, six therapy-related grade 4 adverse events (AE) and three grade 5 were observed. In 24 patients, the target lesion response was evaluable. Three patients had partial response (13%), 14 patients showed stable disease (58%), and 7 patients had progressive disease (29%). Median overall survival (OS) was 6 months (IQR 3.9-8.1). Blood plasma fraction (DCE) and diffusion coefficient (IVIM-DWI) significantly increased during treatment. Baseline perfusion fraction could predict OS (>222 days) with 80% sensitivity and 85% specificity.

CONCLUSION

LDE225 in combination with gemcitabine and nab-paclitaxel was well-tolerated in patients with metastatic PDAC and has promising efficacy after prior treatment with FOLFIRINOX. Quantitative MRI suggested that LDE225 causes increased tumor diffusion and works particularly well in patients with poor baseline tumor perfusion.

Artificial Intelligence and Radiomics in Head and Neck Cancer Care: Opportunities, Mechanics, and Challenges

The advent of large-scale high-performance computing has allowed the development of machine-learning techniques in oncologic applications. Among these, there has been substantial growth in radiomics (machine-learning texture analysis of images) and artificial intelligence (which uses deep-learning techniques for "learning algorithms"); however, clinical implementation has yet to be realized at scale. To improve implementation, opportunities, mechanics, and challenges, models of imaging-enabled artificial intelligence approaches need to be understood by clinicians who make the treatment decisions. This article aims to convey the basic conceptual premises of radiomics and artificial intelligence using head and neck cancer as a use case. This educational overview focuses on approaches for head and neck oncology imaging, detailing current research efforts and challenges to implementation.

Current status and future perspectives on neoadjuvant therapy in gastric cancer

Gastric cancer, with high morbidity and mortality rates, is one of the most heterogeneous tumors. Radical gastrectomy and postoperative chemotherapy are the standard treatments. However, the safety and efficacy of neoadjuvant therapy (NAT) need to be confirmed by many trials before implementation, creating a bottleneck in development. Although clinical benefits of NAT have been observed, a series of problems remain to be solved. Before therapy, more contributing factors should be offered for choice in the intended population and ideal regimens. Enhanced computed tomography (CT) scanning is usually applied to evaluate effectiveness according to Response Evaluation Criteria in Solid Tumors (RECIST), yet CT scanning results sometimes differ from pathological responses. After NAT, the appropriate time for surgery is still empirically defined. Our review aims to discuss the abovementioned issues regarding NAT for GC, including indications, selection of regimens, lesion assessment and NAT-surgery interval time.

Metabolic Imaging Using Hyperpolarized Pyruvate-Lactate Exchange Assesses Response or Resistance to the EGFR Inhibitor Cetuximab in Patient-Derived HNSCC Xenografts

PURPOSE

Optimal head and neck squamous cell carcinoma (HNSCC) patient selection for anti-EGFR-based therapy remains an unmet need since only a minority of patients derive long-term benefit from cetuximab treatment. We assessed the ability of state-of-the-art noninvasive in vivo metabolic imaging to probe metabolic shift in cetuximab-sensitive and -resistant HNSCC patient-derived tumor xenografts (PDTXs).

EXPERIMENTAL DESIGN

Three models selected based on their known sensitivity to cetuximab in patients (cetuximab-sensitive or acquired-resistant HNC007 PDTXs, cetuximab-naïve UCLHN4 PDTXs, and cetuximab-resistant HNC010 PDTXs) were inoculated in athymic nude mice.

RESULTS

Cetuximab induced tumor size stabilization in mice for 4 weeks in cetuximab-sensitive and -naïve models treated with weekly injections (30 mg/kg) of cetuximab. Hyperpolarized ¹³C-pyruvate-¹³C-lactate exchange was significantly decreased in vivo in cetuximab-sensitive xenograft models 8 days after treatment initiation, whereas it was not modified in cetuximab-resistant xenografts. Ex vivo analysis of sensitive tumors resected at day 8 after treatment highlighted specific metabolic changes, likely to participate in the decrease in the lactate to pyruvate ratio in vivo. Diffusion MRI showed a decrease in tumor cellularity in the HNC007-sensitive tumors, but failed to show sensitivity to cetuximab in the UCLHN4 model.

CONCLUSIONS

This study constitutes the first in vivo demonstration of cetuximab-induced metabolic changes in cetuximab-sensitive HNSCC PDTXs that were not present in resistant tumors. Using metabolic imaging, we were able to identify hyperpolarized ¹³C-pyruvate as a potential marker for response and resistance to the EGFR inhibitor in HNSCC.

Assessment of the percentage of apparent diffusion coefficient value changes as an early indicator of the response of colorectal hepatic metastases to chemotherapy

Background

Colorectal cancer is considered one of the most common causes of cancer-related deaths worldwide. We aim to evaluate the efficacy of DWI-MRI in predicting response to chemotherapy in this cohort.

The study included 30 lesions in 20 biopsy proven-colorectal cancer patients with hepatic metastasis larger than 1 cm. All patients underwent both triphasic CT with intravenous contrast, pre-chemotherapy MRI (axial T2 and DW sequences) which was repeated 21 days following chemotherapy. A follow-up CT was done 2 months later. The response of the lesions was evaluated using the RESCIST criteria. On MRI, the lesions corresponding to the ones chosen on CT were identified and the apparent diffusion coefficient (ADC) values of pre- and post-chemotherapy images were recorded and correlated with the CT results.

Results

In the study, 17 (56.7%) of the lesions showed response to chemotherapy while 13 (43.3%) were non-responding. There was no significant difference in pretreatment ADC values between responding and non-responding lesions (p = 0.14). The mean percentage increase in ADC values in responding lesions was 42% compared to 18% in non-responding lesions (p < 0.001). Lesions that showed less than 18% increase were all found to be non-responsive

Conclusion

DWI-MRI has an emerging role in early assessment of early treatment response that can be detected before morphological response for patients with hepatic metastasis from colorectal cancer. Based on our study, the use of 25 % as the cutoff point of percent difference in ADC for detection of non-responding lesions proved to be successful only 21 days after the 1st chemotherapy cycle.

ADC correlation with Sirtuin1 to assess early chemoradiotherapy response of locally advanced esophageal carcinoma patients

Aims

To determine the biological correlation between apparent diffusion coefficient (ADC) values and Sirtuin1 (SIRT1) levels of tumour tissues in patients with esophageal carcinoma (EC), and to ascertain the treatment biomarker of ADC in predicting the early response of patients undergoing definitive chemoradiotherapy (CRT).

