Prognostic value of dynamic MR imaging for non-small-cell lung cancer patients after chemoradiotherapy

Lung Magnetic Resonance Imaging: Technical Advancements and Clinical Applications

ABSTRACT

Since lung magnetic resonance imaging (MRI) became clinically available, limited clinical utility has been suggested for applying MRI to lung diseases. Moreover, clinical applications of MRI for patients with lung diseases or thoracic oncology may vary from country to country due to clinical indications, type of health insurance, or number of MR units available. Because of this situation, members of the Fleischner Society and of the Japanese Society for Magnetic Resonance in Medicine have published new reports to provide appropriate clinical indications for lung MRI. This review article presents a brief history of lung MRI in terms of its technical aspects and major clinical indications, such as (1) what is currently available, (2) what is promising but requires further validation or evaluation, and (3) which developments warrant research-based evaluations in preclinical or patient studies. We hope this article will provide Investigative Radiology readers with further knowledge of the current status of lung MRI and will assist them with the application of appropriate protocols in routine clinical practice.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

ADVANCES IN KNOWLEDGE

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

Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging

Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.

Radiomics for Predicting Lung Cancer Outcomes Following Radiotherapy: A Systematic Review

Lung cancer's radiomic phenotype may potentially inform clinical decision-making with respect to radical radiotherapy. At present there are no validated biomarkers available for the individualisation of radical radiotherapy in lung cancer and the mortality rate of this disease remains the highest of all other solid tumours. MEDLINE was searched using the terms 'radiomics' and 'lung cancer' according to the Preferred Reporting Items for Systematic Reviews and Met-Analyses (PRISMA) guidance. Radiomics studies were defined as those manuscripts describing the extraction and analysis of at least 10 quantifiable imaging features. Only those studies assessing disease control, survival or toxicity outcomes for patients with lung cancer following radical radiotherapy ± chemotherapy were included. Study titles and abstracts were reviewed by two independent reviewers. The Radiomics Quality Score was applied to the full text of included papers. Of 244 returned results, 44 studies met the eligibility criteria for inclusion. End points frequently reported were local (17%), regional (17%) and distant control (31%), overall survival (79%) and pulmonary toxicity (4%). Imaging features strongly associated with clinical outcomes include texture features belonging to the subclasses Gray level run length matrix, Gray level co-occurrence matrix and kurtosis. The median cohort size for model development was 100 (15-645); in the 11 studies with external validation in a separate independent population, the median cohort size was 84 (21-295). The median number of imaging features extracted was 184 (10-6538). The median Radiomics Quality Score was 11% (0-47). Patient-reported outcomes were not incorporated within any studies identified. No studies externally validated a radiomics signature in a registered prospective study. Imaging-derived indices attained through radiomic analyses could equip thoracic oncologists with biomarkers for treatment response, patterns of failure, normal tissue toxicity and survival in lung cancer. Based on routine scans, their non-invasive nature and cost-effectiveness are major advantages over conventional pathological assessment. Improved tools are required for the appraisal of radiomics studies, as significant barriers to clinical implementation remain, such as standardisation of input scan data, quality of reporting and external validation of signatures in randomised, interventional clinical trials.

Dynamic Contrast-enhanced Area-detector CT vs Dynamic Contrast-enhanced Perfusion MRI vs FDG-PET/CT: Comparison of Utility for Quantitative Therapeutic Outcome Prediction for NSCLC Patients Undergoing Chemoradiotherapy

PURPOSE

To directly compare the utility for therapeutic outcome prediction of dynamic first-pass contrast-enhanced (CE)-perfusion area-detector computed tomography (ADCT), MR imaging assessed with the same mathematical method and 2-[fluorine-18]-fluoro-2-deoxy-d-glucose-positron emission tomography combined with CT (PET/CT) for non-small cell lung cancer (NSCLC) patients treated with chemoradiotherapy.

MATERIALS AND METHODS

Forty-three consecutive stage IIIB NSCLC patients, consisting of 25 males (mean age ± standard deviation: 66.6 ± 8.7 years) and 18 females (66.4 ± 8.2 years) underwent PET/CT, dynamic CE-perfusion ADCT and MR imaging, chemoradiotherapy, and follow-up examination. In each patient, total, pulmonary arterial, and systemic arterial perfusions were calculated from both perfusion data and SUV_max on PET/CT, assessed for each targeted lesion, and averaged to determine final values. Receiver operating characteristics analyses were performed to compare the utility for distinguishing responders from non-responders using Response Evaluation Criteria in Solid Tumor (RECIST) 1.1 criteria. Overall survival (OS) assessed with each index were compared between two groups by means of the Kaplan-Meier method followed by the log-rank test.

RESULTS

Area under the curve (Az) for total perfusion on ADCT was significantly larger than that of pulmonary arterial perfusion (P < 0.05). Az of total perfusion on MR imaging was significantly larger than that of pulmonary arterial perfusion (P < 0.05). Mean OS of responder and non-responder groups were significantly different for total and systemic arterial (P < 0.05) perfusion.

