Histopathological Features of MRI-Invisible Regions of Prostate Cancer Lesions.

BACKGROUND: Previous studies have reported tumor volume underestimation with multiparametric (mp)MRI in prostate cancer diagnosis. PURPOSE: To investigate why some parts of lesions are not visible on mpMRI by comparing their histopathology features to those of visible regions. STUDY TYPE: Retrospective. POPULATION: Thirty-four patients with biopsy-proven prostate cancer scheduled for prostatectomy (median 68.7 years). FIELD STRENGTH/SEQUENCE: T2 -weighted, diffusion-weighted imaging, T2 mapping, and dynamic contrast-enhanced MRI on two 3T systems and one 1.5T system. ASSESSMENT: Two readers delineated suspicious lesions on mpMRI. A pathologist delineated the lesions on histopathology. A patient-customized mold enabled the registration of histopathology and MRI. On histopathology we identified mpMRI visible and invisible lesions. Subsequently, within the visible lesions we identified regions that were visible and regions that were invisible on mpMRI. For each lesion and region the following characteristics were determined: size, location, International Society of Urological Pathology (ISUP) grade, and Gleason subpatterns (density [dense/intermediate], tumor morphology [homogeneous/heterogeneous], cribriform growth [yes/no]). STATISTICAL TESTS: With generalized linear mixed-effect modeling we investigated which features explain why a lesion or a region was invisible on MRI. We compared imaging values (T2 , ADC, and Ktrans ) for these features with one-way analysis of variance (ANOVA). RESULTS: Small, anterior, and ISUP grade 1-2 lesions (n = 34) were missed more frequent than large, posterior, ISUP grade ≥ 3 lesions (n = 35). Invisible regions on mpMRI had lower tumor density, heterogeneous tumor morphology, and were located in the transition zone. Both T2 and ADC values were higher in "intermediate" compared with "dense" regions (P = 0.002 and < 0.001) and in regions with heterogeneous compared with homogeneous morphology (P < 0.001 and 0.03). Ktrans was not significantly different (P = 0.24 and 0.99). DATA CONCLUSION: Regions of prostate cancer lesions that are invisible on mpMRI have different histopathology features than visible regions. This may have implications for monitoring during active surveillance and focal treatment strategies. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:1235-1246.

Quantitative MRI Changes During Weekly Ultra-Hypofractionated Prostate Cancer Radiotherapy With Integrated Boost.

Purpose: Quantitative MRI reflects tissue characteristics. As possible changes during radiotherapy may lead to treatment adaptation based on response, we here assessed if such changes during treatment can be detected. Methods and Materials: In the hypoFLAME trial patients received ultra-hypofractionated prostate radiotherapy with an integrated boost to the tumor in 5 weekly fractions. We analyzed T2 and ADC maps of 47 patients that were acquired in MRI exams prior to and during radiotherapy, and performed rigid registrations based on the prostate contour on anatomical T2-weighted images. We analyzed median T2 and ADC values in three regions of interest (ROIs): the central gland (CG), peripheral zone (PZ), and tumor. We analyzed T2 and ADC changes during treatment and compared patients with and without hormonal therapy. We tested changes during treatment for statistical significance with Wilcoxon signed rank tests. Using confidence intervals as recommended from test-retest measurements, we identified persistent T2 and ADC changes during treatment. Results: In the CG, median T2 and ADC values significantly decreased 12 and 8%, respectively, in patients that received hormonal therapy, while in the PZ these values decreased 17 and 18%. In the tumor no statistically significant change was observed. In patients that did not receive hormonal therapy, median ADC values in the tumor increased with 20%, while in the CG and PZ no changes were observed. Persistent T2 changes in the tumor were found in 2 out of 24 patients, while none of the 47 patients had persistent ADC changes. Conclusions: Weekly quantitative MRI could identify statistically significant ADC changes in the tumor in patients without hormonal therapy. On a patient level few persistent T2 changes in the tumor were observed. Long-term follow-up is required to relate the persistent T2 and ADC changes to outcome and evaluate the applicability of quantitative MRI for response based treatment adaptation.

Multiparametric MRI Tumor Probability Model for the Detection of Locally Recurrent Prostate Cancer After Radiation Therapy: Pathologic Validation and Comparison With Manual Tumor Delineations.

