Predicting patient-specific organ doses from thoracic CT examinations using support vector regression algorithm.

PURPOSE: This study aims to propose and develop a fast, accurate, and robust prediction method of patient-specific organ doses from CT examinations using minimized computational resources. MATERIALS AND METHODS: We randomly selected the image data of 723 patients who underwent thoracic CT examinations. We performed auto-segmentation based on the selected data to generate the regions of interest (ROIs) of thoracic organs using the DeepViewer software. For each patient, radiomics features of the thoracic ROIs were extracted via the Pyradiomics package. The support vector regression (SVR) model was trained based on the radiomics features and reference organ dose obtained by Monte Carlo (MC) simulation. The root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R-squared) were evaluated. The robustness was verified by randomly assigning patients to the train and test sets of data and comparing regression metrics of different patient assignments. RESULTS: For the right lung, left lung, lungs, esophagus, heart, and trachea, results showed that the trained SVR model achieved the RMSEs of 2 mGy to 2.8 mGy on the test sets, 1.5 mGy to 2.5 mGy on the train sets. The calculated MAPE ranged from 0.1 to 0.18 on the test sets, and 0.08 to 0.15 on the train sets. The calculated R-squared was 0.75 to 0.89 on test sets. CONCLUSIONS: By combined utilization of the SVR algorithm and thoracic radiomics features, patient-specific thoracic organ doses could be predicted accurately, fast, and robustly in one second even using one single CPU core.

Stereotactic body radiation therapy for non-small cell lung cancer using the non-coplanar radiation of Cyberknife and Varian linac.

PURPOSE: This study aims to evaluate the planned dose of stereotactic body radiation therapy (SBRT) for treating early peripheral non-small cell lung cancer (NSCLC) using the non-coplanar radiation from Cyberknife and Varian linac. Moreover, this study investigates whether Cyberknife and Varian linac are qualified for non-coplanar radiation SBRT for treating early peripheral NSCLC, and which one is better for protecting organs at risk (OARs). METHODS: Retrospective analysis was performed based on the Cyberknife radiation treatment plans (RTPs) and Varian Eclipse RTPs of 10 patients diagnosed with early peripheral NSCLC. The dose distributions in the target and OARs were compared between the RTPs of Cyberknife and Varian Eclipse using Mim medical imaging software. RESULTS: For PTV, no significant difference in D98 and D95 between the Cyberknife and Eclipse was observed (t = -0.35, -1.67, P > 0.05). The homogeneity indexes (HIs) of Cyberknife plans are higher (t = 71.86, P < 0.05) than those of Eclipse plans. The V10, V15, V20, V25, V30 and Dmean of the lung with NSCLC and the V20 of the whole lung for Cyberknife were less than those for Eclipse (t = -4.73, -5.62, -7.75, -6.38, -6.89, -3.14, -7.09, respectively, P < 0.05). Cyberknife plans have smaller spinal cord Dmax, trachea Dmax, heart Dmax, chest wall Dmax (t = -2.49, -2.57, -3.71, -3.56, respectively, P < 0.05) and esophagus Dmax (t = -1.95, P > 0.05) than Varian Eclipse plans. CONCLUSION: To fulfill SBRT by non-coplanar radiation, Cyberknife is recommended for the institutions equipped with Cyberknife, while Varian linac can be applied for the institutions that have not adopted Cyberknife in clinical radiotherapy yet.

Rapid patient-specific organ dose estimation in computed tomography scans via integration of radiomics features and neural networks.

