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Purpose To classify COVID-19, COVID-19-like and non-COVID-19 interstitial pneumonia using lung CT radiomic features. Material and Methods CT data of 115 patients with respiratory symptoms suspected for COVID-19 disease were retrospectively analyzed. Based on the results of nasopharyngeal swab, patients were divided into two main groups, COVID-19 positive (C +) and COVID-19 negative (C−), respectively. C− patients, however, presented with interstitial lung involvement. A subgroup of C−, COVID-19-like (CL), were considered as highly suggestive of COVID pneumonia at CT. Radiomic features were extracted from the whole lungs. A dual machine learning (ML) model approach was used. The first one excluded CL patients from the training set, eventually included on the test set. The second model included the CL patients also in the training set. Results The first model classified C + and C− pneumonias with AUC of 0.83. CL median response (0.80) was more similar to C + (0.92) compared to C− (0.17). Radiomic footprints of CL were similar to the C + ones (possibly false negative swab test). The second model, however, merging C + with CL patients in the training set, showed a slight decrease in classification performance (AUC = 0.81). Conclusion Whole lung ML models based on radiomics can classify C + and C− interstitial pneumonia. This may help in the correct management of patients with clinical and radiological stigmata of COVID-19, however presenting with a negative swab test. CL pneumonia was similar to C + pneumonia, albeit with slightly different radiomic footprints.

Background/aim To assess predictors of local control (LC) for stereotactic ablative radiotherapy (SAbR) in pulmonary oligometastatic disease (OMD) from gastrointestinal (GI) malignancies. Patients and methods Patients with pulmonary OMD treated with SAbR from January 2016 to December 2018 were included in this observational analysis. Primary endpoint was LC. Uni- and multivariate analyses to assess variable correlations were conducted. Results Thirty-seven patients and 59 lung metastases were evaluated. The delivered dose was 30-60 Gy in 3-8 fractions. After a median follow-up of 23.0 months (range=6.3-50.4 months), LC rate at 1/2 years was 89.7%/85.0%, and increased to 96.0%/91.0% for lesions treated with a biologically effective dose (BED10) ≥100 Gy (p=0.03). RECIST response at 6 months was predictive for LC (p=0.002). Conclusion SAbR is an effective option for pulmonary OMD from GI malignancies. A BED10 ≥100 Gy and radiological response at 6 months can affect LC.

In the artificial intelligence era, machine learning (ML) techniques have gained more and more importance in the advanced analysis of medical images in several fields of modern medicine. Radiomics extracts a huge number of medical imaging features revealing key components of tumor phenotype that can be linked to genomic pathways. The multi-dimensional nature of radiomics requires highly accurate and reliable machine-learning methods to create predictive models for classification or therapy response assessment. Multi-parametric breast magnetic resonance imaging (MRI) is routinely used for dense breast imaging as well for screening in high-risk patients and has shown its potential to improve clinical diagnosis of breast cancer. For this reason, the application of ML techniques to breast MRI, in particular to multi-parametric imaging, is rapidly expanding and enhancing both diagnostic and prognostic power. In this review we will focus on the recent literature related to the use of ML in multi-parametric breast MRI for tumor classification and differentiation of molecular subtypes. Indeed, at present, different models and approaches have been employed for this task, requiring a detailed description of the advantages and drawbacks of each technique and a general overview of their performances.

As opposed to external beam radiation therapy (EBRT), treatment planning systems (TPS) dedicated to intraoperative radiation therapy (IORT) were not subject to radical modifications in the last two decades. However, new treatment regimens such as ultrahigh dose rates and combination with multiple treatment modalities, as well as the prospected availability of dedicated in-room imaging, call for important new features in the next generation of treatment planning systems in IORT. Dosimetric accuracy should be guaranteed by means of advanced dose calculation algorithms, capable of modelling complex scattering phenomena and accounting for the non-tissue equivalent materials used to shape and compensate electron beams. Kilovoltage X-ray based IORT also presents special needs, including the correct description of extremely steep dose gradients and the accurate simulation of applicators. TPSs dedicated to IORT should also allow real-time imaging to be used for treatment adaptation at the time of irradiation. Other features implemented in TPSs should include deformable registration and capability of radiobiological planning, especially if unconventional irradiation schemes are used. Finally, patient safety requires that the multiple features be integrated in a comprehensive system in order to facilitate control of the whole process.

Surgical resection after neoadjuvant treatment is the main driver for improved survival in locally advanced pancreatic cancer (LAPC). However, the diagnostic performance of computed tomography (CT) imaging to evaluate the residual tumour burden at restaging after neoadjuvant therapy is low due to the difficulty in distinguishing neoplastic tissue from fibrous scar or inflammation. In this context, radiomics has gained popularity over conventional imaging as a complementary clinical tool capable of providing additional, unprecedented information regarding the intratumor heterogeneity and the residual neoplastic tissue, potentially serving in the therapeutic decision-making process.To assess the capability of radiomic features to predict surgical resection in LAPC treated with neoadjuvant chemotherapy and radiotherapy.Patients with LAPC treated with intensive chemotherapy followed by ablative radiation therapy were retrospectively reviewed. One thousand six hundred and fifty-five radiomic features were extracted from planning CT inside the gross tumour volume. Both extracted features and clinical data contribute to create and validate the predictive model of resectability status. Patients were repeatedly divided into training and validation sets. The discriminating performance of each model, obtained applying a LASSO regression analysis, was assessed with the area under the receiver operating characteristic curve (AUC). The validated model was applied to the entire dataset to obtain the most significant features.Seventy-one patients were included in the analysis. Median age was 65 years and 57.8% of patients were male. All patients underwent induction chemotherapy followed by ablative radiotherapy, and 19 (26.8%) ultimately received surgical resection. After the first step of variable selections, a predictive model of resectability was developed with a median AUC for training and validation sets of 0.862 (95%CI: 0.792-0.921) and 0.853 (95%CI: 0.706-0.960), respectively. The validated model was applied to the entire dataset and 4 features were selected to build the model with predictive performance as measured using AUC of 0.944 (95%CI: 0.892-0.996).The present radiomic model could help predict resectability in LAPC after neoadjuvant chemotherapy and radiotherapy, potentially integrating clinical and morphological parameters in predicting surgical resection.