PURPOSE: Focal salvage treatments of recurrent prostate cancer (PCa) after radiation therapy require accurate delineation of the target volume. Magnetic resonance imaging (MRI) is used for this purpose; however, radiation therapy-induced changes complicate image interpretation, and guidelines are lacking on the assessment and delineation of recurrent PCa. A tumor probability (TP) model was trained and independently tested using multiparametric magnetic resonance imaging (mp-MRI) of patients with radio-recurrent PCa. The resulting probability maps were used to derive target regions for radiation therapy treatment planning. METHODS AND MATERIALS: Two cohorts of patients with radio-recurrent PCa were used in this study. All patients underwent mp-MRI (T2 weighted, diffusion-weighted imaging, and dynamic contrast enhanced). A logistic regression model was trained using imaging features from 21 patients with biopsy-proven recurrence who qualified for salvage treatment. The test cohort consisted of 17 patients treated with salvage prostatectomy. The model was tested against histopathology-derived tumor delineations. The voxel-wise TP maps were clustered using k-means to generate a gross tumor volume (GTV) contour for voxel-level comparisons with manual tumor delineations performed by 2 radiologists and with histopathology-validated contours. Later, k-means was used with 3 clusters to define a clinical target volume (CTV), high-risk CTV, and GTV, with increasing tumor risk. RESULTS: In the test cohort, the model obtained a median (range) area under the curve of 0.77 (0.41-0.99) for the whole prostate. The GTV delineation resulted in a median sensitivity of 0.31 (0-0.87) and specificity of 0.97 (0.84-1.0) with no significant differences between model and manual delineations. The 3-level clustering GTV and high-risk CTV delineations had median sensitivities of 0.17 (0-0.59) and 0.49 (0-0.97) and specificities of 0.98 (0.84-1.00) and 0.94 (0.84-0.99), respectively. CONCLUSIONS: The TP model had a good performance in predicting voxel-wise presence of recurrent tumor. Model-derived tumor risk levels achieved sensitivity and specificity similar to manual delineations in localizing recurrent tumor. Voxel-wise TP derived from mp-MRI can in this way be incorporated for target definition in focal salvage of radio-recurrent PCa.

Quantitative 3-T multi-parametric MRI and step-section pathology of recurrent prostate cancer patients after radiation therapy.

OBJECTIVES: Diagnosis of radio-recurrent prostate cancer using multi-parametric MRI (mp-MRI) can be challenging due to the presence of radiation effects. We aim to characterize imaging of prostate tissue after radiation therapy (RT), using histopathology as ground truth, and to investigate the visibility of tumor lesions on mp-MRI. METHODS: Tumor delineated histopathology slides from salvage radical prostatectomy patients, primarily treated with RT, were registered to MRI. Median T2-weighted, ADC, Ktrans, and kep values in tumor and other regions were calculated. Two radiologists independently performed mp-MRI-based tumor delineations which were compared with the true pathological extent. General linear mixed-effect modeling was used to establish the contribution of each imaging modality and combinations thereof in distinguishing tumor and benign voxels. RESULTS: Nineteen of the 21 included patients had tumor in the available histopathology slides. Recurrence was predominantly multifocal with large tumor foci seen after external beam radiotherapy, whereas these were small and sparse after low-dose-rate brachytherapy. MRI-based delineations missed small foci and slightly underestimated tumor extent. The combination of T2-weighted, ADC, Ktrans, and kep had the best performance in distinguishing tumor and benign voxels. CONCLUSIONS: Using high-resolution histopathology delineations, the real tumor extent and size were found to be underestimated on MRI. mp-MRI obtained the best performance in identifying tumor voxels. Appropriate margins around the visible tumor-suspected region should be included when designing focal salvage strategies. Recurrent tumor delineation guidelines are warranted. KEY POINTS: • Compared to the use of individual sequences, multi-parametric MRI obtained the best performance in distinguishing recurrent tumor from benign voxels. • Delineations based on mp-MRI miss smaller foci and slightly underestimate tumor volume of local recurrent prostate cancer. • Focal salvage strategies should include appropriate margins around the visible tumor.

Quantitative 3T multiparametric MRI of benign and malignant prostatic tissue in patients with and without local recurrent prostate cancer after external-beam radiation therapy.