Background: Computed tomography (CT) offers detailed cross-sectional images of internal anatomy for disease detection but carries a risk of solid cancer or blood malignancies due to exposure to X-ray radiation. This study aimed to develop a new method to quickly predict patient-specific organ doses from CT examinations by training neural networks (NNs) based on radiomics features. Methods: CT Digital Imaging and Communications in Medicine (DICOM) image data were exported to DeepViewer, a clinical autosegmentation software, to segment the regions of interest (ROIs) for patient organs. Radiomics feature extraction was performed based on the selected CT data and ROIs. Reference organ doses were computed using Monte Carlo (MC) simulations. Patient-specific organ doses were predicted by training a NN model based on radiomics features and reference doses. For the dose prediction performance, the relative root mean squared error (RRMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) were evaluated on the test sets. The robustness of the NN model was evaluated via the random rearrangement of patient samples in the training and test sets. Results: The maximal difference between the reference and predicted doses was less than 1 mGy for all investigated organs. The range of MAPE was 1.68% to 5.2% for head organs, 11.42% to 15.2% for chest organs, and 5.0% to 8.0% for abdominal organs; the maximal R2 values were 0.93, 0.86, and 0.89 for the head, chest, and abdominal organs, respectively. Conclusions: The radiomics feature-based NN model can achieve accurate prediction of patient-specific organ doses at a high speed of less than 1 second using a single central processing unit, which supports its use as a user-friendly online clinical application.

Fast prediction of patient-specific organ doses in brain CT scans using support vector regression algorithm.

Objectives. This study aims to develop a method for predicting patient-specific head organ doses by training a support vector regression (SVR) model based on radiomics features and graphics processing unit (GPU)-calculated reference doses.Methods. In this study, 237 patients who underwent brain CT scans were selected, and their CT data were transferred to an autosegmentation software to segment head regions of interest (ROIs). Subsequently, radiomics features were extracted from the CT data and ROIs, and the benchmark organ doses were computed using fast GPU-accelerated Monte Carlo (MC) simulations. The SVR organ dose prediction model was then trained using the radiomics features and benchmark doses. For the predicted organ doses, the relative root mean squared error (RRMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) were evaluated. The robustness of organ dose prediction was verified by changing the patient samples on the training and test sets randomly.Results. For all head organs, the maximal difference between the reference and predicted dose was less than 1 mGy. For the brain, the organ dose was predicted with an absolute error of 1.3%, and theR2reached up to 0.88. For the eyes and lens, the organ doses predicted by SVR achieved an RRMSE of less than 13%, the MAPE ranged from 4.5% to 5.5%, and theR2values were more than 0.7.Conclusions. Patient-specific head organ doses from CT examinations can be predicted within one second with high accuracy, speed, and robustness by training an SVR using radiomics features.

Fast prediction of personalized abdominal organ doses from CT examinations by radiomics feature-based machine learning models.

The X-rays emitted during CT scans can increase solid cancer risks by damaging DNA, with the risk tied to patient-specific organ doses. This study aims to establish a new method to predict patient specific abdominal organ doses from CT examinations using minimized computational resources at a fast speed. The CT data of 247 abdominal patients were selected and exported to the auto-segmentation software named DeepViewer to generate abdominal regions of interest (ROIs). Radiomics feature were extracted based on the selected CT data and ROIs. Reference organ doses were obtained by GPU-based Monte Carlo simulations. The support vector regression (SVR) model was trained based on the radiomics features and reference organ doses to predict abdominal organ doses from CT examinations. The prediction performance of the SVR model was tested and verified by changing the abdominal patients of the train and test sets randomly. For the abdominal organs, the maximal difference between the reference and the predicted dose was less than 1 mGy. For the body and bowel, the organ doses were predicted with a percentage error of less than 5.2%, and the coefficient of determination (R2) reached up to 0.9. For the left kidney, right kidney, liver, and spinal cord, the mean absolute percentage error ranged from 5.1 to 8.9%, and the R2 values were more than 0.74. The SVR model could be trained to achieve accurate prediction of personalized abdominal organ doses in less than one second using a single CPU core.

Combined helical tomotherapy and Gamma Knife stereotactic radiosurgery for high-grade recurrent orbital meningioma: a case report.