Background and ObjectiveTo assess the efficacy of a Risk-Adapted Ablative Radiotherapy (RAdAR) approach, after intensive induction chemotherapy, in patients with locally advanced pancreatic cancer (LAPC).Material and MethodsPatients with LAPC who received RAdAR following induction chemotherapy from January 2017 to December 2019 were included in this observational study. The RAdAR approach consisted of an anatomy- and simultaneous integrated boost (SIB)-based dose prescription strategy. RAdAR was delivered with stereotactic ablative radiation therapy (SAbR), administering 30 Gy in 5 fractions to the tumor volume (PTVt) and 50 Gy SIB (BED10 100 Gy) to the vascular involvement, or with (hypo-)fractionated ablative radiotherapy (HART) prescribing 50.4 Gy in 28 fractions to the PTVt, with a vascular SIB of 78.4 Gy (BED10 100 Gy). Primary end points were freedom from local progression (FFLP), overall survival (OS), and progression-free survival (PFS).ResultsSixty-four LAPC patients were included. Induction chemotherapy consisted of gemcitabine/nab-paclitaxel in 60.9% and FOLFIRINOX in 39.1% of cases. SAbR was used in 52 (81.2%) patients, and HART in 12 (18.8%). After RAdAR, surgery was performed in 17 (26.6%) patients. Median follow-up was 16.1 months. Overall local control (LC) rate was 78.1%, with no difference between resected and non-resected patients (2-year FFLP 75.3% vs 56.4%; p = 0.112). Median OS and PFS were 29.7 months and 8.7 months, respectively, for the entire cohort. Resected patients had a better median OS (not reached versus 26.1 months; p = 0.0001) and PFS (19 versus 5.6 months; p < 0.0001) compared to non-resected patients. In non-resected patients, no significant difference was found between SAbR and HART for median FFLP (28.1 versus 18.5 months; p = 0.614), OS (27.4 versus 25.3 months; p = 0.624), and PFS (5.7 versus 4.3 months; p = 0.486). One patient (1.6%) experienced acute grade 4 gastro-intestinal bleeding. No other acute or late grade ≥ 3 toxicities were observed.ConclusionsThe RAdAR approach, following intensive induction chemotherapy, is an effective radiation treatment strategy for selected LAPC patients, representing a promising therapeutic option in a multimodality treatment regimen.

Purpose Within the Italian Association of Medical Physics and Health Physics (AIFM) working group “FutuRuS” we carried out a survey regarding the number of the peer-reviewed articles by AIFM members. Methods We surveyed papers published in the years 2015–2019. Data extracted from Scopus included information regarding authors, title, journal, impact factor (IF), leading or standard authorship by AIFM members, keywords, type of collaboration (monocentric/multicentric/international), area of interest [radiation oncology (RO), radiology (RAD), nuclear medicine (NM), radioprotection (RP) and professional issue (PI)] and topics. Results We found 1210 papers published in peer-reviewed journals: 48%, 22%, 16%, 6%, 2 and 6% in RO, RAD, NM, RP, PI and other topics, respectively. Forty-seven percent of the papers involved monocentric teams, 31% multicentric and 22% international collaborations. Leading authorship of AIFM members was in 56% of papers, with a corresponding IF equal to 52% of the total IF (3342, IFmean = 2.8, IFmax = 35.4). The most represented journal was Physica Medica, with 15% of papers, while a relevant fraction of IF (54%) appeared in clinically oriented journals. The number of papers increased significantly between 2015 and 2016 and remained almost constant in 2017–2019. Conclusions This survey led to the first quantitative assessment of the number and theme distribution of peer-reviewed scientific articles contributed by AIFM members. It constitutes a ground basis to support future AIFM strategies and promote working groups on scientific activity of medical physicists, and to build the basis for rational comparison with other countries, first of all within Europe.

Background The current management guidelines recommend that patients with borderline resectable pancreatic adenocarcinoma (BRPC) should initially receive neoadjuvant chemotherapy. The addition of advanced radiation therapy modalities, including stereotactic body radiation therapy (SBRT) and intraoperative radiation therapy (IORT), could result in a more effective neoadjuvant strategy, with higher rates of margin-free resections and improved survival outcomes. Methods/design In this single-center, single-arm, intention-to-treat, phase II trial newly diagnosed BRPC will receive a “total neoadjuvant” therapy with FOLFIRINOX (5-fluorouracil, irinotecan and oxaliplatin) and hypofractionated SBRT (5 fractions, total dose of 30 Gy with simultaneous integrated boost of 50 Gy on tumor-vessel interface). Following surgical exploration or resection, IORT will be also delivered (10 Gy). The primary endpoint is 3-year survival. Secondary endpoints include completion of neoadjuvant treatment, resection rate, acute and late toxicities, and progression-free survival. In the subset of patients undergoing resection, per-protocol analysis of disease-free and disease-specific survival will be performed. The estimated sample size is 100 patients over a 36-month period. The trial is currently recruiting. Trial registration NCT04090463 at clinicaltrials.gov.

Objectives This study evaluated the feasibility of DWI for lesion targeting in MRI-guided breast biopsies. Furthermore, it assessed device positioning on DWI during biopsy procedures. Methods A total of 87 biopsy procedures (5/87 bilateral) consecutively performed between March 2019 and June 2020 were retrospectively reviewed: in these procedures, a preliminary DWI sequence (b = 1300 s/mm2) was acquired to assess lesion detectability. We included 64/87 procedures on lesions detectable at DWI; DWI sequences were added to the standard protocol to localize lesion and biopsy device and to assess the site marker correct positioning. Results Mass lesions ranged from 5 to 48 mm, with a mean size of 10.7 mm and a median size of 8 mm. Non-mass lesions ranged from 7 to 90 mm, with a mean size of 33.9 mm and a median size of 31 mm. Positioning of the coaxial system was confirmed on both T1-weighted and DWI sequences. At DWI, the biopsy needle was detectable in 62/64 (96.9%) cases; it was not visible in 2/64 (3.1%) cases. The site marker was always identified using T1-weighted imaging; a final DWI sequence was acquired in 44/64 cases (68.8%). In 42/44 cases (95.5%), the marker was recognizable at DWI. Conclusions DWI can be used as a cost-effective, highly reliable technique for targeting both mass and non-mass lesions, with a minimum size of 5 mm, detectable at pre-procedural DWI. DWI is also a feasible technique to localize the biopsy device and to confirm the deployment of the site marker. Key Points • MRI-guided breast biopsy is performed in referral centers by an expert dedicated staff, based on prior MR imaging; contrast agent administration is usually needed for lesion targeting. • DWI represents a feasible, highly reliable technique for lesion targeting, avoiding contrast agent administration. • DWI allows a precise localization of both biopsy needle device and site marker.