BACKGROUND: Post-radiotherapy locally recurrent prostate cancer (PCa) patients are candidates for focal salvage treatment. Multiparametric MRI (mp-MRI) is attractive for tumor localization. However, radiotherapy-induced tissue changes complicate image interpretation. To develop focal salvage strategies, accurate tumor localization and distinction from benign tissue is necessary. PURPOSE: To quantitatively characterize radio-recurrent tumor and benign radiation-induced changes using mp-MRI, and investigate which sequences optimize the distinction between tumor and benign surroundings. STUDY TYPE: Prospective case-control. SUBJECTS: Thirty-three patients with biochemical failure after external-beam radiotherapy (cases), 35 patients without post-radiotherapy recurrent disease (controls), and 13 patients with primary PCa (untreated). FIELD STRENGTH/SEQUENCES: 3T; quantitative mp-MRI: T2 -mapping, ADC, and Ktrans and kep maps. ASSESSMENT: Quantitative image-analysis of prostatic regions, within and between cases, controls, and untreated patients. STATISTICAL TESTS: Within-groups: nonparametric Friedman analysis of variance with post-hoc Wilcoxon signed-rank tests; between-groups: Mann-Whitney tests. All with Bonferroni corrections. Generalized linear mixed modeling to ascertain the contribution of each map and location to tumor likelihood. RESULTS: Benign imaging values were comparable between cases and controls (P = 0.15 for ADC in the central gland up to 0.91 for kep in the peripheral zone), both with similarly high peri-urethral Ktrans and kep values (min-1 ) (median [range]: Ktrans = 0.22 [0.14-0.43] and 0.22 [0.14-0.36], P = 0.60, kep = 0.43 [0.24-0.57] and 0.48 [0.32-0.67], P = 0.05). After radiotherapy, benign central gland values were significantly decreased for all maps (P ≤ 0.001) as well as T2 , Ktrans , and kep of benign peripheral zone (all with P ≤ 0.002). All imaging maps distinguished recurrent tumor from benign peripheral zone, but only ADC, Ktrans , and kep were able to distinguish it from benign central gland. Recurrent tumor and peri-urethral Ktrans values were not significantly different (P = 0.81), but kep values were (P < 0.001). Combining all quantitative maps and voxel location resulted in an optimal distinction between tumor and benign voxels. DATA CONCLUSION: Mp-MRI can distinguish recurrent tumor from benign tissue. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:269-278.

Performance of a fast and high-resolution multi-echo spin-echo sequence for prostate T2 mapping across multiple systems.

PURPOSE: To evaluate the performance of a multi-echo spin-echo sequence with k-t undersampling scheme (k-t T2 ) in prostate cancer. METHODS: Phantom experiments were performed at five systems to estimate the bias, short-term repeatability, and reproducibility across all systems expressed with the within-subject coefficient of variation (wCV). Monthly measurements were performed on two systems for long-term repeatability estimation. To evaluate clinical repeatability, two T2 maps (voxel size 0.8 × 0.8 × 3 mm3 ; 5 min) were acquired at separate visits on one system for 13 prostate cancer patients. Repeatability was assessed per patient in relation to spatial resolution. T2 values were compared for tumor, peripheral zone, and transition zone. RESULTS: Phantom measurements showed a small bias (median = -0.9 ms) and good short-term repeatability (median wCV = 0.5%). Long-term repeatability was 0.9 and 1.1% and reproducibility between systems was 1.7%. The median bias observed in patients was -1.1 ms. At voxel level, the median wCV was 15%, dropping to 4% for structures of 0.5 cm3 . The median tumor T2 values (79 ms) were significantly lower (P < 0.001) than in the peripheral zone (149 ms), but overlapped with the transition zone (91 ms). CONCLUSIONS: Reproducible T2 mapping of the prostate is feasible with good spatial resolution in a clinically reasonable scan time, allowing reliable measurement of T2 in structures as small as 0.5 cm3 . Magn Reson Med 79:1586-1594, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Repeatability of dose painting by numbers treatment planning in prostate cancer radiotherapy based on multiparametric magnetic resonance imaging.