CONCLUSION

Dynamic first-pass CE-perfusion ADCT and MR imaging as well as PET/CT are useful for early prediction of treatment response by NSCLC patients treated with chemoradiotherapy.

SEOM-SERAM-SEMNIM guidelines on the use of functional and molecular imaging techniques in advanced non-small-cell lung cancer

Imaging in oncology is an essential tool for patient management but its potential is being profoundly underutilized. Each of the techniques used in the diagnostic process also conveys functional information that can be relevant in treatment decision making. New imaging algorithms and techniques enhance our knowledge about the phenotype of the tumor and its potential response to different therapies. Functional imaging can be defined as the one that provides information beyond the purely morphological data, and include all the techniques that make it possible to measure specific physiological functions of the tumor, whereas molecular imaging would include techniques that allow us to measure metabolic changes. Functional and molecular techniques included in this document are based on multi-detector computed tomography (CT), 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET), magnetic resonance imaging (MRI), and hybrid equipments, integrating PET with CT (PET/CT) or MRI (PET-MRI). Lung cancer is one of the most frequent and deadly tumors although survival is increasing thanks to advances in diagnostic methods and new treatments. This increased survival poises challenges in terms of proper follow-up and definitions of response and progression, as exemplified by immune therapy-related pseudoprogression. In this consensus document, the use of functional and molecular imaging techniques will be addressed to exploit their current potential and explore future applications in the diagnosis, evaluation of response and detection of recurrence of advanced NSCLC.

SEOM-SERAM-SEMNIM guidelines on the use of functional and molecular imaging techniques in advanced non-small-cell lung cancer

Imaging in oncology is an essential tool for patient management but its potential is being profoundly underutilized. Each of the techniques used in the diagnostic process also conveys functional information that can be relevant in treatment decision-making. New imaging algorithms and techniques enhance our knowledge about the phenotype of the tumor and its potential response to different therapies. Functional imaging can be defined as the one that provides information beyond the purely morphological data, and include all the techniques that make it possible to measure specific physiological functions of the tumor, whereas molecular imaging would include techniques that allow us to measure metabolic changes. Functional and molecular techniques included in this document are based on multi-detector computed tomography (CT), 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET), magnetic resonance imaging (MRI), and hybrid equipments, integrating PET with CT (PET/CT) or MRI (PET-MRI). Lung cancer is one of the most frequent and deadly tumors although survival is increasing thanks to advances in diagnostic methods and new treatments. This increased survival poises challenges in terms of proper follow-up and definitions of response and progression, as exemplified by immune therapy-related pseudoprogression. In this consensus document, the use of functional and molecular imaging techniques will be addressed to exploit their current potential and explore future applications in the diagnosis, evaluation of response and detection of recurrence of advanced NSCLC.

Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading

BACKGROUND

Presurgical glioma grading by dynamic contrast-enhanced MRI (DCE-MRI) has unresolved issues.

PURPOSE

The aim of this study was to investigate the ability of textural features derived from pharmacokinetic model-based or model-free parameter maps of DCE-MRI in discriminating between different grades of gliomas, and their correlation with pathological index.

STUDY TYPE

Retrospective.

SUBJECTS

Forty-two adults with brain gliomas.

FIELD STRENGTH/SEQUENCE

3.0T, including conventional anatomic sequences and DCE-MRI sequences (variable flip angle T1-weighted imaging and three-dimensional gradient echo volumetric imaging).

ASSESSMENT

Regions of interest on the cross-sectional images with maximal tumor lesion. Five commonly used textural features, including Energy, Entropy, Inertia, Correlation, and Inverse Difference Moment (IDM), were generated.

RESULTS

All textural features of model-free parameters (initial area under curve [IAUC], maximal signal intensity [Max SI], maximal up-slope [Max Slope]) could effectively differentiate between grade II (n = 15), grade III (n = 13), and grade IV (n = 14) gliomas (P < 0.05). Two textural features, Entropy and IDM, of four DCE-MRI parameters, including Max SI, Max Slope (model-free parameters), vp (Extended Tofts), and vp (Patlak) could differentiate grade III and IV gliomas (P < 0.01) in four measurements. Both Entropy and IDM of Patlak-based K^trans and vp could differentiate grade II (n = 15) from III (n = 13) gliomas (P < 0.01) in four measurements. No textural features of any DCE-MRI parameter maps could discriminate between subtypes of grade II and III gliomas (P < 0.05). Both Entropy and IDM of Extended Tofts- and Patlak-based vp showed highest area under curve in discriminating between grade III and IV gliomas. However, intraclass correlation coefficient (ICC) of these features revealed relatively lower inter-observer agreement. No significant correlation was found between microvascular density and textural features, compared with a moderate correlation found between cellular proliferation index and those features.