Background and ObjectiveTo assess the dosimetric feasibility of a stereotactic body radiotherapy (SBRT) dose escalated protocol, with a simultaneous integrated boost (SIB) and a simultaneous integrated protection (SIP) approach, in patients with locally advanced pancreatic cancer (LAPC).Material and MethodsTwenty LAPC lesions, previously treated with SBRT at our Institution, were re-planned. The original prescribed and administered dose was 50/30/25 Gy in five fractions to PTVsib (tumor-vessel interface [TVI])/PTVt (tumor volume)/PTVsip (overlap area between PTVt and planning organs at risk volume [PRVoars]), respectively. At re-planning, the prescribed dose was escalated up to 60/40/33 Gy in five fractions to PTVsib/PTVt/PTVsip, respectively. All plans were performed using an inspiration breath hold (IBH) technique and generated with volumetric modulated arc therapy (VMAT). Well-established and accepted OAR dose constraints were used (D0.5cc < 33 Gy for luminal OARs and D0.5cc < 38 Gy for corresponding PRVoars). The primary end-point was to achieve a median dose equal to the prescription dose for the PTVsib with D98≥ 95% (95% of prescription dose is the minimum dose), and a coverage for PTVt and PTVsip of D95≥95%, with minor deviations in OAR dose constraints in < 10% of the plans.ResultsPTVsib median (± SD) dose/D95/conformity index (CI) were 60.54 (± 0.85) Gy/58.96 (± 0.86) Gy/0.99 (± 0.01), respectively; whilst PTVt median (± SD) dose/D95 were 44.51 (± 2.69) Gy/38.44 (± 0.82) Gy, and PTVsip median (± SD) dose/D95 were 35.18 (± 1.42) Gy/33.01 (± 0.84) Gy, respectively. With regard to OARs, median (± SD) maximum dose (D0.5cc) to duodenum/stomach/bowel was 29.31 (± 5.72) Gy/25.29 (± 6.90) Gy/27.03 (± 5.67) Gy, respectively. A minor acceptable deviation was found for a single plan (bowel and duodenum D0.5cc=34.8 Gy). V38 < 0.5 cc was achieved for all PRV luminal OARs.ConclusionsIn LAPC patients SBRT, with a SIB/SIP dose escalation approach up to 60/40/33 Gy in five fractions to PTVsib/PTVt/PTVsip, respectively, is dosimetrically feasible with adequate PTVs coverage and respect for OAR dose constraints.

Abstarct Methods and Materials From July 2006 to December 2015, 295 patients suitable for breast-conserving therapy entered a single-arm phase II study and were treated with IOERT as radical treatment. Inclusion criteria were age >50, postmenopausal status, cT1N0M0 stage, grade G1-G2, positive estrogen receptor status; unicentric and unifocal disease, histologically proven invasive ductal carcinoma no previous breast irradiation, good performance status. Results With a median follow-up of 7.1 years (95% CI, 6.5;7.4) 6 women (2.0%) experienced a true local recurrence (reappearance of the tumour in the same quadrant). Five-year overall survival and local recurrence-free survival were 96% (95% CI, 92.9;97.8) and 94.9% (95% CI, 91.6;97.0) respectively. Conclusion Our trial suggests that, in highly selected early stage breast cancers, a single-dose IOERT can be safely delivered with excellent results and very low long-term recurrence rates.

ObjectivesTo test whether 3T MRI radiomics of breast malignant lesions improves the performance of predictive models of complete response to neoadjuvant chemotherapy when added to other clinical, histological and radiological information.MethodsWomen who consecutively had pre-neoadjuvant chemotherapy (NAC) 3T DCE-MRI between January 2016 and October 2019 were retrospectively included in the study. 18F-FDG PET-CT and histological information obtained through lesion biopsy were also available. All patients underwent surgery and specimens were analyzed. Subjects were divided between complete responders (Pinder class 1i or 1ii) and non-complete responders to NAC. Geometric, first order or textural (higher order) radiomic features were extracted from pre-NAC MRI and feature reduction was performed. Five radiomic features were added to other available information to build predictive models of complete response to NAC using three different classifiers (logistic regression, support vector machines regression and random forest) and exploring the whole set of possible feature selections.ResultsThe study population consisted of 20 complete responders and 40 non-complete responders. Models including MRI radiomic features consistently showed better performance compared to combinations of other clinical, histological and radiological information. The AUC (ROC analysis) of predictors that did not include radiomic features reached up to 0.89, while all three classifiers gave AUC higher than 0.90 with the inclusion of radiomic information (range: 0.91-0.98).ConclusionsRadiomic features extracted from 3T DCE-MRI consistently improved predictive models of complete response to neo-adjuvant chemotherapy. However, further investigation is necessary before this information can be used for clinical decision making.

Background and ObjectiveThe aim of this study was to assess the ability of Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (18F-FDG PET/CT) to provide functional information useful in predicting pathological response to an intensive neoadjuvant chemo-radiotherapy (nCRT) protocol for both esophageal squamous cell carcinoma (SCC) and adenocarcinoma (ADC) patients.Material and MethodsEsophageal carcinoma (EC) patients, treated in our Center between 2014 and 2018, were retrospectively reviewed. The nCRT protocol schedule consisted of an induction phase of weekly administered docetaxel, cisplatin, and 5-fluorouracil (TCF) for 3 weeks, followed by a concomitant phase of weekly TCF for 5 weeks with concurrent radiotherapy (50–50.4 Gy in 25–28 fractions). Three 18F-FDG PET/CT scans were performed: before (PET1) and after (PET2) induction chemotherapy (IC), and prior to surgery (PET3). Correlation between PET parameters [maximum and mean standardized uptake value (SUVmax and SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG)], radiomic features and tumor regression grade (TGR) was investigated.ResultsFifty-four patients (35 ADC, 19 SCC; 48 cT3/4; 52 cN+) were eligible for the analysis. Pathological response to nCRT was classified as major (TRG1-2, 41/54, 75.9%) or non-response (TRG3-4, 13/54, 24.1%). A major response was statistically correlated with SCC subtype (p = 0.02) and smaller tumor length (p = 0.03). MTV and TLG measured prior to IC (PET1) were correlated to TRG1-2 response (p = 0.02 and p = 0.02, respectively). After IC (PET2), SUVmean and TLG correlated with major response (p = 0.03 and p = 0.04, respectively). No significance was detected when relative changes of metabolic parameters between PET1 and PET2 were evaluated. At textural quantitative analysis, three independent radiomic features extracted from PET1 images ([JointEnergy and InverseDifferenceNormalized of GLCM and LowGrayLevelZoneEmphasis of GLSZM) were statistically correlated with major response (p < 0.0002).Conclusions18F-FDG PET/CT traditional metrics and textural features seem to predict pathologic response (TRG) in EC patients treated with induction chemotherapy followed by neoadjuvant chemo-radiotherapy. Further investigations are necessary in order to obtain a reliable predictive model to be used in the clinical practice.