Dose painting by numbers (DPBN) refers to a voxel-wise prescription of radiation dose modelled from functional image characteristics, in contrast to dose painting by contours which requires delineations to define the target for dose escalation. The direct relation between functional imaging characteristics and DPBN implies that random variations in images may propagate into the dose distribution. The stability of MR-only prostate cancer treatment planning based on DPBN with respect to these variations is as yet unknown. We conducted a test-retest study to investigate the stability of DPBN for prostate cancer in a semi-automated MR-only treatment planning workflow. Twelve patients received a multiparametric MRI on two separate days prior to prostatectomy. The tumor probability (TP) within the prostate was derived from image features with a logistic regression model. Dose mapping functions were applied to acquire a DPBN prescription map that served to generate an intensity modulated radiation therapy (IMRT) treatment plan. Dose calculations were done on a pseudo-CT derived from the MRI. The TP and DPBN map and the IMRT dose distribution were compared between both MRI sessions, using the intraclass correlation coefficient (ICC) to quantify repeatability of the planning pipeline. The quality of each treatment plan was measured with a quality factor (QF). Median ICC values for the TP and DPBN map and the IMRT dose distribution were 0.82, 0.82 and 0.88, respectively, for linear dose mapping and 0.82, 0.84 and 0.94 for square root dose mapping. A median QF of 3.4% was found among all treatment plans. We demonstrated the stability of DPBN radiotherapy treatment planning in prostate cancer, with excellent overall repeatability and acceptable treatment plan quality. Using validated tumor probability modelling and simple dose mapping techniques it was shown that despite day-to-day variations in imaging data still consistent treatment plans were obtained.

Multicenter validation of prostate tumor localization using multiparametric MRI and prior knowledge.

PURPOSE: Tumor localization provides crucial information for radiotherapy dose differentiation treatments, such as focal dose escalation and dose painting by numbers, which aim at achieving tumor control with minimal side effects. Multiparametric (mp-)MRI is increasingly used for tumor detection and localization in prostate because of its ability to visualize tissue structure and to reveal tumor characteristics. However, it can be challenging to distinguish cancer, particularly in the transition zone. In this study, we enhance the performance of a mp-MRI-based tumor localization model by incorporating prior knowledge from two sources: a population-based tumor probability atlas and patient-specific biopsy examination results. This information typically would be considered by a physician when carrying out a manual tumor delineation. MATERIALS AND METHODS: Our study involves 40 patients from two centers: 23 patients from the University Hospital Leuven (Leuven), Leuven, Belgium and 17 patients from the Netherlands Cancer Institute (NKI), Amsterdam, the Netherlands. All patients received a mp-MRI exam consisting of a T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI before prostatectomy. Thirty-one features were extracted for each voxel in the prostate. Among these, 29 were from the multiparametric-MRI, one was from the population-based tumor probability atlas and one from the biopsy map. T2-weighted images of each patient were registered to whole-mount section pathology slices to obtain the ground truth. The study was validated in two settings: single-center (training and test sets were from the same cohort); and cross-center (training and test sets were from different cohorts). In addition, automatic delineations created by our model were compared with manual tumor delineations done by six different teams on a subset of Leuven cohort including 15 patients. RESULTS: In the single-center setting, mp-MRI-based features yielded area under the ROC curves (AUC) of 0.690 on a pooled set of patients from both cohorts. Including prevalence into mp-MRI-based features increased the AUC to 0.751 and including all features achieved the best performance with AUC of 0.775. Using all features always showed better results when varying the size of the training set. In addition, its performance is comparable with the average performance of six teams delineating the tumors manually. The error rate using all features was 0.22. The two prior knowledge features ranked among the top four most important features out of the 31 features. In the cross-center setting, combining all features also yielded the best performance in terms of the mean AUC of 0.777 on the pooled set of patients from both cohorts. In addition, the difference in performance between the single-center setting and cross-center setting was not significant. CONCLUSIONS: The results showed significant improvements when including prior knowledge features in addition to mp-MRI-based features in both single- and cross-center settings.

Histopathology-derived modeling of prostate cancer tumor control probability: Implications for the dose to the tumor and the gland.

PURPOSE: To evaluate the impact of GTV-CTV dose differentiation by simulating response of prostate patients to radiotherapy, considering histopathology of prostatectomy specimens. MATERIAL AND METHODS: Tumors' cell numbers (N0) and Gleason Scores (GS) were derived from histopathology of 25 specimens. Index lesions and tumors ⩾0.5cm(3) were considered GTV. Satellites <0.5cm(3) constituted the tumor load in the CTV. Each patient's tumor control probability (TCP) was simulated using the linear quadratic model and considering the N0 while assuming either a constant or GS-dependent α and ß. RESULTS: 19/25 patients had multi-focal disease. In 11 patients the CTV contained GS 4+3 or 4+4 tumors. Compared to the GTV, the CTV pathology was more favorable. For an α=0.140Gy(-1), a GTV dose of 79Gy with a CTV dose of 72Gy achieved an 80% TCP in the population. Varying α between 0.160-0.118Gy(-1) with GS, a GTV and CTV dose of 80Gy and 70Gy also gave an 80% TCP. CONCLUSIONS: Considering only N0, our simulations suggest that a GTV-CTV dose differentiation of 7Gy would not compromise TCP of the patient population. When assuming an increased radiosensitivity with lower GS, a further dose differentiation of 10Gy might be feasible.