DATA CONCLUSION

Textural features of DCE-MRI parameter maps displayed a good ability in glioma grading.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1099-1111.

Contrast-enhanced CT- and MRI-based perfusion assessment for pulmonary diseases: basics and clinical applications

Assessment of regional pulmonary perfusion as well as nodule and tumor perfusions in various pulmonary diseases are currently performed by means of nuclear medicine studies requiring radioactive macroaggregates, dual-energy computed tomography (CT), and dynamic first-pass contrast-enhanced perfusion CT techniques and unenhanced and dynamic first-pass contrast enhanced perfusion magnetic resonance imaging (MRI), as well as time-resolved three-dimensional or four-dimensional contrast-enhanced magnetic resonance angiography (MRA). Perfusion scintigraphy, single-photon emission tomography (SPECT) and SPECT fused with CT have been established as clinically available scintigraphic methods; however, they are limited by perfusion information with poor spatial resolution and other shortcomings. Although positron emission tomography with 15O water can measure absolute pulmonary perfusion, it requires a cyclotron for generation of a tracer with an extremely short half-life (2 min), and can only be performed for academic purposes. Therefore, clinicians are concentrating their efforts on the application of CT-based and MRI-based quantitative and qualitative perfusion assessment to various pulmonary diseases. This review article covers 1) the basics of dual-energy CT and dynamic first-pass contrast-enhanced perfusion CT techniques, 2) the basics of time-resolved contrast-enhanced MRA and dynamic first-pass contrast-enhanced perfusion MRI, and 3) clinical applications of contrast-enhanced CT- and MRI-based perfusion assessment for patients with pulmonary nodule, lung cancer, and pulmonary vascular diseases. We believe that these new techniques can be useful in routine clinical practice for not only thoracic oncology patients, but also patients with different pulmonary vascular diseases.

Dynamic contrast-enhanced perfusion area-detector CT assessed with various mathematical models: Its capability for therapeutic outcome prediction for non-small cell lung cancer patients with chemoradiotherapy as compared with that of FDG-PET/CT

PURPOSE

To directly compare the capability of dynamic first-pass contrast-enhanced (CE-) perfusion area-detector CT (ADCT) and PET/CT for early prediction of treatment response, disease progression and overall survival of non-small cell carcinoma (NSCLC) patients treated with chemoradiotherapy.

MATERIALS AND METHODS

Fifty-three consecutive Stage IIIB NSCLC patients who had undergone PET/CT, dynamic first-pass CE-perfusion ADCT, chemoradiotherapy, and follow-up examination were enrolled in this study. They were divided into two groups: 1) complete or partial response (CR+PR) and 2) stable or progressive disease (SD+PD). Pulmonary arterial and systemic arterial perfusions and total perfusion were assessed at targeted lesions with the dual-input maximum slope method, permeability surface and distribution volume with the Patlak plot method, tumor perfusion with the single-input maximum slope method, and SUV_max, and results were averaged to determine final values for each patient. Next, step-wise regression analysis was used to determine which indices were the most useful for predicting therapeutic effect. Finally, overall survival of responders and non-responders assessed by using the indices that had a significant effect on prediction of therapeutic outcome was statistically compared.

RESULTS

The step-wise regression test showed that therapeutic effect (r²=0.63, p=0.01) was significantly affected by the following three factors in order of magnitude of impact: systemic arterial perfusion, total perfusion, and SUV_max. Mean overall survival showed a significant difference for total perfusion (p=0.003) and systemic arterial perfusion (p=0.04).

CONCLUSION

Dynamic first-pass CE-perfusion ADCT as well as PET/CT are useful for treatment response prediction in NSCLC patients treated with chemoradiotherapy.

Value of intravoxel incoherent motion and dynamic contrast-enhanced MRI for predicting the early and short-term responses to chemoradiotherapy in nasopharyngeal carcinoma

The aim of the study was to investigate the value of intravoxel incoherent motion diffusion-weighted magnetic resonance imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the early and short-term responses to chemoradiotherapy (CRT) in patients with nasopharyngeal carcinoma (NPC).Forty-three NPC patients underwent IVIM-DWI and DCE-MRI at baseline (pretreatment) and after the first cycle of induction chemotherapy (posttreatment). Based on whether locoregional lesions were identified, patients were divided into the residual and nonresidual groups at the end of CRT and into the good-responder and poor-responder groups 6 months after the end of CRT. The pretreatment and posttreatment IVIM-DWI parameters (ADC, D, D*, and f) and DCE-MRI parameters (K, Kep, and Ve) values and their percentage changes (Δ%) were compared between the residual and nonresidual groups and between the good-responder and poor-responder groups.None of perfusion-related parametric values derived from either DCE-MRI or IVIM-DWI showed significant differences either between the residual and nonresidual groups or between the good-responder and poor-responder groups. The nonresidual group exhibited lower pre-ADC, lower pre-D, and higher Δ%D values than did the residual group (all P <0.05). The good-responder group had lower pre-D and pre-ADC values than did the poor-responder group (both P <0.05). Based on receiver operating characteristic (ROC) curve analysis, pre-D had the highest area under the curve in predicting both the early and short-term responses to CRT for NPC patients (0.817 and 0.854, respectively).IVIM-DWI is more valuable than DCE-MRI in predicting the early and short-term response to CRT for NPC, and furthermore diffusion-related IVIM-DWI parameters (pre-ADC, pre-D, and Δ%D) are more powerful than perfusion-related parameters derived from both IVIM-DWI and DCE-MRI.