Background and purpose: To explore the use of texture analysis (TA) features of patients' 3D dose distributions to improve prediction modelling of treatment complication rates in prostate cancer radiotherapy. Material and methods: Late toxicity scores, dose distributions, and non-treatment related (NTR) predictors for late toxicity, such as age and baseline symptoms, of 351 patients of the hypofractionation arm of the HYPRO randomized trial were used in this study. Apart from DVH parameters, also TA features of rectum and bladder 3D dose distributions were used for predictive modelling of gastrointestinal (GI) and genitourinary (GU) toxicities. Logistic Normal Tissue Complication Probability (NTCP) models were derived, using only NTR parameters, NTR + DVH, NTR + TA, and NTR + DVH + TA. Results: For rectal bleeding, the area under the curve (AUC) for using only NTR parameters was 0.58, which increased to 0.68, and 0.73, when adding DVH or TA parameters respectively. For faecal incontinence, the AUC went up from 0.63 (NTR only), to 0.68 (+ DVH) and 0.73 (+ TA). For nocturia, adding TA features resulted in an AUC increase from 0.64 to 0.66, while no improvement was seen when including DVH parameters in the modelling. For urinary incontinence, the AUC improved from 0.68 to 0.71 (+ DVH) and 0.73 (+ TA). For GI, model improvements resulting from adding TA parameters to NTR instead of DVH were statistically significant (p

Motion management in radiation oncology is an important aspect of modern treatment planning and delivery. Special attention has been paid to control respiratory motion in recent years. However, other medical procedures related to both diagnosis and treatment are likely to benefit from the explicit control of breathing motion. Quantitative imaging - including increasingly important tools in radiology and nuclear medicine - is among the fields where a rapid development of motion control is most likely, due to the need for quantification accuracy. Emerging treatment modalities like focussed-ultrasound tumor ablation are also likely to benefit from a significant evolution of motion control in the near future. In the present article an overview of available respiratory motion systems along with ongoing research in this area is provided. Furthermore, an attempt is made to envision some of the most expected developments in this field in the near future.

The year 1895, with the discovery of X-rays, can be considered as the beginning of radiotherapy. Subsequent developments were implemented to improve the quality and precision of radiation delivery. In the last decades, radiotherapy has achieved huge technological progress leading to the introduction of intensity-modulated radiation therapy (IMRT), image-guided radiation therapy (IGRT), and volumetric modulated arc therapy (VMAT). Through the delivery of nonuniform intensities of radiation, these innovations allow a significantly more precise and effective treatment, maximizing and optimizing the dose to the target tumor mass while simultaneously minimizing exposure of the surrounding normal tissues. However, these modalities based on the anatomical data deriving from traditional simulation have obvious limitations in delineating tumor margins, because of variations in the apparent tumor size due to inflammation, edema, and necrosis. The introduction in the clinical practice of molecular imaging techniques, such as positron-emission tomography (PET) and new magnetic resonance imaging (MRI) sequences, may overcome these limitations, thanks to the visualization of surrogates of several pathophysiological characteristics of tumor tissue, such as proliferation, metabolism, hypoxia, perfusion, etc. By knowing the tissue differentiation and biology inside the tumor, the dose distribution could be tailored accordingly. As a consequence, the integration of molecular imaging in an individualized radiation treatment planning warrants a significant improvement in the ability of modern radiotherapy to precisely target tumor while limiting as much as possible the irradiation of normal tissues. The most common molecular images for tumor volume delineation and for assessment of the pathophysiological characteristics of tissues derive from PET data.

Purpose: The aim of this study was to implement a Dirichlet process mixture (DPM) model for automatic tumor edge identification on 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET)images by optimizing the parameters on which the algorithm depends, to validate it experimentally, and to test its robustness. Methods: The DPM model belongs to the class of the Bayesian nonparametric models and uses the Dirichlet process prior for flexible nonparametric mixture modeling, without any preliminary choice of the number of mixture components. The DPM algorithm implemented in the statistical software package R was used in this work. The contouring accuracy was evaluated on several imagedata sets: on an IEC phantom (spherical inserts with diameter in the range 10–37 mm) acquired by a Philips Gemini Big Bore PET-CT scanner, using 9 different target-to-background ratios (TBRs) from 2.5 to 70; on a digital phantom simulating spherical/uniform lesions and tumors, irregular in shape and activity; and on 20 clinical cases (10 lung and 10 esophageal cancer patients). The influence of the DPM parameters on contour generation was studied in two steps. In the first one, only the IEC spheres having diameters of 22 and 37 mm and a sphere of the digital phantom (41.6 mm diameter) were studied by varying the main parameters until the diameter of the spheres was obtained within 0.2% of the true value. In the second step, the results obtained for this training set were applied to the entire data set to determine DPM based volumes of all available lesions. These volumes were compared to those obtained by applying already known algorithms (Gaussian mixture model and gradient-based) and to true values, when available. Results: Only one parameter was found able to significantly influence segmentation accuracy (ANOVA test). This parameter was linearly connected to the uptake variance of the tested region of interest (ROI). In the first step of the study, a calibration curve was determined to automatically generate the optimal parameter from the variance of the ROI. This “calibration curve” was then applied to contour the whole data set. The accuracy (mean discrepancy between DPM model-based contours and reference contours) of volume estimation was below (1 ± 7)% on the whole data set (1 SD). The overlap between true and automatically segmented contours, measured by the Dice similarity coefficient, was 0.93 with a SD of 0.03. Conclusions: The proposed DPM model was able to accurately reproduce known volumes of FDG concentration, with high overlap between segmented and true volumes. For all the analyzed inserts of the IEC phantom, the algorithm proved to be robust to variations in radius and in TBR. The main advantage of this algorithm was that no setting of DPM parameters was required in advance, since the proper setting of the only parameter that could significantly influence the segmentation results was automatically related to the uptake variance of the chosen ROI. Furthermore, the algorithm did not need any preliminary choice of the optimum number of classes to describe the ROIs within PETimages and no assumption about the shape of the lesion and the uptake heterogeneity of the tracer was required.

Objectives To test whether 3 T multiparametric magnetic resonance imaging (mMRI) provides information related to molecular subtypes of breast cancer. Methods Women with mammographic or US findings of breast lesions (BI-RADS 4–5) underwent 3 T mMRI (DCE, DWI and MR spectroscopy). The histological type of breast cancer was assessed. Estrogen-receptor (ER), progesterone-receptor (PgR), Ki-67 status and HER-2 expression, assessed by immunohistochemistry (IHC), defined four molecular subtypes: Luminal-A, Luminal-B, HER2-enriched and triple-negative. Non-parametric tests (Kruskal-Wallis, k-sample equality of medians, and Mann-Whitney), logistic regression or ANOVA, and a multivariate analysis were performed to investigate correlations between the four molecular subtypes and mMRI (lesion volume, margins or distribution, enhancement pattern, ADC, type of kinetic curve, and total choline (tCho) signal-to-noise-ratio (SNR)). A ROC analysis was finally performed to test the diagnostic power of a multivariate logistic regression model. Results 433 patients (453 lesions) were considered. Volume was smaller in Luminal-B and larger in triple-negative tumours compared to the other subtypes combined. Margins were significantly correlated to Luminal-A and Luminal-B. The type of curve was significantly correlated to Luminal-A. ADC values were higher in Luminal-A. tCho SNR was higher in triple-negative tumours. The ROC analysis showed that the area under the curve (AUC) significantly improved when multiple MRI features were used compared to individual parameters. Conclusions A significant correlation was found between some MRI features and molecular subtypes of breast tumours. A multiparametric approach improved the diagnostic power of MRI. However, further research is needed in order to predict the molecular subtype on the sole basis of mMRI.