Methods

A total of 66 patients were enrolled, and the specimens of tumour tissues were collected before treatment to perform immunohistochemical (IHC) examinations and quantify the levels of SIRT1. Then all patients were given two esophageal magnetic resonance imaging (MRI) examinations with diffused weighed imaging (DWI) including pretreatment and intra-treatment (1~2 weeks after the start of radiotherapy). The regions of interest (ROIs) were contoured according to the stipulated rules in advance using off-line software, and the values of the ADC in the ROIs were generated automatically. Then, the values of the ADC at baseline and intra-treatment were labeled as pre-ADC and intra-ADC respectively, and ΔADC, ADC_ratio were calculated. Pearson’s correlation coefficients were acquired to estimate the correlation between each of ADC values and SIRT1 levels. Spearman’s rank correlation coefficients were acquired to estimate the correlation between early response and the values of each ADC. Receptor operation characteristics (ROC) curves were constructed to estimate the accuracy of the ADC in predicting the early response of CRT.

Results

The findings of this study showed different correlations between ADC values and the levels of SIRT1 (ΔADC: r = − 0.943, P = 0.002; ADC_ratio: r = − 0.911, P = 0.000; intra-ADC: r = − 0.748, P = 0.002; pre-ADC: r = 0.109, P = 0.558). There was a positive correlation between ΔADC and early response to treatment (ρ = 0.615, P = 0.023), and multivariable logistic regression revealed that ΔADC was significantly associated with short-term response of CRT in esophageal carcinoma patients.

Conclusions

In summary, early increases in ADC may facilitate the predication of early CRT response in patients with esophageal squamous cell carcinoma (ESCC), which may be attributed to the different correlation between ADC changes and SIRT1 expression.

Colorectal cancer: Parametric evaluation of morphological, functional and molecular tomographic imaging

Colorectal cancer (CRC) represents one of the leading causes of tumor-related deaths worldwide. Among the various tools at physicians' disposal for the diagnostic management of the disease, tomographic imaging (e.g., CT, MRI, and hybrid PET imaging) is considered essential. The qualitative and subjective evaluation of tomographic images is the main approach used to obtain valuable clinical information, although this strategy suffers from both intrinsic and operator-dependent limitations. More recently, advanced imaging techniques have been developed with the aim of overcoming these issues. Such techniques, such as diffusion-weighted MRI and perfusion imaging, were designed for the "in vivo" evaluation of specific biological tissue features in order to describe them in terms of quantitative parameters, which could answer questions difficult to address with conventional imaging alone (e.g., questions related to tissue characterization and prognosis). Furthermore, it has been observed that a large amount of numerical and statistical information is buried inside tomographic images, resulting in their invisibility during conventional assessment. This information can be extracted and represented in terms of quantitative parameters through different processes (e.g., texture analysis). Numerous researchers have focused their work on the significance of these quantitative imaging parameters for the management of CRC patients. In this review, we aimed to focus on evidence reported in the academic literature regarding the application of parametric imaging to the diagnosis, staging and prognosis of CRC while discussing future perspectives and present limitations. While the transition from purely anatomical to quantitative tomographic imaging appears achievable for CRC diagnostics, some essential milestones, such as scanning and analysis standardization and the definition of robust cut-off values, must be achieved before quantitative tomographic imaging can be incorporated into daily clinical practice.

Stability of radiomic features of apparent diffusion coefficient (ADC) maps for locally advanced rectal cancer in response to image pre-processing

Quantitative imaging features (radiomics) extracted from apparent diffusion coefficient (ADC) maps of rectal cancer patients can provide additional information to support treatment decision. Most available radiomic computational packages allow extraction of hundreds to thousands of features. However, two major factors can influence the reproducibility of radiomic features: interobserver variability, and imaging filtering applied prior to features extraction. In this exploratory study we seek to determine to what extent various commonly-used features are reproducible with regards to the mentioned factors using ADC maps from two different clinics (56 patients). Features derived from intensity distribution histograms are less sensitive to manual tumour delineation differences, noise in ADC images, pixel size resampling and intensity discretization. Shape features appear to be strongly affected by delineation quality. On the whole, textural features appear to be poorly or moderately reproducible with respect to the image pre-processing perturbations we reproduced.

Diffusion-weighted magnetic resonance imaging is useful for the response evaluation of chemotherapy and/or radiotherapy to recurrent lesions of lung cancer

Diffusion-weighted magnetic resonance imaging (DWI) has been reported to be useful for the assessment of lung cancer staging. It is uncertain whether DWI is more accurate for the response evaluation of chemotherapy and/or radiotherapy compared to computed tomography (CT). The purpose of this study is to compare the response evaluation of DWI for chemotherapy and/or radiotherapy to recurrent tumors of lung cancer with that of CT which is a standard tool in RECIST (Response Evaluation Criteria in Solid Tumours). Forty-one patients who agreed to this project and had CT scan and DWI examinations within a month of each other every six months for at least 2 years after pulmonary resection of primary lung cancer were enrolled in this study. Of the patients, 24 patients had metastases or recurrences, and CT and DWI were performed for assessment of the response evaluation of chemotherapy and/or radiotherapy to recurrent lesions. They were followed up for at least two years after the relapse. The response evaluation by CT using RECIST were PR in five patients, SD in two, and PD in the remaining 17 patients. On the other hand, the response evaluation by DWI were CR in four patients, PR in two patients, SD in one, and PD in the remaining 17 patients. Follow-up studies revealed the response evaluation by DWI were correct. Functional evaluation of DWI is better than that of CT for the response evaluation of chemotherapy and/or radiotherapy to recurrent tumors of lung cancer.

The Value of Diffusion-Weighted Magnetic Resonance Imaging in Predicting the Efficacy of Radiation and Chemotherapy in Cervical Cancer

Background

To analyze the application value of apparent diffusion coefficient (ADC) and exponent apparent diffusion coefficient (EADC) in evaluating the efficacy of radiation and chemotherapy in cervical cancer using pre- and posttreatment diffusion-weighted magnetic resonance imaging (DW-MRI) scans.

Methods

52 patients with cervical cancer were administered radiation and chemotherapy. Both MRI and DW-MRI were obtained at different stages. The ADC and EADC values, as well as the maximum tumor diameter, were measured and analyzed.