Comparison of CT volumetric measurement with RECIST response in patients with lung cancer

PURPOSE

To examine the correlations between uni-dimensional RECIST and volumetric measurements in patients with lung adenocarcinoma and to assess their association with overall survival (OS) and progression-free survival (PFS).

MATERIALS AND METHODS

In this study of patients receiving chemotherapy for lung cancer in the setting of a clinical trial, response was prospectively evaluated using RECIST 1.0. Retrospectively, volumetric measurements were recorded and response was assessed by two different volumetric methods at each followup CT scan using a semi-automated segmentation algorithm. We subsequently evaluated the correlation between the uni-dimensional RECIST measurements and the volumetric measurements and performed landmark analyses for OS and PFS at the completion of the first and second follow-ups. Kaplan-Meier curves together with log-rank tests were used to evaluate the association between the different response criteria and patient outcome.

RESULTS

Forty-two patients had CT scans at baseline, after the first follow up scan and second followup scan, and then every 8 weeks. The uni-dimensional RECIST measurements and volumetric measurements were strongly correlated, with a Spearman correlation coefficient (ρ) of 0.853 at baseline, ρ=0.861 at the first followup, ρ=0.843 at the 2nd followup, and ρ=0.887 overall between-subject. On first follow-up CT, partial responders and non responders as assessed by an "ellipsoid" volumetric criteria showed a significant difference in OS (p=0.008, 1-year OS of 70% for partial responders and 46% for non responders). There was no difference between the groups when assessed by RECIST criteria on first follow-up CT (p=0.841, 1-year OS rate of 64% for partial responders and 64% for non responders).

CONCLUSION

Volumetric response on first follow-up CT may better predict OS than RECIST response.

CLINICAL RELEVANCE STATEMENT

Assessment of tumor size and response is of utmost importance in clinical trials. Volumetric measurements may help to better predict OS than uni-dimensional RECIST criteria.

Dynamic contrast-enhanced perfusion area detector CT for non-small cell lung cancer patients: Influence of mathematical models on early prediction capabilities for treatment response and recurrence after chemoradiotherapy

PURPOSE

To determine the capability and influence of the mathematical method on dynamic contrast-enhanced (CE-) perfusion area detector CT (ADCT) for early prediction of treatment response as well as progression free and overall survival (PFS and OS) of non-small cell lung cancer (NSCLC) patients treated with chemoradiotherapy.

MATERIALS AND METHODS

Sixty-six consecutive stage III NSCLC patients underwent dynamic CE-perfusion ADCT examinations, chemoradiotherapy and follow-up examinations. Response Evaluation Criteria in Solid Tumors (RECIST) criteria were used to divide all patients into responders and non-responders. Differences in each of the indices for all targeted lesions between measurements obtained 2 weeks prior to the first and the third course of chemotherapy were determined for all patients. ROC analyses were employed to determine the capability of perfusion indices as markers for distinguishing RECIST responders from non-responders. To evaluate their capability for early prediction of therapeutic effect, OS of perfusion index-based responders and non-responders were compared by using the Kaplan-Meier method followed by log-rank test.

RESULTS

Area under the curve (Az) for total perfusion by means of the dual-input maximum slope method was significantly larger than that of pulmonary arterial perfusion using the same method (p=0.007) and of perfusion with the single-input maximum slope method (p=0.007). Mean OS demonstrated significantly difference between responder- and non-responder groups for total perfusion (p=0.02).

CONCLUSION

Mathematical models have significant influence on assessment for early prediction of treatment response, disease progression and overall survival using dynamic CE-perfusion ADCT for NSCLC patients treated with chemoradiotherapy.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.

Modern diagnostic and therapeutic interventional radiology in lung cancer

Imaging has an important role in the multidisciplinary management of primary lung cancer. This article reviews the current state-of-the-art imaging modalities used for the evaluation, staging and post-treatment follow-up and surveillance of lung cancers, and image-guided percutaneous techniques for biopsy to confirm the diagnosis and for local therapy in non-surgical candidates.