Purpose: To find an optimized workflow for the use of respiratory‐gated PET (4D‐PET) in target volume delineation of tumors subject to respiratory‐gated radiation therapy.Methods: 15 patients with lung (11) and pancreas (4) tumors who had FDG‐PET‐CT for target delineation prior to EBRT were studied. Patients were selected among the group that showed respiratory‐induced tumor motion 〉5mm. 4D‐PET was performed by means of a Philips Gemini BigBore scanner, using the Varian RPM gating system. An identical system was available at the linac for treatment. The breathing cycle was equally divided in 4 phases, according to a previous study. Since planning was made on a single CT‐phase, no ITV was explicitly built from the set of phases. The BTV was identified with SUV=2.2 threshold and the PTV was obtained expanding the BTV by 8mm(S‐I), 5mm(A‐P) and 3mm(L‐R) to account for residual motion and setup errors. The most advantageous CT‐phase for treatment planning was then identified by simulating plans on each phase and analyzing the resulting DVHs of OARs (lung, trachea, oesophagus, spinal cord, left ventricle). Results: The observed maximum range of motion was 5.5mm(L‐R), 12.3mm(A‐P) and 19.2mm(S‐I). The standard deviation of the BTV volume in the 4 phases ranged from 6% to 13.7%. V20 (lung) ranged 7.1%–15.2% in inspiration and 7.8%–18.6% in expiration. The mean dose to the oesophagus ranged 0.1–2.2Gy in inspiration and 1.4–2.0Gy in expiration. In general, the dose to OARs was smaller when planning on a single phase than on the overall, respiratory‐uncontrolled volume (p‐value〈0.05). Conclusions: The BTV volume was almost constant between phases, confirming that the motion might be described by 4 phases. There was no obvious choice of the optimal phase for treatment planning, suggesting patient‐by‐patient studies. However, planning and delivery on one phase consistently allowed dose sparing to be obtained compared to non‐gated techniques.

To test 3T proton magnetic resonance spectroscopy (1H-MRS) for breast mass lesions. Patients with BI-RADS 4–5 lesions at mammography/ultrasound were prospectively enrolled. After contrast-enhanced breast MRI, single-voxel MRS (point-resolved volume selection, PRESS); pencil-beam shimming; volume of interest 1 cm3; TR/TE = 3000/135 ms) was performed. Spectra were considered reliable if the full width at half maximum (FWHM) of the water peak was ≤45 Hz. A signal-to-noise ratio of the total choline (tCho) peak at 3.21 ppm ≥2 was used as cutoff for malignancy. All lesions underwent needle sampling. Final pathology was available for all malignant lesions; for benign lesions the reference standard was final pathology or at least 1-year negative follow-up. Reliable spectra were obtained in 115/127 lesions (91%), with a mean FWHM of 32.4 Hz (range 8–45 Hz). A tCho peak SNR ≥2 was detected in 66 malignant lesions (62 invasive cancers; 4 ductal carcinoma in situ) and in 3 benign lesions. Excluding lesions located ≤1 cm from the skin (n = 3) or pectoral muscle (n = 11), sensitivity was 65/73 [89%, 95% confidence interval (CI): 80–95%], and specificity 25/28 (89%) (95% CI: 72–98%). Considering only invasive cancers, sensitivity reached 61/68 (90%, 95% CI: 81–96%). MRS additional time was 8 min. When lesions close to the skin or pectoral muscle are excluded, 3T 1H-MRS of mass lesions ≥1 cm showed a high diagnostic performance, however, insufficient to avoid needle biopsy.

To test a single-energy low-voltage CT protocol for pancreatic adenocarcinoma.A total of 30 patients with pathology-proven pancreatic adenocarcinoma underwent 64-row MDCT with arterial phase at 80 kV and were compared to a similar group of 30 patients scanned with a 120 kV protocol. Scans were compared for quantitative image parameters (attenuation and standard deviation in the pancreas, tumor, aorta), CTDI and DLP using an unpaired t-test. Image noise values for each protocol (SD of the psoas) were compared using an unpaired t-test. Effective dose was calculated for each protocol. CNR (=conspicuity/SDnoise) and FOM (CNR2/ED) were calculated. The Catphan600 phantom was used to evaluate image non-uniformity, noise, spatial resolution, and low contrast detectability.Mean patient weight was 68 kg in the study group and 73 kg in the control group (p=0.0355), while patient diameters at the celiac axis were not significantly different. Mean attenuation was significantly higher at 80 kV in the aorta (517.5±116.4 vs 290.3±76.4 HU) and normal pancreas (154.0±39.95 vs 90.02±19.01 HU) (all p0.0001), while no significant difference was observed for adenocarcinoma (61.43±35.61 vs 47.45±18.95; p=n.s.). CTDI and DLP were significantly lower at 80 kV (6.00±0.90 mGy vs 10.24±2.93 mGy, and 180.4±35.49 mGy cm vs 383.8±117 mGy cm, respectively; all p0.0001). Tumor conspicuity (HUpancreas-HUtumor) was significantly higher at 80 kV (94.2±39.3 vs 39.5±22 HU; p0.0001). Mean image noise was significantly higher at 80kV (28.32±10.06 vs 19.7±7.1HU; p0.0001). Effective dose was significantly lower at 80 kV (1.984±0.39 vs 5.75±1.75 mSv; p0.0001). The total DLP for the exam was 1024±31.86 mGy cm for the 80 kV protocol and 1357±62.60 mGy cm for the 120 kV protocol (p0.0001). Phantoms showed higher non-uniformity, slightly higher noise, slightly lower MTF (50%) and slightly higher percentage contrast for the 80 kV protocol.Single-source 80 kV pancreatic phase scanning results in higher conspicuity of pancreatic adenocarcinoma and FOM and in significant dose reduction while maintaining acceptable image quality.