Results

We found that the ADC value increased after treatment, and the EADC value decreased. Changes in the calculated ADC occurred earlier than the morphologic changes of the tumors. A negative correlation was detected between reduced rates in the maximum tumor diameter two months after treatment and pretreatment ADC value (r = –0.658, P < 0.05). An ROC curve and nonlinear regression analysis showed that the formula, y = (1525500.122x² – 4689.962x + 3.482) × 100%, can be used to calculate the percentage of complete remission after treatment according to the pretreatment ADC value.

Conclusion

Our data suggest that pretreatment ADC and EADC values are predictive of the efficacy of radiation and chemotherapy. Both ADC and EADC values during treatment were instrumental in early monitoring and dynamic observation.

2'-deoxy-2'-[18F] fluoro-D-glucose positron emission tomography, diffusion-weighted magnetic resonance imaging, and choline spectroscopy to predict the activity of cetuximab in tumor xenografts derived from patients with squamous cell carcinoma of the head and neck

We investigated changes on 2'-deoxy-2'-[18F]fluoro-D-glucose positron emission tomography (¹⁸FDG-PET), diffusion-weighted magnetic resonance imaging (DW-MRI), and choline spectroscopy as early markers of cetuximab activity in squamous cell carcinoma of the head and neck (SCCHN). SCCHN patient-derived tumor xenografts models were selected based on their cetuximab sensitivity. Three models were resistant to cetuximab and two were sensitive (one was highly sensitive and the other one was moderately sensitive). Cetuximab was infused on day 0 and 7. Maximal standardized uptake values (SUVmax), apparent diffusion coefficient (ADC), and total choline pool were measured at baseline and at day 8. To investigate the possible clinical relevance of our pre-clinical findings, we also studied the SUVmax and ADC modifications induced by cetuximab in five patients. Cetuximab induced a significant decrease in SUVmax and an increase in ADC at day 8 compared to baseline in the most cetuximab-sensitive model but not in the other models. At day 8, in one resistant model, SUVmax was decreased compared to baseline and was significantly lower than the controls. Choline spectroscopy was not able to predict cetuximab activity. The five patients treated with cetuximab had a ¹⁸FDG-PET partial response. One patient had a partial response according to RECISTv1.1. Interestingly, this last had also an increase in ADC value above 25%. Our preclinical data support the use of PDTX to investigate imaging techniques to detect early treatment response. Our pre-clinical and clinical data suggest that DW-MRI and ¹⁸FDG-PET should be further investigated to predict cetuximab activity.

UK quantitative WB-DWI technical workgroup: consensus meeting recommendations on optimisation, quality control, processing and analysis of quantitative whole-body diffusion-weighted imaging for cancer

OBJECTIVE

Application of whole body diffusion-weighted MRI (WB-DWI) for oncology are rapidly increasing within both research and routine clinical domains. However, WB-DWI as a quantitative imaging biomarker (QIB) has significantly slower adoption. To date, challenges relating to accuracy and reproducibility, essential criteria for a good QIB, have limited widespread clinical translation. In recognition, a UK workgroup was established in 2016 to provide technical consensus guidelines (to maximise accuracy and reproducibility of WB-MRI QIBs) and accelerate the clinical translation of quantitative WB-DWI applications for oncology.

METHODS

A panel of experts convened from cancer centres around the UK with subspecialty expertise in quantitative imaging and/or the use of WB-MRI with DWI. A formal consensus method was used to obtain consensus agreement regarding best practice. Questions were asked about the appropriateness or otherwise on scanner hardware and software, sequence optimisation, acquisition protocols, reporting, and ongoing quality control programs to monitor precision and accuracy and agreement on quality control.

RESULTS

The consensus panel was able to reach consensus on 73% (255/351) items and based on consensus areas made recommendations to maximise accuracy and reproducibly of quantitative WB-DWI studies performed at 1.5T. The panel were unable to reach consensus on the majority of items related to quantitative WB-DWI performed at 3T.

CONCLUSION

This UK Quantitative WB-DWI Technical Workgroup consensus provides guidance on maximising accuracy and reproducibly of quantitative WB-DWI for oncology. The consensus guidance can be used by researchers and clinicians to harmonise WB-DWI protocols which will accelerate clinical translation of WB-DWI-derived QIBs.

Inter- and intra-observer reproducibility of ADC measurements in esophageal carcinoma primary tumors

The apparent diffuse coefficient (ADC) may correlate with the treatment response to chemotherapy/radiotherapy in solid tumors. Our aim was to determine the inter- and intra-observer reproducibility of ADC measurements in primary esophageal squamous cell carcinoma (ESCC). ADCs were blindly measured in 31 patients diagnosed with ESCC by two observers before treatment (pre-ADC) and after 5^th fraction radiotherapy (intra-ADC) twice with a 2-week interval. The mean pre-ADC of primary tumors was 1.25±0.22 and 1.27±0.23 (in 10⁻³mm²/s) from observer A for measurements 1 and 2, respectively, and the intra-observer measurements were -0.02 bias vs. -0.13-0.09 limits of agreement. From observer B, the mean pre-ADC varied between 1.25±0.23 and 1.27±0.23 (in 10⁻³mm²/s) for measurements 1 and 2, respectively, and intra-observer measurements were -0.02 bias vs. -0.17∼0.16 limits of agreement. The mean pre-ADC of primary tumors was 1.26±0.24 (in 10⁻³mm²/s) from observers A and B, and inter-observer measurements were 0.01 bias vs. -0.09-0.09 limits of agreement, revealing a low inter-observer variance. Similar measurements of the intra-SD parameters showed that the pre- and intra-ADC of primary tumors differed significantly. Thus ADC measurements may have sufficient inter-observer and intra-observer reproducibility to measure primary tumor responses to treatment, and the ADCs before and during treatment differed.

Evaluation of connectivity map-discovered celastrol as a radiosensitizing agent in a murine lung carcinoma model: Feasibility study of diffusion-weighted magnetic resonance imaging

This study was designed to identify potential radiosensitizing (RS) agents for combined radio- and chemotherapy in a murine model of human lung carcinoma, and to evaluate the in vivo effect of the RS agents using diffusion-weighted magnetic resonance imaging (DW-MRI). Radioresistance-associated genes in A549 and H460 cells were isolated on the basis of their gene expression profiles. Celastrol was selected as a candidate RS by using connectivity mapping, and its efficacy in lung cancer radiotherapy was tested. Mice inoculated with A549 carcinoma cells were treated with single ionizing radiation (SIR), single celastrol (SC), or celastrol-combined ionizing radiation (CCIR). Changes in radiosensitization over time were assessed using DW-MRI before and at 3, 6, and 12 days after therapy initiation. The tumors were stained with hematoxylin and eosin at 6 and 12 days after therapy. The percentage change in the apparent diffusion coefficient (ADC) value in the CCIR group was significantly higher than that in the SC and SIR group on the 12^th day (Mann–Whitney U-test, p = 0.05; Kruskal–Wallis test, p < 0.05). A significant correlation (Spearman’s rho correlation coefficient of 0.713, p = 0.001) was observed between the mean percentage tumor necrotic area and the mean ADC values after therapy initiation. These results suggest that the novel radiosensitizing agent celastrol has therapeutic effects when combined with ionizing radiation (IR), thereby maximizing the therapeutic effect of radiation in non–small cell lung carcinoma. In addition, DW-MRI is a useful noninvasive tool to monitor the effects of RS agents by assessing cellularity changes and sequential therapeutic responses.