Lung cancer imaging

Lung cancer remains the leading cause of cancer-related deaths in the US. Imaging plays an important role in the diagnosis, staging, and follow-up evaluation of patients with lung cancer. With recent advances in technology, it is important to update and standardize the radiological practices in lung cancer evaluation. In this article, the authors review the main clinical applications of different imaging modalities and the most common radiological presentations of lung cancer.

State of the art: Response assessment in lung cancer in the era of genomic medicine

Tumor response assessment has been a foundation for advances in cancer therapy. Recent discoveries of effective targeted therapy for specific genomic abnormalities in lung cancer and their clinical application have brought revolutionary advances in lung cancer therapy and transformed the oncologist's approach to patients with lung cancer. Because imaging is a major method of response assessment in lung cancer both in clinical trials and practice, radiologists must understand the genomic alterations in lung cancer and the rapidly evolving therapeutic approaches to effectively communicate with oncology colleagues and maintain the key role in lung cancer care. This article describes the origin and importance of tumor response assessment, presents the recent genomic discoveries in lung cancer and therapies directed against these genomic changes, and describes how these discoveries affect the radiology community. The authors then summarize the conventional Response Evaluation Criteria in Solid Tumors and World Health Organization guidelines, which continue to be the major determinants of trial endpoints, and describe their limitations particularly in an era of genomic-based therapy. More advanced imaging techniques for lung cancer response assessment are presented, including computed tomography tumor volume and perfusion, dynamic contrast material-enhanced and diffusion-weighted magnetic resonance imaging, and positron emission tomography with fluorine 18 fluorodeoxyglucose and novel tracers. State-of-art knowledge of lung cancer biology, treatment, and imaging will help the radiology community to remain effective contributors to the personalized care of lung cancer patients.

Evaluating radiation-induced white matter changes in patients treated with stereotactic radiosurgery using diffusion tensor imaging: a pilot study

Stereotactic radiosurgery (SRS) has been an effective treatment method for brain tumors; however, few data are available regarding radiation-induced white matter (WM) damage by SRS. In this work, diffusion tensor imaging (DTI) was used to investigate WM changes following SRS. Fifteen patients with gliomas were enrolled, with prescription doses ranging 18-25 Gy. Patients were scanned with magnetic resonance imaging (MRI) including DTI before and after SRS. Diffusion tensors were calculated and fiber tracking was performed. Non-irradiated WM volumes and irradiated WM volumes receiving ≥ 12 Gy and ≥ Gy were contoured as volumes of interest (VOI). Apparent diffusion coefficient (〈D〉), fractional anisotropy (FA) and number of fibers (NF) were calculated and assessed using the Wilcoxon signed-rank test. Compared with those of non-irradiated VOIs, FA and NF decreased considerably after two months of SRS in the irradiated WM VOIs. The variation in (〈D〉 was however small and was not statistically significant. The preliminary results suggested that FA and NF might potentially be more sensitive indicators than (〈D〉 in measuring radiation-induced WM changes and DTI could be a valuable tool to assess radiation-induced WM changes in SRS. Although it is still preliminary, this pilot study may be useful to provide insights for future studies.

The potential for an enhanced role for MRI in radiation-therapy treatment planning

The exquisite soft-tissue contrast of magnetic resonance imaging (MRI) has meant that the technique is having an increasing role in contouring the gross tumor volume (GTV) and organs at risk (OAR) in radiation therapy treatment planning systems (TPS). MRI-planning scans from diagnostic MRI scanners are currently incorporated into the planning process by being registered to CT data. The soft-tissue data from the MRI provides target outline guidance and the CT provides a solid geometric and electron density map for accurate dose calculation on the TPS computer. There is increasing interest in MRI machine placement in radiotherapy clinics as an adjunct to CT simulators. Most vendors now offer 70 cm bores with flat couch inserts and specialised RF coil designs. We would refer to these devices as MR-simulators. There is also research into the future application of MR-simulators independent of CT and as in-room image-guidance devices. It is within the background of this increased interest in the utility of MRI in radiotherapy treatment planning that this paper is couched. The paper outlines publications that deal with standard MRI sequences used in current clinical practice. It then discusses the potential for using processed functional diffusion maps (fDM) derived from diffusion weighted image sequences in tracking tumor activity and tumor recurrence. Next, this paper reviews publications that describe the use of MRI in patient-management applications that may, in turn, be relevant to radiotherapy treatment planning. The review briefly discusses the concepts behind functional techniques such as dynamic contrast enhanced (DCE), diffusion-weighted (DW) MRI sequences and magnetic resonance spectroscopic imaging (MRSI). Significant applications of MR are discussed in terms of the following treatment sites: brain, head and neck, breast, lung, prostate and cervix. While not yet routine, the use of apparent diffusion coefficient (ADC) map analysis indicates an exciting future application for functional MRI. Although DW-MRI has not yet been routinely used in boost adaptive techniques, it is being assessed in cohort studies for sub-volume boosting in prostate tumors.