Orbital meningioma is a rare type of orbital tumor with high invasiveness and recurrence rates, making it extremely challenging to treat. Due to the special location of the disease, surgery often cannot completely remove the tumor, requiring postoperative radiation therapy. Here, we report a case of an elderly male patient with right-sided proptosis, visual impairment, and diplopia. Imaging diagnosis revealed a space-occupying lesion in the extraconal space of the right orbit. Pathological and immunohistochemical examination of the resected tumor confirmed it as a grade 3 anaplastic meningioma. Two months after surgery, the patient complained of right eye swelling and a magnetic resonance imaging (MRI) scan showed a recurrence of the tumor. The patient received helical tomotherapy (TOMO) in the postoperative tumor bed and high-risk areas within the orbit with a total dose of 48Gy. However, there was no significant improvement in the patient's right eye swelling, and the size of the recurrent lesion showed no significant change on imaging. Gamma knife multifractionated stereotactic radiosurgery (MF-SRS) was then given to the recurrent lesion with 50% prescription dose 13.5Gy/3f, once every other day. An imaging diagnosis performed 45 days later showed that the tumor had disappeared completely. The patient's vision remained unchanged, but diplopia was significantly relieved after MF-SRS. We propose a new hybrid treatment model for recurrent orbital meningioma, where conventional radiation therapy ensures local control of high-risk areas around the postoperative cavity, and MF-SRS maximizes the radiation dose to recurrent lesion areas while protecting surrounding tissues and organs.

Predicting the prognosis of lung cancer patients treated with intensity-modulated radiotherapy based on radiomic features.

AIMS: This study aimed to develop a method for predicting short-term outcomes of lung cancer patients treated with intensity-modulated radiotherapy (IMRT) using radiomic features detected through computed tomography images. METHOD: A prediction model was developed based on a dataset of radiomic features obtained from 132 patients with lung cancer receiving IMRT. Dimension reduction was performed for the features using the maximum-relevance and minimum-redundancy (mRMR) algorithm, and the least absolute shrinkage and selection operator (LASSO) regression model was utilized to optimize feature selection for the IMRT-sensitivity prediction model. The model was constructed using binary logistic regression analysis and was evaluated using the concordance index (C-index), calibration plots, receiver operating characteristic curve, and decision curve analysis. RESULTS: Fifty features were selected from 1348 radiomic features using the mRMR method. Of these, three radiomic features were selected by LASSO logistic regression to construct the radiomics nomogram. The C-index of the model was 0.776 (95% confidence interval: 0.689-0.862) and 0.791 (95% confidence interval: 0.607-0.974) in the training and validation cohorts, respectively. Decision curve analysis showed that the radiomics nomogram was clinically useful. CONCLUSION: Radiomic features have the potential to be applied to predict the short-term efficacy of IMRT in patients with inoperable lung cancer.

Exploring the Interior of Europa with the Europa Clipper.

The Galileo mission to Jupiter revealed that Europa is an ocean world. The Galileo magnetometer experiment in particular provided strong evidence for a salty subsurface ocean beneath the ice shell, likely in contact with the rocky core. Within the ice shell and ocean, a number of tectonic and geodynamic processes may operate today or have operated at some point in the past, including solid ice convection, diapirism, subsumption, and interstitial lake formation. The science objectives of the Europa Clipper mission include the characterization of Europa's interior; confirmation of the presence of a subsurface ocean; identification of constraints on the depth to this ocean, and on its salinity and thickness; and determination of processes of material exchange between the surface, ice shell, and ocean. Three broad categories of investigation are planned to interrogate different aspects of the subsurface structure and properties of the ice shell and ocean: magnetic induction, subsurface radar sounding, and tidal deformation. These investigations are supplemented by several auxiliary measurements. Alone, each of these investigations will reveal unique information. Together, the synergy between these investigations will expose the secrets of the Europan interior in unprecedented detail, an essential step in evaluating the habitability of this ocean world.

Investigating beam range uncertainty in proton prostate treatment using pelvic-like biological phantoms.