Decision support systems for personalized and participative radiation oncology

A paradigm shift from current population based medicine to personalized and participative medicine is underway. This transition is being supported by the development of clinical decision support systems based on prediction models of treatment outcome. In radiation oncology, these models 'learn' using advanced and innovative information technologies (ideally in a distributed fashion - please watch the animation: http://youtu.be/ZDJFOxpwqEA) from all available/appropriate medical data (clinical, treatment, imaging, biological/genetic, etc.) to achieve the highest possible accuracy with respect to prediction of tumor response and normal tissue toxicity. In this position paper, we deliver an overview of the factors that are associated with outcome in radiation oncology and discuss the methodology behind the development of accurate prediction models, which is a multi-faceted process. Subsequent to initial development/validation and clinical introduction, decision support systems should be constantly re-evaluated (through quality assurance procedures) in different patient datasets in order to refine and re-optimize the models, ensuring the continuous utility of the models. In the reasonably near future, decision support systems will be fully integrated within the clinic, with data and knowledge being shared in a standardized, dynamic, and potentially global manner enabling truly personalized and participative medicine.

Apparent diffusion coefficient of normal adrenal glands

Objective

To assess the feasibility and reliability of apparent diffusion coefficient (ADC) measurements of normal adrenal glands.

Materials and methods

This was a retrospective study involving 32 healthy subjects, divided into two groups: prepubertal (PreP, n = 12), aged from 2 months to 12.5 years (4 males; 8 females); and postpubertal (PostP, n = 20), aged from 11.9 to 61 years (5 males; 15 females). Diffusion-weighted magnetic resonance imaging (DW-MRI) sequences were acquired at a 1.5 T scanner using b values of 0, 20, 500, and 1000 s/mm². Two radiologists evaluated the images. ADC values were measured pixel-by-pixel on DW-MRI scans, and automatic co-registration with the ADC map was obtained.

Results

Mean ADC values for the right adrenal glands were 1.44 × 10^-3 mm²/s for the PreP group and 1.23 × 10^-3 mm²/s for the PostP group, whereas they were 1.58 × 10^-3 mm²/s and 1.32 × 10^-3 mm²/s, respectively, for the left glands. ADC values were higher in the PreP group than in the PostP group (p < 0.05). Agreement between readers was almost perfect (intraclass correlation coefficient, 0.84-0.94; p < 0.05).

Conclusion

Our results demonstrate the feasibility and reliability of performing DW-MRI measurements of normal adrenal glands. They could also support the feasibility of ADC measurements of small structures.

Restriction spectrum imaging: An evolving imaging biomarker in prostate MRI

Restriction spectrum imaging (RSI) is a novel diffusion-weighted MRI technique that uses the mathematically distinct behavior of water diffusion in separable microscopic tissue compartments to highlight key aspects of the tissue microarchitecture with high conspicuity. RSI can be acquired in less than 5 min on modern scanners using a surface coil. Multiple field gradients and high b-values in combination with postprocessing techniques allow the simultaneous resolution of length-scale and geometric information, as well as compartmental and nuclear volume fraction filtering. RSI also uses a distortion correction technique and can thus be fused to high resolution T2-weighted images for detailed localization, which improves delineation of disease extension into critical anatomic structures. In this review, we discuss the acquisition, postprocessing, and interpretation of RSI for prostate MRI. We also summarize existing data demonstrating the applicability of RSI for prostate cancer detection, in vivo characterization, localization, and targeting.

LEVEL OF EVIDENCE

5 J. Magn. Reson. Imaging 2017;45:323-336.

Apparent diffusion coefficient of breast cancer and normal fibroglandular tissue in diffusion-weighted imaging: the effects of menstrual cycle and menopausal status

The purpose of this study was to investigate prospectively whether the apparent diffusion coefficients (ADCs) of both breast cancer and normal fibroglandular tissue vary with the menstrual cycle and menopausal status. Institutional review board approval was obtained, and informed consent was obtained from each participant. Fifty-seven women (29 premenopausal, 28 postmenopausal) with newly diagnosed breast cancer underwent diffusion-weighted imaging twice (interval 12-20 days) before surgery. Two radiologists independently measured ADC of breast cancer and normal contralateral breast tissue, and we quantified the differences according to the phases of menstrual cycle and menopausal status. With normal fibroglandular tissue, ADC was significantly lower in postmenopausal than in premenopausal women (P = 0.035). In premenopausal women, ADC did not differ significantly between proliferative and secretory phases in either breast cancer or normal fibroglandular tissue (P = 0.969 and P = 0.519, respectively). In postmenopausal women, no significant differences were found between ADCs measured at different time intervals in either breast cancer or normal fibroglandular tissue (P = 0.948 and P = 0.961, respectively). The within-subject variability of the ADC measurements was quantified using the coefficient of variation (CV) and was small: the mean CVs of tumor ADC were 2.90 % (premenopausal) and 3.43 % (postmenopausal), and those of fibroglandular tissue ADC were 4.37 % (premenopausal) and 2.55 % (postmenopausal). Both intra- and interobserver agreements were excellent for ADC measurements, with intraclass correlation coefficients in the range of 0.834-0.974. In conclusion, the measured ADCs of breast cancer and normal fibroglandular tissue were not affected significantly by menstrual cycle, and the measurements were highly reproducible both within and between observers.