Introduction The aim of this work was to assess the role of 3T-MR spectroscopy (MRS) in the multi-parametric MRI evaluation of breast lesions, using a pattern-recognition based classification method. Methods 291 patients (301 lesions, median 2.3 cm3) were enrolled in the study (age 18–85 y, mean 54.2 y). T1-TSE (TR/TE = 400/10 ms) and T2-STIR imaging (TR/TE = 5000/60 ms), dynamic-contrast-enhanced MRI (DCE-MRI), apparent diffusion coefficient (ADC) (b = 0–800 s/mm2), and single-voxel MRS (10 × 10 × 10 mm3, PRESS, TR/TE = 3000 ms/135 ms) were performed by means of a 3T scanner. MRS results were accepted if the FWHM of the water peak was ⩽45 Hz. Total choline (tCho) was considered detected if the signal-to-noise ratio (SNR) of the 3.2 ppm peak was ⩾2. A classifier-based analysis (support-vector-machines, SVM) was performed with 4-dimensional vectors including type of margin, DCE-MRI kinetic curve type, ADC mean value, and tCho SNR. A comparison with 3-dimensional vectors (without tCho SNR) was used to assess MRS impact on sensitivity, specificity, and positive-negative predictive values (PPV-NPV) for malignancy. Results 228 lesions (180 malignant/48 benign) showed acceptable spectral quality. Comparison of classification results with histopathological examination of surgical specimens showed sensitivity = 93.7%, specificity = 84.9%, PPV = 95.2%, NPV = 81.5% without the inclusion of MRS in the SVM analysis. When MRS was included, the figures increased to 95.1%, 90.7%, 97.2%, and 85.0%, respectively. Conclusions Inclusion of 3T-MRS in the multi-parametric MRI evaluation of breast lesions improved the performance of the SVM-based classifier, showing a possible role of high-field MR spectroscopy in the differential diagnosis between benign and malignant breast lesions. Further research is however needed to confirm this initial evidence.

Purpose To focus on the current status of MR spectroscopy (MRS) and multiparametric MR imaging (mMRI) of breast lesions, from the standpoint of the medical physicist in a multidisciplinary clinical setting. Methods A meta-analysis of the available literature on the subject has been performed. Studies at 1.5 T as well as at 3.0 T were considered. Higher magnetic fields were also included for the sake of completeness. Results MRS of breast lesions has not yet entered the field of routine examinations due to technical difficulties and confounding factors that limit its sensitivity. Major limitations include patient motion, strong lipid signals in MR spectra, and suboptimal performances of dedicated breast coils. In a recent meta-analysis [1], pooled sensitivity and specificity were reported as 73% and 88%, respectively. On the other hand, mMRI shows increased sensitivity and specificity compared to single MRI modalities. A study on mMRI at 7 T has recently reported a sensitivity of 100% and a specificity of 88.2% when dynamic studies and DWI were simultaneously taken into account [2]. In another study, MRS was shown to improve the performance of a machine-learning classifier when added to mMRI based on morphology, dynamic imaging and DWI [3]. Conclusions MR spectroscopy of breast lesions might finally find its role in the clinical practice. Multiparametric MRI has shown promising results in the characterization of suspicious breast lesions and in the correlation to molecular subtypes of breast tumors. The role of the medical physicist in a multidisciplinary clinical setting is increasingly recognized as a key factor in order to guarantee the quality of the information provided by quantitative MRI imaging techniques.

Background: Women with early stage disease not only have a better prognosis, but also have the opportunity to preserve their breasts. Despite the positive evidence and outcomes for breast-conserving therapy (BCT), many women are unable or unwilling to undergo 5–7 weeks of external-beam radiotherapy (EBRT). We report the results of a single-institution phase II trial of accelerated partial breast irradiation (APBI) using a single dose of intraoperative electron radiotherapy (IOERT) in patients with low risk early stage breast cancer. Methods and materials: From July 2006 to December 2009, 226 patients suitable for BCT were enrolled in a phase II trial with IOERT as radical treatment immediately after surgical resection. All patients had biopsy proven cancer. After the surgeon temporarily re-approximated the excision cavity, a dose of 21 Gy using IOERT was delivered to the tumor bed with a margin of 2 cm laterally. Results: No acute reactions were reported after irradiation. Three patients experienced a transient edema. In 7 others a haematoma was observed. No cases of liponecrosis were observed. With a mean follow-up of 49 months (range 31–66 months), only one case of local recurrence has been reported. The observed toxicity was considered acceptable. As to cosmetic results, at 6 months after the end of IORT, 71/226 patients (31.4.%) had a score of 2 for symmetry and contour (asymmetry exhibited by 1/3 or less of volume breast), while 19/226 (8.4%) had a score 3 (asymmetry greater than 1/3 of breast volume). These findings remained unchanged at the following examinations. No breast oedema, discoloration at site or scar prominence were observed. Discussion: IOERT has significant advantages compared to other post-operative APBI approaches. The surgical re-approximation of the tumor bed, combined with the high quality of electron beam radiation, generates substantially more uniform dose distributions. IOERT offers the advantage of an excellent delineation of the tumor bed under visual control and high sparing of normal tissue, including the skin. IOERT delivers a very high biologically dose at the time of the surgery, when residual tumor cells are more rapidly proliferating. IOERT is insensitive to chemotherapy sequencing since all of the radiation is given during the surgery. IOERT offers low-risk women the possibility of a one-day procedure to treat their cancer and preserve their breast. The results of our study are very encouraging compared with other series with IOERT or APBI. The absolute recurrence rate of 0.4% and the recurrence rate per year of 0.2% of the present study are lower compared to the ones from the largest series with IOERT ever published (3.6% and 1.2%, respectively) (1). Conclusion: APBI using a single dose of IOERT can be delivered safely in women with early, low risk breast cancer. A longer follow-up is needed to ascertain its efficacy compared to that of the current standard treatment of whole breast irradiation. References 1. Veronesi U, Orecchia R, Luini A, et al. Intraoperative radiotherapy during breast conserving surgery: a study on 1,822 cases treated with electrons. Breast Cancer Res Treat 2010; 124:141–151. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P4-16-08.

The aim of this work was to investigate the main dosimetric characteristics and the performance of an A26 Exradin ionization microchamber (A26 IC) and a W1 Exradin plastic scintillation detector (W1 PSD) in small photon beam dosimetry for treatment planning system commissioning and quality assurance programme.Detector characterization measurements (short-term stability, dose linearity, angular dependence and energy dependence) were performed in water for field sizes up to 10 × 10 cmResults were compared with those obtained with other detectors we already use for small photon beam dosimetry. A26 IC and W1 PSD showed a linear dose response. While the A26 IC showed no energy dependence, the W1 PSD showed energy dependence within 2%; no angular dependence was registered. PThe results of our investigation confirm that A26 IC and W1 PSD could play an important role in small field relative dosimetry. Advances in knowledge: Dosimetric characteristics of Exradin A26 ionization microchamber and W1 plastic scintillation detector for small field dosimetry.