This study aims to develop a method for verifying site-specific and/or beam path specific proton beam range, which could reduce range uncertainty margins and the associated treatment complications. It investigates the range uncertainties from both CT HU to relative stopping power conversion and patient positioning errors for prostate treatment using pelvic-like biological phantoms. Three 25 × 14 × 12 cm3phantoms, made of fresh animal tissues mimicking the pelvic anatomies of prostate patients, were scanned with a general electric CT simulator. A 22 cm circular passive scattering beam with 29 cm range and 8 cm modulation width was used to measure the water equivalent path lengths (WEPL) through the phantoms at multiple points using the dose extinction method with a MatriXXPT detector. The measured WEPLs were compared to those predicted by TOPAS simulations and ray-tracing WEPL calculations. For the three phantoms, the WEPL differences between measured and theoretical prediction (WDMT) are below 1.8% for TOPAS, and 2.5% for ray-tracing. WDMT varies with phantom anatomies by about 0.5% for both TOPAS and ray-tracing. WDMT also correlates with the tissue types of a specific treated region. For the regions where the proton beam path is parallel to sharp bone edges, the WDMTs of TOPAS and ray-tracing respectively reach up to 1.8% and 2.5%. For the region where proton beams pass through just soft tissues, the WDMT is mostly less than 1% for both TOPAS and ray-tracing. For prostate treatments, range uncertainty depends on the tissue types within a specific treated region, patient anatomies and the range calculation methods in the planning algorithms. Our study indicates range uncertainty is less than 2.5% for the whole treated region with both ray-tracing and TOPAS, which suggests the potential to reduce the current 3.5% range uncertainty margin used in the clinics by at least 1% even for single-energy CT data.

Analysis on the emission and potential application of Cherenkov radiation in boron neutron capture therapy: A Monte Carlo simulation study.

This paper was aimed to explore the physics of Cherenkov radiation and its potential application in boron neutron capture therapy (BNCT). The Monte Carlo toolkit Geant4 was used to simulate the interaction between the epithermal neutron beam and the phantom containing boron-10. Results showed that Cherenkov photons can only be generated from secondary charged particles of gamma rays in BNCT, in which the 2.223 MeV prompt gamma rays are the main contributor. The number of Cherenkov photons per unit mass generated in the measurement region decreases linearly with the increase of boron concentration in both water and tissue phantom. The work presented the fundamental basis for applications of Cherenkov radiation in BNCT.

Investigation of the dose perturbation effect for therapeutic beams with the presence of a 1.5 T transverse magnetic field in magnetic resonance imaging-guided radiotherapy.

BACKGROUND: Magnetic resonance imaging (MRI)-guided radiotherapy is a promising image-guided cancer radiotherapy method. For MRI-guided radiotherapy, the proper energy of a therapeutic beam is important for beam-designing processes, and the magnetic-induced dose perturbation would be mainly influenced, especially the perturbation surrounding the tissue-air or air-tissue interfaces. Thus, it was necessary to investigate the impact of beam energy from photon, proton, and carbon ion beams on the magnetic-induced dose perturbations. MATERIALS AND METHODS: Using a phantom of a water-air-water structure, the dose distributions were calculated with or without the presence of a 1.5 T uniform magnetic field through GEANT4. Based on the calculated doses, magnetic-induced dose perturbations were then obtained. For investigating the effects of beam energies on magnetic-induced dose perturbations, low-, middle-, and high-beam energies were adopted for each beam type. RESULTS AND DISCUSSION: For photon beams, the dose perturbations were increased as the beam energies increased. At the up water-air interface, the maximum perturbations exceeded 50%. Near the edge of the radiation field, perturbations of 5%-20% were achieved. For proton and carbon ion beams, their Bragg peaks were shifted from original positions, and the shifting distances were increased with the increased beam energies. However, no evident magnetic-induced dose perturbations were noted at the up water-air interface and bottom air-water interface for all the beam energies. To some extent, this study provided references for assessing the effects of beam energies on magnetic-induced dose perturbations, especially the perturbations around the air cavities inside cancer patients. CONCLUSION: In MRI-guided cancer radiotherapy, the dose perturbation effects for therapeutic beams are relatively obvious, and the beam energies of therapeutic beams have large impacts on the magnetic-induced dose perturbations with the presence of a 1.5 T transverse magnetic field.