Diagnosis and treatment of bone metastasis: comprehensive guideline of the Japanese Society of Medical Oncology, Japanese Orthopedic Association, Japanese Urological Association, and Japanese Society for Radiation Oncology

Diagnosis and treatment of bone metastasis requires various types of measures, specialists and caregivers. To provide better diagnosis and treatment, a multidisciplinary team approach is required. The members of this multidisciplinary team include doctors of primary cancers, radiologists, pathologists, orthopaedists, radiotherapists, clinical oncologists, palliative caregivers, rehabilitation doctors, dentists, nurses, pharmacists, physical therapists, occupational therapists, medical social workers, etc. Medical evidence was extracted from published articles describing meta-analyses or randomised controlled trials concerning patients with bone metastases mainly from 2003 to 2013, and a guideline was developed according to the Medical Information Network Distribution Service Handbook for Clinical Practice Guideline Development 2014. Multidisciplinary team meetings are helpful in diagnosis and treatment. Clinical benefits such as physical or psychological palliation obtained using the multidisciplinary team approaches are apparent. We established a guideline describing each specialty field, to improve understanding of the different fields among the specialists, who can further provide appropriate treatment, and to improve patients’ outcomes.

Role of quantitative magnetic resonance imaging parameters in the evaluation of treatment response in malignant tumors

OBJECTIVE

To elaborate the role of quantitative magnetic resonance imaging (MRI) parameters in the evaluation of treatment response in malignant tumors.

DATA SOURCES

Data cited in this review were obtained mainly from PubMed in English from 1999 to 2014, with keywords "dynamic contrast-enhanced (DCE)-MRI," "diffusion-weighted imaging (DWI)," "microcirculation," "apparent diffusion coefficient (ADC)," "treatment response" and "oncology."

STUDY SELECTION

Articles regarding principles of DCE-MRI, principles of DWI, clinical applications as well as opportunity and aspiration were identified, retrieved and reviewed.

RESULTS

A significant correlation between ADC values and treatment response was reported in most DWI studies. Most quantitative DCE-MRI studies showed a significant correlation between K trans values and treatment response. However, in different tumors and studies, both high and low pretreatment ADC or K trans values were found to be associated with response rate. Both DCE-MRI and DWI demonstrated changes in their parameters hours to days after treatment, showing a decrease in K trans or an increase in ADC associated with response in most cases.

CONCLUSIONS

Combinations of quantitative MRI play an important role in the evaluation of treatment response of malignant tumors and hold promise for use as a cancer treatment response biomarker. However, validation is hampered by the lack of reproducibility and standardization. MRI acquisition protocols and quantitative image analysis approaches should be properly addressed prior to further testing the clinical use of quantitative MRI parameters in the assessment of treatments.

Time-window of early detection of response to concurrent chemoradiation in cervical cancer by using diffusion-weighted MR imaging: a pilot study

Background

To investigate the feasibility of DWI in evaluating early therapeutic response of uterine cervical cancer to concurrent chemoradiation (CCR) and establish optimal time window for early detection of treatment response.

Methods

This was a prospective study and informed consent was obtained from all patients. Thirty-three patients with uterine cervical cancer who received CCR underwent conventional MRI and DWI examinations prior to therapy (base-line) and at 3 days (postT1), 7 days (postT2), 14 days (postT3), 1 month (postT4) and 2 months (postT5) after the therapy initiated. Tumor response was determined by comparing the base-line and postT5 MRI by using RECIST criterion.

Results

Percentage ADC change (γADC) of complete response (CR) group at each follow up time was greater than that of partial response (PR) group, and the differences were significant at postT3 (p = 0.007), postT4 (p = 0.001), and postT5 (p = 0.019). There was positive correlation between γADC at each follow-up time and percentage size reduction at postT5. The day of 14 after the therapy initiated can be considered as the optimal time for monitoring early treatment response of uterine cervical cancer to CCR, and the representative and sensitive index was γADC. With the cut-off value of 35.4 %, the sensitivity and specificity for prediction of CR group were 100 % and 73.1 %, respectively.

Conclusions

It is feasible to use DWI to predict and monitor early treatment response in patients with uterine cervical cancer that undergoing CCR, and optimal time window for early detection of tumor response is the day of 14 after therapy initiated.

Inhibition of Pediatric Glioblastoma Tumor Growth by the Anti-Cancer Agent OKN-007 in Orthotopic Mouse Xenografts

Pediatric glioblastomas (pGBM), although rare, are one of the leading causes of cancer-related deaths in children, with tumors essentially refractory to existing treatments. Here, we describe the use of conventional and advanced in vivo magnetic resonance imaging (MRI) techniques to assess a novel orthotopic xenograft pGBM mouse (IC-3752GBM patient-derived culture) model, and to monitor the effects of the anti-cancer agent OKN-007 as an inhibitor of pGBM tumor growth. Immunohistochemistry support data is also presented for cell proliferation and tumor growth signaling. OKN-007 was found to significantly decrease tumor volumes (p<0.05) and increase animal survival (p<0.05) in all OKN-007-treated mice compared to untreated animals. In a responsive cohort of treated animals, OKN-007 was able to significantly decrease tumor volumes (p<0.0001), increase survival (p<0.001), and increase diffusion (p<0.01) and perfusion rates (p<0.05). OKN-007 also significantly reduced lipid tumor metabolism in responsive animals [(Lip1.3 and Lip0.9)-to-creatine ratio (p<0.05)], as well as significantly decrease tumor cell proliferation (p<0.05) and microvessel density (p<0.05). Furthermore, in relationship to the PDGFRα pathway, OKN-007 was able to significantly decrease SULF2 (p<0.05) and PDGFR-α (platelet-derived growth factor receptor-α) (p<0.05) immunoexpression, and significantly increase decorin expression (p<0.05) in responsive mice. This study indicates that OKN-007 may be an effective anti-cancer agent for some patients with pGBMs by inhibiting cell proliferation and angiogenesis, possibly via the PDGFRα pathway, and could be considered as an additional therapy for pediatric brain tumor patients.

MRI methods for the evaluation of high intensity focused ultrasound tumor treatment: Current status and future needs

Thermal ablation with high intensity focused ultrasound (HIFU) is an emerging noninvasive technique for the treatment of solid tumors. HIFU treatment of malignant tumors requires accurate treatment planning, monitoring and evaluation, which can be facilitated by performing the procedure in an MR-guided HIFU system. The MR-based evaluation of HIFU treatment is most often restricted to contrast-enhanced T1 -weighted imaging, while it has been shown that the non-perfused volume may not reflect the extent of nonviable tumor tissue after HIFU treatment. There are multiple studies in which more advanced MRI methods were assessed for their suitability for the evaluation of HIFU treatment. While several of these methods seem promising regarding their sensitivity to HIFU-induced tissue changes, there is still ample room for improvement of MRI protocols for HIFU treatment evaluation. In this review article, we describe the major acute and delayed effects of HIFU treatment. For each effect, the MRI methods that have been-or could be-used to detect the associated tissue changes are described. In addition, the potential value of multiparametric MRI for the evaluation of HIFU treatment is discussed. The review ends with a discussion on future directions for the MRI-based evaluation of HIFU treatment.