The aim of this study was to implement a Dirichlet process mixture (DPM) model for automatic tumor edge identification on (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) images by optimizing the parameters on which the algorithm depends, to validate it experimentally, and to test its robustness.The DPM model belongs to the class of the Bayesian nonparametric models and uses the Dirichlet process prior for flexible nonparametric mixture modeling, without any preliminary choice of the number of mixture components. The DPM algorithm implemented in the statistical software package R was used in this work. The contouring accuracy was evaluated on several image data sets: on an IEC phantom (spherical inserts with diameter in the range 10-37 mm) acquired by a Philips Gemini Big Bore PET-CT scanner, using 9 different target-to-background ratios (TBRs) from 2.5 to 70; on a digital phantom simulating spherical/uniform lesions and tumors, irregular in shape and activity; and on 20 clinical cases (10 lung and 10 esophageal cancer patients). The influence of the DPM parameters on contour generation was studied in two steps. In the first one, only the IEC spheres having diameters of 22 and 37 mm and a sphere of the digital phantom (41.6 mm diameter) were studied by varying the main parameters until the diameter of the spheres was obtained within 0.2% of the true value. In the second step, the results obtained for this training set were applied to the entire data set to determine DPM based volumes of all available lesions. These volumes were compared to those obtained by applying already known algorithms (Gaussian mixture model and gradient-based) and to true values, when available.Only one parameter was found able to significantly influence segmentation accuracy (ANOVA test). This parameter was linearly connected to the uptake variance of the tested region of interest (ROI). In the first step of the study, a calibration curve was determined to automatically generate the optimal parameter from the variance of the ROI. This "calibration curve" was then applied to contour the whole data set. The accuracy (mean discrepancy between DPM model-based contours and reference contours) of volume estimation was below (1 ± 7)% on the whole data set (1 SD). The overlap between true and automatically segmented contours, measured by the Dice similarity coefficient, was 0.93 with a SD of 0.03.The proposed DPM model was able to accurately reproduce known volumes of FDG concentration, with high overlap between segmented and true volumes. For all the analyzed inserts of the IEC phantom, the algorithm proved to be robust to variations in radius and in TBR. The main advantage of this algorithm was that no setting of DPM parameters was required in advance, since the proper setting of the only parameter that could significantly influence the segmentation results was automatically related to the uptake variance of the chosen ROI. Furthermore, the algorithm did not need any preliminary choice of the optimum number of classes to describe the ROIs within PET images and no assumption about the shape of the lesion and the uptake heterogeneity of the tracer was required.

Background We report the results of a single-institution, phase II trial of accelerated partial breast irradiation (APBI) using a single dose of intraoperative electron radiation therapy (IOERT) in patients with low-risk early stage breast cancer. Methods and Materials A cohort of 226 patients with low-risk, early stage breast cancer were treated with local excision and axillary management (sentinel node biopsy with or without axillary node dissection). After the surgeon temporarily reapproximated the excision cavity, a dose of 21 Gy using IOERT was delivered to the tumor bed, with a margin of 2 cm laterally. Results With a mean follow-up of 46 months (range, 28-63 months), only 1 case of local recurrence was reported. The observed toxicity was considered acceptable. Conclusions APBI using a single dose of IOERT can be delivered safely in women with early, low-risk breast cancer in carefully selected patients. A longer follow-up is needed to ascertain its efficacy compared to that of the current standard treatment of whole-breast irradiation.

The task group (TG) for quality assurance for robotic radiosurgery was formed by the American Association of Physicists in Medicine's Science Council under the direction of the Radiation Therapy Committee and the Quality Assurance (QA) Subcommittee. The task group (TG-135) had three main charges: (1) To make recommendations on a code of practice for Robotic Radiosurgery QA; (2) To make recommendations on quality assurance and dosimetric verification techniques, especially in regard to real-time respiratory motion tracking software; (3) To make recommendations on issues which require further research and development. This report provides a general functional overview of the only clinically implemented robotic radiosurgery device, the CyberKnife. This report includes sections on device components and their individual component QA recommendations, followed by a section on the QA requirements for integrated systems. Examples of checklists for daily, monthly, annual, and upgrade QA are given as guidance for medical physicists. Areas in which QA procedures are still under development are discussed.

Purpose: In highly-conformal radiotherapy, due to the complexity of both beam configurations and dose distributions, traditional in vivo dosimetry is unpractical or even impossible. The ideal dosimeter would be implanted inside the planning treatment volume so that it can directly measure the total delivered dose during each fraction with no additional uncertainty due to calculation models. The aim of this work is to verify if implantable metal oxide semiconductors field effect transistors (MOSFETs) can achieve a sufficient degree of dosimetric accuracy when used inside extracranial targets undergoing radiotherapy treatments using the Cyberknife system. Methods: Based on the preliminary findings of this study, new prototypes for high dose fractionations were developed to reduce the time dependence for long treatment delivery times. These dosimeters were recently cleared and are marketed as DVS-HFT. Multiple measurements were performed using both Virtual Water and water phantoms to characterize implantable MOSFETs under the Cyberknife beams, and included the reference-dosimetry consistency, the dependence of the response on the collimator size, on the daily delivered dose, and the time irradiation modality. Finally a Cyberknife prostate treatment simulation using a body phantom was conducted, and both MOSFET and ionization readings were compared to Monte Carlo calculations. The feasibility analysismore » was conducted based on the ratios of the absorbed dose divided by the dose reading, named as ''further calibration factor'' (FCF). Results: The average FCFs resulted to be 0.98 for the collimator dependence test, and about 1.00 for the reference-dosimetry test, the dose-dependence test, and the time-dependence test. The average FCF of the prostate treatment simulation test was 0.99. Conclusions: The obtained results are well within DVS specifications, that is, the factory calibration is still valid for such kind of treatments using the Cyberknife system, with no need of further calibration factors to be applied. The final accuracy of implantable MOSFETs when used for such kind of treatments was estimated to be within {+-}4%. Additional investigations using dose/fraction higher than 12 Gy, different beam configurations, and tracking systems could extend the present findings to other kind of treatments. MOSFET technology was proven to have high versatility in fast adaptation of existing detectors to new applications. It is plausible to expect a general feasibility of implantable MOSFET technology for in vivo dosimetry of the extracranial-targets treatments using the Cyberknife, provided each particular application will be validated by suitable both physical and clinical studies.« less