Modulation of lateral positions of Bragg peaks via magnetic fields inside cancer patients: Toward magnetic field modulated proton therapy.

PURPOSE: This work investigated whether the Bragg peak (BP) positions of proton beams can be modulated to produce uniform doses and cover a tumor under the magnetic fields inside cancer patients, and whether magnetic field modulated proton therapy (MMPT) is effective in vital organ protection. METHODS: The authors initially constructed an ideal water phantom comprising a central tumor surrounded by cuboid organ regions using GEANT4. Second, we designed the proton beams passing through the gap between two adjacent organ regions during beam configuration. Third, we simulated the beam transports under magnetic fields inside the phantom through GEANT4. Then, the beams were discarded, which did not stop in the tumor. Fourth, the authors modulated the intensities of the remaining beams to produce uniform tumor doses. Subsequently, the calculated MMPT doses were compared with those of traditional methods, such as single, opposing, orthogonal, and box fields. Moreover, the authors repeated the above research procedures for abdominal anatomies comprising tumors at the pancreatic tail and liver to evaluate whether MMPT is effective for the human anatomy. RESULTS: For the water phantom, the vital organ doses were approximately 50%, 30%, 30%, and 15% for the single, opposing, orthogonal, and box fields, respectively. As the vital organ doses decreased, the organ volume receiving proton irradiations for the opposing, orthogonal, and box fields increased by two, two, and four times compared with that for the single field. The vital organ volume receiving proton irradiations were controlled to a fairly low level through MMPT, whereas the BP positions of the proton beams were properly modulated through the magnetic fields inside the phantom. The tumor was sufficiently covered by a 95% dose line, and the maximum tumor doses were smaller than 110%. For the pancreatic tumor case, the proton beams were curved and bypassed the kidney to generate uniform doses inside the tumor through MMPT. In the liver tumor case, the liver volume receiving proton irradiations was reduced by approximately 40% through MMPT compared with traditional methods. CONCLUSIONS: The BP positions can be intentionally modulated to produce uniform tumor doses under the magnetic fields inside cancer patients. In some special cases, the vital organs surrounding the tumor can almost be exempted from proton irradiations without sacrificing tumor dose coverage through MMPT. For the tumors inside parallel organs, the parallel organ volume receiving proton irradiations was largely reduced through MMPT. The results of this study can serve as beneficial implications for future proton therapy studies with reduced vital organ damage and complications.

Measurement of dose in radionuclide therapy by using Cerenkov radiation.

This work aims to determine the relationship between Cerenkov photon emission and radiation dose from internal radionuclide irradiation. Water and thyroid phantoms were used to simulate the distribution of Cerenkov photon emission and dose deposition through Monte Carlo method. The relationship between Cerenkov photon emission and dose deposition was quantitatively analyzed. A neck phantom was also used to verify Cerenkov photon detection for thyroid radionuclide therapy. Results show that Cerenkov photon emission and dose deposition exhibit the same distribution pattern in water phantom, and this relative distribution relationship also existed in the thyroid phantom. Moreover, Cerenkov photon emission exhibits a specific quantitative relation to dose deposition. For thyroid radionuclide therapy, only a part of Cerenkov photon produced by thyroid could penetrate the body for detection; therefore, the use of Cerenkov radiation for measurement of radionuclide therapy dose may be more suitable for superficial tumors. This study demonstrated that Cerenkov radiation has the potential to be used for measuring radiation dose for radionuclide therapy.