Quantitative radiology: applications to oncology

Oncologists, clinician-scientists, and basic scientists collect computed tomography, magnetic resonance, and positron emission tomography images in the process of caring for patients, managing clinical trials, and investigating cancer biology. As we have developed more sophisticated means for noninvasively delineating and characterizing neoplasms, these image data have come to play a central role in oncology. In parallel, the increasing complexity and volume of these data have necessitated the development of quantitative methods for assessing tumor burden, and by proxy, disease-free survival.

Personalized radiotherapy: concepts, biomarkers and trial design

In the past decade, and pointing onwards to the immediate future, clinical radiotherapy has undergone considerable developments, essentially including technological advances to sculpt radiation delivery, the demonstration of the benefit of adding concomitant cytotoxic agents to radiotherapy for a range of tumour types and, intriguingly, the increasing integration of targeted therapeutics for biological optimization of radiation effects. Recent molecular and imaging insights into radiobiology will provide a unique opportunity for rational patient treatment, enabling the parallel design of next-generation trials that formally examine the therapeutic outcome of adding targeted drugs to radiation, together with the critically important assessment of radiation volume and dose-limiting treatment toxicities. In considering the use of systemic agents with presumed radiosensitizing activity, this may also include the identification of molecular, metabolic and imaging markers of treatment response and tolerability, and will need particular attention on patient eligibility. In addition to providing an overview of clinical biomarker studies relevant for personalized radiotherapy, this communication will highlight principles in addressing clinical evaluation of combined-modality-targeted therapeutics and radiation. The increasing number of translational studies that bridge large-scale omics sciences with quality-assured phenomics end points-given the imperative development of open-source data repositories to allow investigators the access to the complex data sets-will enable radiation oncology to continue to position itself with the highest level of evidence within existing clinical practice.

Early changes in apparent diffusion coefficient as an indicator of response to sorafenib in hepatocellular carcinoma

OBJECTIVE

The relationship between apparent diffusion coefficient (ADC) and chemotherapy has been established. However, whether ADC could be considered as a measure for monitoring response to sorafenib in hepatocellular carcinoma (HCC) has not been demonstrated. This study was to investigate the ADC changes of advanced HCC under sorafenib treatment.

METHODS

Athymic mice with HepG2 xenografts were allocated to two groups: control and sorafenib (40 mg/kg, bid). T2 and diffusion images were acquired at each time point (0, 10, 14, and 18 d post-therapy). Tumor volume and changes in ADC were calculated.

RESULTS

Tumor volumes on Days 10, 14, and 18 after treatment showed significant decreases in the sorafenib-treated group compared with the control. Pretreatment ADC values were not significantly different between the control and treated groups. A slow increase in ADC in the peripheral zone of tumors appeared in the treated group, which was significantly higher compared with the control group on Days 10, 14, and 18. In the central part of tumors on Day 10 after treatment, an increase in ADC appeared in the treated and control groups, the ADC of the control group being significantly lower compared with the treated tumors. From Day 10 to Day 14, the ADC map showed a progressive decrease in the central region of tumors in the treated and control groups. However, this change is more significant in the treated groups.

CONCLUSIONS

Early changes in mean ADC correlated with sorafenib treatment in HCC, which are promising indicators for predicting sorafenib response in this carcinoma.

Multimodality imaging to predict response to systemic treatment in patients with advanced colorectal cancer

Aim

Aim of this study was to investigate the potential of ¹⁸F-FDG PET, diffusion weighted imaging (DWI) and susceptibility-weighted (T2*) MRI to predict response to systemic treatment in patients with colorectal liver metastases. The predictive values of pretreatment measurements and of early changes one week after start of therapy, were evaluated.

Methods

Imaging was performed prior to and one week after start of first line chemotherapy in 39 patients with colorectal liver metastases. ¹⁸F-FDG PET scans were performed on a PET/CT scanner and DWI and T2* were performed on a 1.5T MR scanner. The maximum standardized uptake values (SUV), total lesion glycolysis (TLG), apparent diffusion coefficient (ADC) and T2* value were assessed in the same lesions. Up to 5 liver metastases per patient were analyzed. Outcome measures were progression free survival (PFS), overall survival (OS) and size response.

Results

Pretreatment, high SUV_max, high TLG, low ADC and high T2* were associated with a shorter OS. Low pretreatment ADC value was associated with shorter PFS. After 1 week a significant drop in SUV_max and rise in ADC were observed. The drop in SUV was correlated with the rise in ADC (r=-0.58, p=0.002). Neither change in ADC nor in SUV was predictive of PFS or OS. T2* did not significantly change after start of treatment.

Conclusion

Pretreatment SUV_max, TLG, ADC, and T2* values in colorectal liver metastases are predictive of patient outcome. Despite sensitivity of DWI and ¹⁸F-FDG PET for early treatment effects, change in these parameters was not predictive of long term outcome.

Functional MRI and CT biomarkers in oncology

Imaging biomarkers derived from MRI or CT describe functional properties of tumours and normal tissues. They are finding increasing numbers of applications in diagnosis, monitoring of response to treatment and assessment of progression or recurrence. Imaging biomarkers also provide scope for assessment of heterogeneity within and between lesions. A wide variety of functional parameters have been investigated for use as biomarkers in oncology. Some imaging techniques are used routinely in clinical applications while others are currently restricted to clinical trials or preclinical studies. Apparent diffusion coefficient, magnetization transfer ratio and native T1 relaxation time provide information about structure and organization of tissues. Vascular properties may be described using parameters derived from dynamic contrast-enhanced MRI, dynamic contrast-enhanced CT, transverse relaxation rate (R2*), vessel size index and relative blood volume, while magnetic resonance spectroscopy may be used to probe the metabolic profile of tumours. This review describes the mechanisms of contrast underpinning each technique and the technical requirements for robust and reproducible imaging. The current status of each biomarker is described in terms of its validation, qualification and clinical applications, followed by a discussion of the current limitations and future perspectives.

Integrated whole body MR/PET: where are we?