Magnetic resonance imaging for prostate cancer radiotherapy.

For radiotherapy of prostate cancer, MRI is used increasingly for delineation of the prostate gland. For focal treatment of low-risk prostate cancer or focal dose escalation for intermediate and high-risk cancer, delineation of the tumor is also required. While multi-parametric MRI is well established for detection of tumors and for staging of the disease, delineation of the tumor inside the prostate is not common practice. Guidelines, such as the PI-RADS classification, exist for tumor detection and staging, but no such guidelines are available for tumor delineation. Indeed, interobserver studies show substantial variation in tumor contours. Computer-aided tumor detection and delineation may help improve the robustness of the interpretation of multi-parametric MRI data. Comparing the performance of an earlier developed model for tumor segmentation with expert delineations, we found a significant correlation between tumor probability in a voxel and the number of experts identifying this voxel as tumor. This suggests that the model agrees with 'the wisdom of the crowd', and thus could serve as a reference for individual physicians in their decision making. With multi-parametric MRI it becomes feasible to revisit the GTV-CTV concept in radiotherapy of prostate cancer. While detection of index lesions is quite reliable, contouring variability and the low sensitivity to small lesions suggest that the remainder of the prostate should be treated as CTV. Clinical trials that investigate the options for dose differentiation, for example with dose escalation to the visible tumor or dose reduction to the CTV, are therefore warranted.

Decreasing Irradiated Rat Lung Volume Changes Dose-Limiting Toxicity From Early to Late Effects.

PURPOSE: Technological developments in radiation therapy result in smaller irradiated volumes of normal tissue. Because the risk of radiation therapy-induced toxicity generally depends on irradiated volume, changing volume could change the dose-limiting toxicity of a treatment. Recently, in our rat model, we found that early radiation-induced lung dysfunction (RILD) was closely related to irradiated volume dependent vascular remodeling besides inflammation. The exact relationship between early and late RILD is still unknown. Therefore, in this preclinical study we investigated the dose-volume relationship of late RILD, assessed its dependence on early and late pathologies and studied if decreasing irradiated volume changed the dose-limiting toxicity. METHODS AND MATERIALS: A volume of 25%, 32%, 50%, 63%, 88%, or 100% of the rat lung was irradiated using protons. Until 26 weeks after irradiation, respiratory rates were measured. Macrovascular remodeling, pulmonary inflammation, and fibrosis were assessed at 26 weeks after irradiation. For all endpoints dose-volume response curves were made. These results were compared to our previously published early lung effects. RESULTS: Early vascular remodeling and inflammation correlated significantly with early RILD. Late RILD correlated with inflammation and fibrosis, but not with vascular remodeling. In contrast to the early effects, late vascular remodeling, inflammation and fibrosis showed a primarily dose but not volume dependence. Comparison of respiratory rate increases early and late after irradiation for the different dose-distributions indicated that with decreasing irradiated volumes, the dose-limiting toxicity changed from early to late RILD. CONCLUSIONS: In our rat model, different pathologies underlie early and late RILD with different dose-volume dependencies. Consequently, the dose-limiting toxicity changed from early to late dysfunction when the irradiated volume was reduced. In patients, early and late RILD are also due to different pathologies. As such, new radiation techniques reducing irradiated volume might change the dose-limiting toxicity of the radiation therapy treatment.

A new CT-based method to quantify radiation-induced lung damage in patients.

A new method to assess radiation-induced lung toxicity (RILT) using CT-scans was developed. It is more sensitive in detecting damage and corresponds better to physician-rated radiation pneumonitis than routinely-used methods. Use of this method may improve lung toxicity assessment and thereby facilitate development of more accurate predictive models for RILT.

Prostate tumor delineation using multiparametric magnetic resonance imaging: Inter-observer variability and pathology validation.