Analysis of parametric histogram from dynamic contrast-enhanced MRI: application in evaluating brain tumor response to radiotherapy

Dynamic contrast-enhanced MRI (DCE MRI) has been used to study tumor response to treatment for many years. In this study, the modified full width at half-maximum (mFWHM), calculated from the wash-in slope histogram, is proposed as a parameter for the evaluation of changes in tumor heterogeneity which respond to radiotherapy. Twenty-five patients with brain tumors were evaluated and divided into the nonresponder group (n = 11) and the responder group (n = 14) according to the Response Evaluation Criteria in Solid Tumors (RECIST). All selected tumors were evaluated by mFWHM ratios of post- to pre-therapy (the ratio was defined as the therapeutic mFWHM ratio, TMR). The changes in kurtosis of the histograms and the averaged K(trans) within a tumor were also calculated for comparison. The receiver operating characteristic analysis and Kaplan-Meier curves were used to examine the diagnosis ability. The TMR values were significantly higher in nonresponders than in responders (p < 0.001). When compared with the other two parameters, the proposed method also demonstrated better sensitivity and specificity. When adopting the TMR for the estimation of prognosis after therapy, there was a significant difference between the population survival curves. In conclusion, the derived mFWHM reflects tumor heterogeneity, and the ability to depict patient survival probability from TMR corresponds well with that from RECIST. The results reveal that, in brain tumors, progression may be exhibited not only by tumor size, but also by tumor heterogeneity.

Head and neck cancer as a model for advances in imaging prognosis, early assessment, and posttherapy evaluation

Novel noninvasive functional imaging methods are necessary to predict therapeutic outcome and thereby improve the ability to properly select patients for treatment with both conventional and targeted therapies, to better evaluate therapeutic effectiveness during the early phases of treatment, and to enhance a priori risk assessment for treatment induced toxicity. Functional metabolic imaging typically involves pretreatment baseline magnetic resonance imaging (MRI) and/or positron emission tomographic (PET) scans and performance of subsequent scans during and/or after treatment. Imaging parameter changes are routinely attributed to the intervening therapy and clinical outcomes subsequently correlated with these changes. The physiologic parameter(s) that best correlate with clinical outcome and the relative utility of MRI versus PET are unknown, however. Furthermore, tumor vascular physiology and metabolic parameters are heterogeneous and dynamic processes. Large daily fluctuations often occur in the absence of treatment. The magnitude of this temporal variability is not established for MRI or for PET. Routine and meaningful clinical application of functional imaging requires understanding and quantification of the intrinsic variability of the underlying biologic processes and a demonstration that treatment-induced changes exceed intrinsic temporal variation.

Applications of molecular imaging

Today molecular imaging technologies play a central role in clinical oncology. The use of imaging techniques in early cancer detection, treatment response, and new therapy development is steadily growing and has already significantly impacted on clinical management of cancer. In this chapter, we overview three different molecular imaging technologies used for the understanding of disease biomarkers, drug development, or monitoring therapeutic outcome. They are (1) optical imaging (bioluminescence and fluorescence imaging), (2) magnetic resonance imaging (MRI), and (3) nuclear imaging (e.g., single-photon emission computed tomography (SPECT) and positron emission tomography (PET)). We review the use of molecular reporters of biological processes (e.g., apoptosis and protein kinase activity) for high-throughput drug screening and new cancer therapies, diffusion MRI as a biomarker for early treatment response and PET and SPECT radioligands in oncology.

Imaging of lung cancer in the era of molecular medicine

Recent discoveries characterizing the molecular basis of lung cancer brought fundamental changes in lung cancer treatment. The authors review the molecular pathogenesis of lung cancer, including genomic abnormalities, targeted therapies, and resistance mechanisms, and discuss lung cancer imaging with novel techniques. Knowledge of the molecular basis of lung cancer is essential for radiologists to properly interpret imaging and assess response to therapy. Quantitative and functional imaging helps assessing the biologic behavior of lung cancer.

Prediction of disease-free survival in patients with squamous cell carcinomas of the head and neck using dynamic contrast-enhanced MR imaging

BACKGROUND AND PURPOSE

Patients with HNSCC have a poor prognosis and development of imaging biomarkers that predict long-term outcome might aid in planning optimal treatment strategies. Therefore, the purpose of the present study was to predict disease-free survival in patients with HNSCC by using pretreatment K(trans) measured from dynamic contrast-enhanced MR imaging.

MATERIALS AND METHODS

Sixty-six patients with HNSCC were recruited from January 2005 to October 2008. Three patients were excluded because they underwent upfront neck dissection, and 6 patients were excluded due to suboptimal MR imaging data or being lost to follow-up. Disease-free survival was measured in the remaining 57 patients from the end date of chemoradiation therapy. In patients who died, the end point was the date of death, while in surviving patients the date of last clinical follow-up was used as the end point. Pretreatment K(trans) and nodal volume were computed from the largest metastatic node, and median pretreatment K(trans) and volume were used to divide patients into 2 groups (at or above the threshold value [group I] and below the threshold value [group II]. Disease-free survival was analyzed by the Kaplan-Meier method, and the results were compared by using a logrank test with K(trans) and nodal volume as predictors. A P value <.05 was considered significant.