Whole body integrated magnetic resonance imaging (MR)/positron emission tomography (PET) imaging systems have recently become available for clinical use and are currently being used to explore whether the combined anatomic and functional capabilities of MR imaging and the metabolic information of PET provide new insight into disease phenotypes and biology, and provide a better assessment of oncologic diseases at a lower radiation dose than a CT. This review provides an overview of the technical background of combined MR/PET systems, a discussion of the potential advantages and technical challenges of hybrid MR/PET instrumentation, as well as collection of possible solutions. Various early clinical applications of integrated MR/PET are also addressed. Finally, the workflow issues of integrated MR/PET, including maximizing diagnostic information while minimizing acquisition time are discussed.

Differential Diagnosis of Malignant Biliary Tract Cancer from Benign Tissues using Apparent Diffusion Coefficient Measurements with Diffusion Weighted Imaging in Asians

BACKGROUND

The aim of this meta-analysis was to assess the efficacy of the apparent diffusion coefficient (ADC) value of diffusion-weighted MRI (DWI) for differentiating biliary tract cancer (BTC) from benign biliary tract diseases in Asians.

MATERIALS AND METHODS

We systematically searched Embase and PubMed prior to December 2014. Eight studies conducted in Asians met our predetermined inclusion criteria.

RESULTS

Our meta-analysis results showed that ADC values in BTC tissues were significantly lower than in benign biliary tract tissues (SMD = -1.54, 95%CI: -1.75~-1.33, P<0.001). Subgroup analysis based on the MRI machine type showed that the ADC values were consistent, accurate and reliable in the diagnosis of BTC when comparing cancer tissue vs. benign tissue under the Siemens 1.5 T/3.0 T, Philips 1.5 T/3.0 T, GE 1.5 T, and Toshiba 1.5 T types, respectively (all P<0.05). Further, ADC values were still consistent and accurate in the differential diagnosis of BTC under the b value of 800 and 1000 s/mm2 (all P<0.05).

CONCLUSIONS

Our findings supported potential clinical applications of DWI ADC values in differentiating BTC from benign biliary tract diseases in Asians.

Monitoring the response of bone metastases to treatment with Magnetic Resonance Imaging and nuclear medicine techniques: a review and position statement by the European Organisation for Research and Treatment of Cancer imaging group

Assessment of the response to treatment of metastases is crucial in daily oncological practice and clinical trials. For soft tissue metastases, this is done using computed tomography (CT), Magnetic Resonance Imaging (MRI) or Positron Emission Tomography (PET) using validated response evaluation criteria. Bone metastases, which frequently represent the only site of metastases, are an exception in response assessment systems, because of the nature of the fixed bony defects, their complexity, which ranges from sclerotic to osteolytic and because of the lack of sensitivity, specificity and spatial resolution of the previously available bone imaging methods, mainly bone scintigraphy. Techniques such as MRI and PET are able to detect the early infiltration of the bone marrow by cancer, and to quantify this infiltration using morphologic images, quantitative parameters and functional approaches. This paper highlights the most recent developments of MRI and PET, showing how they enable early detection of bone lesions and monitoring of their response. It reviews current knowledge, puts the different techniques into perspective, in terms of indications, strengths, weaknesses and complementarity, and finally proposes recommendations for the choice of the most adequate imaging technique.

From PET/CT to PET/MRI: advances in instrumentation and clinical applications

Multimodality imaging of positron emission tomography/computed tomography (PET/CT) provides both metabolic information and the anatomic structure, which is significantly superior to either PET or CT alone and has greatly improved its clinical applications. Because of the higher soft-tissue contrast of magnetic resonance imaging (MRI) and no extra ionizing radiation, PET/MRI imaging is the hottest topic currently. PET/MRI is swiftly making its way into clinical practice. However, it has many technical difficulties to overcome, such as photomultiplier tubes, which cannot work properly in a magnetic field, and the inability to provide density information on the object for attenuation correction. This paper introduces the technique process of PET/MRI and summarizes its clinical applications, including imaging in oncology, neurology, and cardiology.

Understanding the tumor microenvironment and radioresistance by combining functional imaging with global gene expression

The objective of this review is to present an argument for performing joint analyses between functional imaging with global gene expression studies. The reason for making this link is that tumor microenvironmental influences on functional imaging can be uncovered. Such knowledge can lead to (1) more informed decisions regarding how to use functional imaging to guide therapy and (2) discovery of new therapeutic targets. As such, this approach could lead to identification of patients who need aggressive treatment tailored toward the phenotype of their tumor vs those who could be spared treatment that carries risk for more normal tissue complications. Only a handful of papers have been published on this topic thus far, but all show substantial promise.

Diffusion-weighted magnetic resonance imaging in the prediction and assessment of chemotherapy outcome in liver metastases

PURPOSE

This study assessed the capability of magnetic resonance (MR) diffusion-weighted imaging (DwI) with measurement of apparent diffusion coefficient (ADC) in both predicting and evaluating the response to chemotherapy (CHT) of liver metastases by itself and along with preliminary dimensional assessment.

METHODS AND MATERIALS

Patients affected by liver metastases from cancers of the digestive tract and breast were prospectively enrolled and underwent computed tomography and MR-DwI before CHT (time 0) and 20-25 days after the beginning of the second cycle (time 3). Moreover, MR-DwI was performed 10-15 (time 1) and 20-25 days (time 2) after the beginning of the first cycle. Maximum diameter and mean ADC value (×10(-3) mm(2)/s) of metastases were evaluated. Lesions were classified as progressive disease (PD), stable disease (SD) or partial response (PR) according to dimensional changes between time 0 and time 3, following RECIST 1.1 indications. Clinically, PD lesions were defined as nonresponding (NR), and SD and PR lesions as responding (R). Analysis of variance and ROC analyses were performed (significance at p < 0.05).

RESULTS

Eighty-six metastases (33 patients) were classified as follows: 15 PD, 39 SD and 32 PR without significant differences in mean ADC values among the groups before CHT and at all corresponding times. The mean ADC values of SD and PR groups at times 1 (respectively 1.66 ± 0.36 and 1.59 ± 0.23), 2 (1.72 ± 0.42 and 1.68 ± 0.37) and 3 (1.86 ± 0.44 and 1.73 ± 0.39) were significantly higher than the corresponding values at time 0 (1.50 ± 0.30 and 1.39 ± 0.33). An accurate cutoff value of ADC increase or diameter decrease for the early identification of R or NR lesions was not found.

CONCLUSION

The pretreatment ADC value of a liver metastasis does not seem useful in predicting the CHT outcome. A trend towards early ADC increase, alone or occurring with dimensional decrease, may be a good indicator of a responding lesion.