BACKGROUND AND PURPOSE: Boosting the dose to the largest (dominant) lesion in radiotherapy of prostate cancer may improve treatment outcome. The success of this approach relies on the detection and delineation of tumors. The agreement among teams of radiation oncologists and radiologists delineating lesions on multiparametric magnetic resonance imaging (mp-MRI) was assessed by measuring the distances between observer contours. The accuracy of detection and delineation was determined using whole-mount histopathology specimens as reference. MATERIAL AND METHODS: Six observer teams delineated tumors on mp-MRI of 20 prostate cancer patients who underwent a prostatectomy. To assess the inter-observer agreement, the inter-observer standard deviation (SD) of the contours was calculated for tumor sites which were identified by all teams. RESULTS: Eighteen of 89 lesions were identified by all teams, all were dominant lesions. The median histological volume of these was 2.4cm(3). The median inter-observer SD of the delineations was 0.23cm. Sixty-six of 69 satellites were missed by all teams. CONCLUSION: Since all teams identify most dominant lesions, dose escalation to the dominant lesion is feasible. Sufficient dose to the whole prostate may need to be maintained to prevent under treatment of smaller lesions and undetected parts of larger lesions.

Gross tumor volume and clinical target volume in prostate cancer: How do satellites relate to the index lesion.

PURPOSE: There is an increasing interest for dose differentiation in prostate radiotherapy. The purpose of our study was to analyze the spatial distribution of tumor satellites inside the prostate. METHODS AND MATERIALS: 61 prostatectomy specimens were stained with H&E. Tumor regions were delineated by the uro-pathologist. Volumes, distances and cell densities of all delineated tumor regions were measured and further analyzed. RESULTS: Multifocal disease was seen in 84% of the patients. The median number of tumor foci was 3. The median distance between the index lesion and the satellites was 1.0 cm, with a maximum of 4.4 cm. The index lesions accounted for 88% of the total tumor volume. The contribution of tumor foci<0.1 cm(3) to the total tumor volume was 2%. The median cell density of the index lesion and all satellites, regardless of size, were significantly higher than that of the prostate. CONCLUSIONS: Satellites do not appear in a limited margin around the index lesion (GTV). Consequently, a fixed CTV margin would not effectively cover all satellites. Thus if the aim is to treat all tumor foci, the entire prostate gland should be considered CTV.

ACE inhibition attenuates radiation-induced cardiopulmonary damage.

BACKGROUND AND PURPOSE: In thoracic irradiation, the maximum radiation dose is restricted by the risk of radiation-induced cardiopulmonary damage and dysfunction limiting tumor control. We showed that radiation-induced sub-clinical cardiac damage and lung damage in rats mutually interact and that combined irradiation intensifies cardiopulmonary toxicity. Unfortunately, current clinical practice does not include preventative measures to attenuate radiation-induced lung or cardiac toxicity. Here, we investigate the effects of the ACE inhibitor captopril on radiation-induced cardiopulmonary damage. MATERIAL AND METHODS: After local irradiation of rat heart and/or lungs captopril was administered orally. Cardiopulmonary performance was assessed using biweekly breathing rate measurements. At 8 weeks post-irradiation, cardiac hemodynamics were measured, CT scans and histopathology were analyzed. RESULTS: Captopril significantly improved breathing rate and cardiopulmonary density/structure, but only when the heart was included in the radiation field. Consistently, captopril reduced radiation-induced pleural and pericardial effusion and cardiac fibrosis, resulting in an improved left ventricular end-diastolic pressure only in the heart-irradiated groups. CONCLUSION: Captopril improves cardiopulmonary morphology and function by reducing acute cardiac damage, a risk factor in the development of radiation-induced cardiopulmonary toxicity. ACE inhibition should be evaluated as a strategy to reduce cardiopulmonary complications induced by radiotherapy to the thoracic area.

Physiological interaction of heart and lung in thoracic irradiation.