Object The authors describe a method that utilizes an image-guided robotic radiosurgical apparatus (the CyberKnife) for treatment of cerebral arteriovenous malformations (AVMs). This procedure required the development of an original technique that allows a high degree of automation. Methods Angiographic images were imported into the treatment planning software by coregistering CT and 3D rotational angiography. The nidus contour was delineated using the contouring tools of the treatment planning system. Functional MR imaging was employed for contouring critical cortical regions, such as the motor cortex and language areas. Once the radiation dose to be delivered to the target volume and dose constraints to critical structures were prescribed, the inverse treatment planning function determined the optimal treatment plan. Results A series of 279 patients with cerebral AVMs underwent CyberKnife radiosurgery. One transitory adverse effect of the radiation procedure was observed. Eight bleeding occurrences were noted before complete AVM obliteration. Of the 102 patients with follow-up > 36 months, 80 underwent angiographic evaluation. In this group, 65 patients (81.2%) showed complete angiographic obliteration of their AVM. In 8 more patients, complete angiographic obliteration was demonstrated by MR angiography only. Conclusions This is the first report describing a technique developed for CyberKnife radiosurgery of cerebral AVMs. The use of different imaging modalities for automatic delineation of the target and critical structures combined with the employment of the inverse treatment planning capability is the crucial point of the procedure. The procedure proved to be safe and efficient.

The scope of this work was to apply a method for estimation of total scatter factors of the smallest beams of the Cyberknife radiosurgery system to newly available solid‐state detectors: the PTW 60008 diode, the SunNuclear EdgeDetector™ diode, and the Thomson and Nielsen TN502RDM micromosfet. The method is based on a consistency check between Monte Carlo simulation of the detectors and experimental results, and was described in a recent publication. Corrected total scatter factors were in excellent agreement with the findings of the former study. The results showed that the diodes tend to overestimate the total scatter factor of small beams, probably due to excessive scatter from the material surrounding the active layer. The correction factor for diodes and for the micromosfet, however, was found to be independent of the electron beam width. This is a desirable characteristic because it allows standard correction factors to be used for treatment units of the same type, without the need of case‐by‐case Monte Carlo simulation. PACS numbers: 87.55.kh; 87.55.ne; 87.56.Fc.

Purpose An analysis is performed of the setup errors measured by a kV cone beam computed tomography (CBCT) for intracranial stereotactic radiotherapy (SRT) patients immobilized by a thermoplastic mask and a bite-block and positioned using stereotactic coordinates. We evaluated the overall positioning precision and accuracy of the immobilizing and localizing systems. The potential of image-guided radiotherapy to replace stereotactic methods is discussed. Methods and Materials Fifty-seven patients received brain SRT. After a frame-guided setup, before each fraction (131 fractions), a CBCT was acquired and the detected displacements corrected online. Translational and rotational errors were analyzed calculating overall mean and standard deviation. A separate analysis was performed for bite-block (in conjunction with mask) and for simple thermoplastic mask. Interobserver variability for CBCT three-dimensional registration was assessed. The residual error after correction and intrafractional motion were calculated. Results The mean module of the three-dimensional displacement vector was 3.0 ± 1.4 mm. Setup errors for bite block and mask were smaller (2.9 ± 1.3 mm) than those for thermoplastic mask alone (3.2 ± 1.5 mm), but statistical significance was not reached ( p = 0.15). Interobserver variability was negligible. The maximum margin calculated for residual errors and intra fraction motion was small but not negligible (1.57 mm). Conclusions Considering the detected setup errors, daily image guidance is essential for the efficacy of SRT treatments when mask immobilization is used, and even when a bite-block is used in conjunction. The frame setup is still used as a starting point for the opportunity of rotational corrections. Residual margins after on-line corrections must be evaluated.

Purpose Different biologically equivalent dose (BED) values associated with stereotactic radiotherapy (SRT) of patients with primary and metastatic pulmonary nodules were studied. The BED values were calculated for tumoral tissue and low α/β ratio, assuming that better local response could be obtained by using stereotactic high-BED treatment. Methods and Materials Fifty-eight patients with T1–T3 N0 non–small-cell lung cancer and 46 patients with metastatic lung nodules were treated with SRT. The BED was calculated for α/β ratios of 3 and 10. Overall survival (OS) was assessed according to Kaplan-Meier and appraised as a function of three BED levels: low (30–50 Gy), medium (50–70 Gy), and high (70–98 Gy; α/β = 10). Results The OS rates for all 104 patients at 12, 24, and 36 months were 73%, 48.3%, and 35.8%, respectively. Local response greater than 50% for low, medium, and high BED values was observed in 54%, 47%, and 73%, respectively. In the high-BED treated group, OS rates at 12, 24, and 36 months (80.9%, 70%, and 53.6%, respectively) were significantly improved compared with low- (69%, 46.1%, and 30.7%, respectively) and medium-BED (67%, 28%, and 21%, respectively) treated patients. Results are also discussed in terms of BED calculated on α/β 3 Gy characteristic of the microcapillary bed. No acute toxicity higher than Grade 1 was observed. Conclusions Radioablation of pulmonary neoplastic nodules may be achieved with SRT delivered by using a high-dose fraction with high BED value.

The scope of this study was to estimate total scatter factors ( s c , p ) of the three smallest collimators of the Cyberknife radiosurgery system (5–10 mm in diameter), combining experimental measurements and Monte Carlo simulation. Two microchambers, a diode, and a diamonddetector were used to collect experimental data. The treatment head and the detectors were simulated by means of a Monte Carlo code in order to calculate correction factors for the detectors and to estimate total scatter factors by means of a consistency check between measurement and simulation. Results for the three collimators were: s c , p ( 5 mm ) = 0.677 ± 0.004 , s c , p ( 7.5 mm ) = 0.820 ± 0.008 , s c , p ( 10 mm ) = 0.871 ± 0.008 , all relative to the 60 mm collimator at 80 cm source-to-detector distance. The method also allows the full width at half maximum of the electron beam to be estimated; estimations made with different collimators and different detectors were in excellent agreement and gave a value of 2.1 mm. Correction factors to be applied to the detectors for the measurement of s c , p were consistent with a prevalence of volume effect for the microchambers and the diamond and a prevalence of scattering from high- Z material for the diode detector. The proposed method is more sensitive to small variations of the electron beam diameter with respect to the conventional method used to commission Monte Carlo codes, i.e., by comparison with measured percentage depth doses (PDD) and beam profiles. This is especially important for small fields (less than 10 mm diameter), for which measurements of PDD and profiles are strongly affected by the type of detector used. Moreover, this method should allow s c , p of Cyberknife systems different from the unit under investigation to be estimated without the need for further Monte Carlo calculation, provided that one of the microchambers or the diode detector of the type used in this study are employed. The results for the diamond are applicable only to the specific detector that was investigated due to excessive variability in manufacturing.