Imaging angiogenesis, inflammation, and metastasis in the tumor microenvironment with magnetic resonance imaging

With the development of new imaging techniques, the potential for probing the molecular, cellular, and structural components of the tumor microenvironment in situ has increased dramatically. A multitude of imaging modalities have been successfully employed to probe different aspects of the tumor microenvironment, including expression of molecules, cell motion, cellularity, vessel permeability, vascular perfusion, metabolic and physiological changes, apoptosis, and inflammation. This chapter focuses on the most recent advances in magnetic resonance imaging methods, which offer a number of advantages over other methodologies, including high spatial resolution and the use of nonionizing radiation, as well as the use of such methods in the context of primary and secondary brain tumors. It also highlights how they can be used to assess the molecular and cellular changes in the tumor microenvironment in response to therapy.

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors

BACKGROUND AND PURPOSE

Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features.

MATERIALS AND METHODS

This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data.

RESULTS

ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix.

CONCLUSIONS

Support vector machine-based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology.

Micro-RNAs as potential new molecular biomarkers in oncology: have they reached relevance for the clinical imaging sciences?

Minimally invasive biomarkers for early cancer detection and monitoring of personalized therapies are of high importance to further improve prognosis in oncological disease. MicroRNAs (miRNAs) are small regulatory RNAs in humans and play a key role in carcinogenesis. In recent years they have emerged as promising biomarkers in oncology. miRNA profiling has demonstrated its capacity for sub-classifying tumors and monitoring of therapeutic effects. Different expression profiles of miRNAs in cancer and the stability of circulating miRNAs potentially provide a clinically accessible molecular monitoring tool of malignant tissues and its response to therapies. Clinical imaging including the modalities PET/CT and MRI is well established for characterizing tumor tissue and sub-classifying morphological, metabolic or vascular treatment response in cancer. Sophisticated clinical imaging biomarkers for cancer detection and monitoring should now been correlatively applied to further validate the potential of miRNAs as oncologic biomarkers for the clinic.

Response to chemotherapy in gastric adenocarcinoma with diffusion-weighted MRI and (18) F-FDG-PET/CT: correlation of apparent diffusion coefficient and partial volume corrected standardized uptake value with histological tumor regression grade

PURPOSE

To assess whether changes in diffusion-weighted MRI (DW-MRI) and (18) F-fluoro-2-deoxyglucose positron emission tomography/computed tomography ((18) F-FDG PET/CT), correlate with treatment response to neoadjuvant therapy (NT), as expressed by tumor regression grade (TRG), from locally advanced gastric adenocarcinoma (GA).

MATERIALS AND METHODS

Seventeen patients underwent both DW-MRI and (18) F-FDG-PET/CT scans before and after the end of NT. Apparent diffusion coefficient (ADC) and mean standardized uptake value (SUV) corrected for partial volume effect (PVC-SUVBW-mean ) were evaluated and compared with histopathological TRG.

RESULTS

Pre- and post-NT and percentage changes for ADC and PVC-SUVBW-mean were assessed. Post-NT ADC and ΔADC showed a significant inverse correlation with TRG (r = -0.71; P = 0.0011 and r = -0.78; P = 0.00020, respectively) and significant differences in their mean values were found between responders (TRG 1-2-3) and nonresponders (TRG 4-5) (P = 0.0009; P = 0.000082, respectively). No correlations with TRG were found for pre-NT ADC and for all PVC-SUVBW-mean values as well as between ΔADC and Δ PVC-SUVBW-mean .

CONCLUSION

DW-MRI seems more accurate than (18) F-FDG-PET/CT and ADC modifications may represent a reproducible tool to assess tumor response for GA.

Comparison of different MRI sequences in lesion detection and early response evaluation of diffuse large B-cell lymphoma--a whole-body MRI and diffusion-weighted imaging study

To compare different MRI sequences for the detection of lesions and the evaluation of response to chemotherapy in patients with diffuse large B-cell lymphoma (DLBCL), 18 patients with histology-confirmed DLBCL underwent 3-T MRI scanning prior to and 1 week after chemotherapy. The MRI sequences included T1-weighted pre- and post-contrast, T2 -weighted with and without fat suppression, and a single-shot echo-planar diffusion-weighted imaging (DWI) with two b values (0 and 800 s/mm(2)). Conventional MRI sequence comparisons were performed using the contrast ratio between tumor and normal vertebral body instead of signal intensity. The apparent diffusion coefficient (ADC) of the tumor was measured directly on the parametric ADC map. The tumor volume was used as a reference for the evaluation of chemotherapy response. The mean tumor volume was 374 mL at baseline, and decreased by 65% 1 week after chemotherapy (p < 0.01). The T2 -weighted image with fat suppression showed a significantly higher contrast ratio compared with images from all other conventional MRI sequences, both before and after treatment (p < 0.01, respectively). The contrast ratio of the T2 -weighted image with fat suppression decreased significantly (p < 0.01), and that of the T1 -weighted pre-contrast image increased significantly (p < 0.01), after treatment. However, there was no correlation between the change in contrast ratio and tumor volume. The mean ADC value was 0.68 × 10(-3) mm(2)/s at baseline; it increased by 89% after chemotherapy (p < 0.001), and the change in ADC value correlated with the change in tumor volume (r = 0.66, p < 0.01). The baseline ADC value also correlated inversely with the percentage change in ADC after treatment (r = -0.62, p < 0.01). In conclusion, this study indicates that T2-weighted imaging with fat suppression is the best conventional sequence for the detection of lesions and evaluation of the efficacy of chemotherapy in DLBCL. DWI with ADC mapping is an imaging modality with both diagnostic and prognostic value that could complement conventional MRI.

Predicting outcomes in radiation oncology--multifactorial decision support systems

With the emergence of individualized medicine and the increasing amount and complexity of available medical data, a growing need exists for the development of clinical decision-support systems based on prediction models of treatment outcome. In radiation oncology, these models combine both predictive and prognostic data factors from clinical, imaging, molecular and other sources to achieve the highest accuracy to predict tumour response and follow-up event rates. In this Review, we provide an overview of the factors that are correlated with outcome-including survival, recurrence patterns and toxicity-in radiation oncology and discuss the methodology behind the development of prediction models, which is a multistage process. Even after initial development and clinical introduction, a truly useful predictive model will be continuously re-evaluated on different patient datasets from different regions to ensure its population-specific strength. In the future, validated decision-support systems will be fully integrated in the clinic, with data and knowledge being shared in a standardized, instant and global manner.