INTRODUCTION: The risk of early radiation-induced lung toxicity (RILT) limits the dose and efficacy of radiation therapy of thoracic tumors. In addition to lung dose, coirradiation of the heart is a known risk factor in the development RILT. The aim of this study was to identify the underlying physiology of the interaction between lung and heart in thoracic irradiation. METHODS AND MATERIALS: Rat hearts, lungs, or both were irradiated to 20 Gy using high-precision proton beams. Cardiopulmonary performance was assessed using breathing rate measurements and F(18)-fluorodeoxyglucose positron emission tomography ((18)F-FDG-PET) scans biweekly and left- and right-sided cardiac hemodynamic measurements and histopathology analysis at 8 weeks postirradiation. RESULTS: Two to 12 weeks after heart irradiation, a pronounced defect in the uptake of (18)F-FDG in the left ventricle (LV) was observed. At 8 weeks postirradiation, this coincided with LV perivascular fibrosis, an increase in LV end-diastolic pressure, and pulmonary edema in the shielded lungs. Lung irradiation alone not only increased pulmonary artery pressure and perivascular edema but also induced an increased LV relaxation time. Combined irradiation of lung and heart induced pronounced increases in LV end-diastolic pressure and relaxation time, in addition to an increase in right ventricle end-diastolic pressure, indicative of biventricular diastolic dysfunction. Moreover, enhanced pulmonary edema, inflammation and fibrosis were also observed. CONCLUSIONS: Both lung and heart irradiation cause cardiac and pulmonary toxicity via different mechanisms. Thus, when combined, the loss of cardiopulmonary performance is intensified further, explaining the deleterious effects of heart and lung coirradiation. Our findings show for the first time the physiological mechanism underlying the development of a multiorgan complication, RILT. Reduction of dose to either of these organs offers new opportunities to improve radiation therapy treatment of thoracic tumors, potentially facilitating increased treatment doses and tumor control.

Quantifying local radiation-induced lung damage from computed tomography.

PURPOSE: Optimal implementation of new radiotherapy techniques requires accurate predictive models for normal tissue complications. Since clinically used dose distributions are nonuniform, local tissue damage needs to be measured and related to local tissue dose. In lung, radiation-induced damage results in density changes that have been measured by computed tomography (CT) imaging noninvasively, but not yet on a localized scale. Therefore, the aim of the present study was to develop a method for quantification of local radiation-induced lung tissue damage using CT. METHODS AND MATERIALS: CT images of the thorax were made 8 and 26 weeks after irradiation of 100%, 75%, 50%, and 25% lung volume of rats. Local lung tissue structure (S(L)) was quantified from local mean and local standard deviation of the CT density in Hounsfield units in 1-mm(3) subvolumes. The relation of changes in S(L) (DeltaS(L)) to histologic changes and breathing rate was investigated. Feasibility for clinical application was tested by applying the method to CT images of a patient with non-small-cell lung carcinoma and investigating the local dose-effect relationship of DeltaS(L). RESULTS: In rats, a clear dose-response relationship of DeltaS(L) was observed at different time points after radiation. Furthermore, DeltaS(L) correlated strongly to histologic endpoints (infiltrates and inflammatory cells) and breathing rate. In the patient, progressive local dose-dependent increases in DeltaS(L) were observed. CONCLUSION: We developed a method to quantify local radiation-induced tissue damage in the lung using CT. This method can be used in the development of more accurate predictive models for normal tissue complications.

A radiobiological review on melatonin: a novel radioprotector.

In spite of the fact that radiotherapy is a common and effective tool for cancer treatment; the radio sensitivity of normal tissues adjacent to the tumor which are unavoidably exposed to radiation limits therapeutic gain. For the sake of improvement in radiation therapy, radiobiology- the study of the action of ionizing radiation on living things- plays a crucial role through explaining observed phenomena, and suggesting improvements to existing therapies. Due to the damaging effects of ionizing radiation, radiobiologists have long been interested in identifying novel, nontoxic, effective, and convenient compounds to protect humans against radiation induced normal tissue injuries. In hundreds of investigations, melatonin (N-acetyl-5-methoxytryptamine), the chief secretory product of the pineal gland in the brain, has been documented to ameliorate the oxidative injuries due to ionizing radiation. This article reviews different features that make melatonin a potentially useful radioprotector. Moreover, based on radiobiological models we can hypothesize that melatonin may postpone the saturation of repair enzymes which leads to repairing more induced damage by repair system and more importantly allows the use of higher doses of radiation during radiotherapy to get a better therapeutic ratio. The implications of the accumulated observations suggest by virtue of melatonin's radioprotective and anticancer effects; it is time to use it as a radioprotector both for radiation workers and patients suffering from cancer either alone for cancer inhibition or in combination with traditional radiotherapy for getting a favorable efficacy/toxicity ratio during the treatment. Although compelling evidence suggests that melatonin may be effective for a variety of disorders, the optimum dose of melatonin for human radioprotection is yet to be determined. We propose that, in the future, melatonin improve the therapeutic ratio in radiation oncology.