RESULTS

Thirteen of 57 patients had died of HNSCC by the last follow-up period (March 31, 2009). Patients with higher pretreatment K(trans) values had prolonged disease-free survival compared with patients with lower K(trans) values (P=.029). However, there was no significant difference in disease-free survival when nodal volume was used as a predictor (P=.599).

CONCLUSIONS

Pretreatment K(trans) may be a useful prognostic marker in HNSCC.

Use of new imaging techniques to predict tumour response to therapy

Imaging of tumour response to therapy has steadily evolved over the past few years as a result of advances in existing imaging modalities and the introduction of new functional techniques. The use of imaging as an early surrogate biomarker of response is appealing, because it might allow for a window of opportunity during which treatment regimens can be tailored accordingly, depending on the expected response. The clinical effect of this would ultimately result in a reduction in morbidity and undue costs. The aim of this review is to describe the potential of various new imaging techniques as biomarkers of early tumour response. We have reviewed the literature and identified studies that have assessed these techniques, such as diffusion-weighted MRI, dynamic contrast-enhanced MRI, magnetic resonance spectroscopy, and 18-fluorodeoxyglucose-PET as early response indicators, and highlight the current clinical awareness of their use.

Predicting survival and early clinical response to primary chemotherapy for patients with locally advanced breast cancer using DCE-MRI

PURPOSE

To evaluate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as a tool for early prediction of response to neoadjuvant chemotherapy (NAC) and 5-year survival in patients with locally advanced breast cancer.

MATERIALS AND METHODS

DCE-MRI was performed in patients scheduled for NAC (n = 24) before and after the first treatment cycle. Clinical response was evaluated after completed NAC. Relative signal intensity (RSI) and area under the curve (AUC) were calculated from the DCE-curves and compared to clinical treatment response. Kohonen and probabilistic neural network (KNN and PNN) analysis were used to predict 5-year survival.

RESULTS

RSI and AUC were reduced after only one cycle of NAC in patients with clinical treatment response (P = 0.02 and P = 0.08). The mean and 10th percentile RSI values before NAC were significantly lower in patients surviving more than 5 years compared to nonsurvivors (P = 0.05 and 0.02). This relationship was confirmed using KNN, which demonstrated that patients who remained alive clustered in separate regions from those that died. Calibration of contrast enhancement curves by PNN for patient survival at 5 years yielded sensitivity and specificity for training and testing ranging from 80%-92%.

CONCLUSION

DCE-MRI in locally advanced breast cancer has the potential to predict 5-year survival in a small patient cohort. In addition, changes in tumor vascularization after one cycle of NAC can be assessed.

DCEMRI monitoring of canine tumors during fractionated radiotherapy

PURPOSE

To monitor the contrast enhancement in spontaneous canine tumors during fractionated radiotherapy by Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCEMRI).

METHODS AND MATERIAL

Six dogs with tumors in the oral or nasal cavity received fractionated conformal radiotherapy with 54 Gy given in 18 fractions. T1 weighted DCE imaging was performed prior to each treatment fraction. The tumor was manually delineated in the MR images following every imaging session, and the time dependence of the Relative Signal Intensity (RSI) in the tumor was extracted voxel by voxel. RSI images at the time of maximum enhancement were generated, in addition to images of the initial slope of the RSI curves. The dependence of the median RSI and median slope in the tumor on the accumulated radiation dose was investigated, and images obtained at different treatment fraction were compared by correlation analysis.

RESULTS

Five of the six tumors regressed during treatment. The dose dependence of the RSI varied between the tumors, with some showing an increase and others a decrease in RSI with dose. This was also the case for the initial slope of the RSI curves. The correlation between images acquired before the first treatment fraction and subsequent fractions was in general low, and decreased significantly with accumulated radiation dose for five of six tumors.

CONCLUSIONS

Large individual variations in the dose response of tumor contrast enhancement were found. Decreasing image correlation resulted both from tumor regression and intratumoral changes in the RSI distribution during treatment. These findings may have consequences for treatment design in biological image-guided radiotherapy.

Prognostic value of pre-treatment DCE-MRI parameters in predicting disease free and overall survival for breast cancer patients undergoing neoadjuvant chemotherapy

The purpose of this study was to investigate whether dynamic contrast enhanced MRI (DCE-MRI) data, both pharmacokinetic and empirical, can predict, prior to neoadjuvant chemotherapy, which patients are likely to have a shorter disease free survival (DFS) and overall survival (OS) interval following surgery. Traditional prognostic parameters were also included in the survival analysis. Consequently, a comparison of the prognostic value could be made between all the parameters studied. MR examinations were conducted on a 1.5 T system in 68 patients prior to the initiation of neoadjuvant chemotherapy. DCE-MRI consisted of a fast spoiled gradient echo sequence acquired over 35 phases with a mean temporal resolution of 11.3s. Both pharmacokinetic and empirical parameters were derived from the DCE-MRI data. Kaplan-Meier survival plots were generated for each parameter and group comparisons were made utilising logrank tests. The results from the 54 patients entered into the univariate survival analysis demonstrated that traditional prognostic parameters (tumour grade, hormonal status and size), empirical parameters (maximum enhancement index, enhancement index at 30s, area under the curve and initial slope) and adjuvant therapies demonstrated significant differences in survival intervals. Further multivariate Cox regression survival analysis revealed that empirical enhancement parameters contributed the greatest prediction of both DFS and OS in the resulting models. In conclusion, this study has demonstrated that in patients who exhibit high levels of perfusion and vessel permeability pre-treatment, evidenced by elevated empirical DCE-MRI parameters, a significantly lower disease free survival and overall survival can be expected.

3-T MRI for differentiating inflammation- and fibrosis-predominant lesions of usual and nonspecific interstitial pneumonia: comparison study with pathologic correlation

OBJECTIVE

The purpose of our study was to evaluate the utility of 3-T MRI of the lung for differentiating inflammation- and fibrosis-predominant lesions in the usual and nonspecific types of interstitial pneumonia.

SUBJECTS AND METHODS

The subjects were 26 patients (10 men, 16 women; mean age, 57 +/- 9 [SD] years; 16 with nonspecific interstitial pneumonia; 10 with usual interstitial pneumonia) who underwent 3-T MRI of the lung and surgical biopsy. A total of 54 biopsy sites were classified histopathologically into two groups: inflammation predominant and fibrosis predominant. After a T2-weighted triple-inversion black blood turbo spin-echo (TSE) sequence, dynamic MRI was performed with a T1-weighted 3D turbo field-echo sequence (coronal images with 2.5-mm slice thickness) before and 1, 3, 5, and 10 minutes after i.v. contrast injection. The chi-square test was used to compare differences in signal intensity on T2-weighted triple-inversion black blood TSE MR images and visually assessed enhancement patterns at dynamic MRI for the inflammation- and fibrosis-predominant sites.

RESULTS

Inflammation-predominant specimens were obtained from 31% (17 of 54) of the biopsy sites. Inflammation-predominant biopsy sites had an early enhancement pattern (82%, 14 of 17 sites, p < 0.001) on dynamic studies and high signal intensity (53%, nine of 17 sites, p = 0.001) on T2-weighted triple-inversion black blood TSE images.

CONCLUSION

Multiphase dynamic enhancement studies with a turbo field-echo sequence and T2-weighted triple-inversion black blood TSE images on 3-T MRI appear to be useful for differentiating inflammation- and fibrosis-predominant lesions.

Dynamic contrast-enhanced MRI as a predictor of tumour response to radiotherapy

A predictive technique in the management of patients with cancer could improve the therapeutic index by allowing better individualisation of treatment. The standard risk factors that are currently used do not adequately account for the unpredictable and substantial variation seen in the treatment response of patients with a similar risk profile. Dynamic contrast-enhanced (DCE) MRI is a non-invasive technique that can provide anatomical and physiological information on the tumour. The DCE-MRI data reflects the tumour microenvironment variables that are known to influence radiation response. The aim of this review is to describe the potential clinical application of DCE-MRI as a predictor of radiation response. We have reviewed the literature and identified 29 studies (total of 1194 patients) that correlate DCE-MRI with histopathological or clinical outcome data relevant to radiotherapy.

MRT zum Staging des Lungenkarzinoms

PURPOSE

Overview of magnetic resonance imaging (MRI) in staging of lung cancer.

MATERIAL AND METHODS

Currently available methods of imaging lung cancer, lymph node and distant metastases by MRI are explained. At present, MRI is mainly used in the detection of cerebral metastases and assessment of infiltration of the thoracic wall and of the mediastinum. The capabilities of T2-weighted single-shot TSE (HASTE) and T1-weighted 3D gradient echo techniques (VIBE) are demonstrated.

RESULTS

With the advent of new fast sequences like HASTE and VIBE the spatial resolution comes close to that of computed tomography but with an outstanding soft tissue contrast and without radiation exposure. The introduction of lymph node specific contrast media will improve sensitivity and specificity in N staging. Additionally, whole-body MRI is capable of detecting distant metastases, in particular in the organs at risk, i.e. brain, upper abdomen and musculoskeletal system.

CONCLUSION

MRI is gaining importance as part of a multimodal imaging approach for staging of lung cancer.