Magnetic resonance-guided focused ultrasound unilateral thalamotomy for medically refractory essential tremor: 3-year follow-up data.

Introduction: Magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy of the ventralis intermediate (Vim) nucleus is an "incisionless" treatment for medically refractory essential tremor (ET). We present data on 49 consecutive cases of MRgFUS Vim thalamotomy followed-up for 3 years and review the literature on studies with longer follow-up data. Methods: A retrospective chart review of patients who underwent MRgFUS thalamotomy (January 2018-December 2020) at our institution was performed. Clinical Rating Scale for Tremor (CRST) and Quality of Life in Essential Tremor (QUEST) scores were obtained pre-operatively and at each follow-up with an assessment of side effects. Patients had post-operative magnetic resonance imaging within 24 h and at 1 month to figure out lesion location, size, and extent. The results of studies with follow-up ≥3 years were summarized through a literature review. Results: The CRST total (baseline: 58.6 ± 17.1, 3-year: 40.8 ± 18.0) and subscale scores (A + B, baseline: 23.5 ± 6.3, 3-year: 12.8 ± 7.9; C, baseline: 12.7 ± 4.3, 3-year: 5.8 ± 3.9) and the QUEST score (baseline: 38.0 ± 14.8, 3-year: 18.7 ± 13.3) showed significant improvement that was stable during the 3-year follow-up. Three patients reported tremor recurrence and two were satisfactorily retreated. Side effects were reported by 44% of patients (severe: 4%, mild and transient: 40%). The improvement in tremor and quality of life in our cohort was consistent with the literature. Conclusion: We confirmed the effectiveness and safety of MRgFUS Vim thalamotomy in medically refractory ET up to 3 years.

The Italian young medical physicist scenario: Results from the young AIFM group survey.

PURPOSE: The young working group of the Italian Association of Medical and Health Physics (AIFM) designed a survey to assess the current situation of the under 35 AIFM members. METHODS: An online survey including 65 questions was designed to gather personal information, educational issues, working and research experience, and to evaluate the AIFM activities. The survey was distributed to the under 35 members between November 2022 and February 2023, through the young AIFM mailing list and social media. RESULTS: 160 answers from 230 affiliates (70%, 31 years median age) were obtained. The results highlighted that 87% of the respondents had a fixed term/permanent employment, mainly in public hospitals (58%). Regarding Medical Physicists (MPs) training, 54% of the students left their region of origin due to the training plan (40%) and the availability of scholarships (25%) in the chosen university. Most of the respondents have no Radiation Protection Expert title, while the remaining 20%, 6%, and 3% are qualified to the first, second, and third level, respectively. Several young MPs (62.2%) were involved in research activities; however, only 28% had teaching experience, mainly within their workplace (20%, safety courses), during AIFM courses (4%), or university lectures (3%). CONCLUSIONS: This survey reported the current situation of the under 35 AIFM members, highlighting the "brain drain" phenomenon from the south to the north of Italy, mainly due to the lack of post-graduate schools, scholarships, and job opportunities. The obtained results will help the future working program of the AIFM.

Treatment Planning in Intraoperative Radiation Therapy (IORT): Where Should We Go?

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.

Machine learning for multi-parametric breast MRI: radiomics-based approaches for lesion classification.

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.

Computed tomography-based radiomic to predict resectability in locally advanced pancreatic cancer treated with chemotherapy and radiotherapy.

BACKGROUND: 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. AIM: To assess the capability of radiomic features to predict surgical resection in LAPC treated with neoadjuvant chemotherapy and radiotherapy. METHODS: 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. RESULTS: 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). CONCLUSION: 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.

Long-Term Outcomes Using Electron IOERT APBI for Early Stage Breast Cancer: The Verona University Hospital Experience.

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.

The scientific publications of AIFM members in 2015-2019: A survey of the FutuRuS working group.

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.

3T DCE-MRI Radiomics Improves Predictive Models of Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

OBJECTIVES: To 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. METHODS: Women 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. RESULTS: The 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). CONCLUSIONS: Radiomic 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.

Risk Adapted Ablative Radiotherapy After Intensive Chemotherapy for Locally Advanced Pancreatic Cancer.

BACKGROUND AND OBJECTIVE: To 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 METHODS: Patients 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). RESULTS: Sixty-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. CONCLUSIONS: The 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.

CT radiomic models to distinguish COVID-19 pneumonia from other interstitial pneumonias.

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.

A phase II trial proposal of total neoadjuvant treatment with primary chemotherapy, stereotactic body radiation therapy, and intraoperative radiation therapy in borderline resectable pancreatic adenocarcinoma.

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.

MRI-guided breast biopsy based on diffusion-weighted imaging: a feasibility study.

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.

18F-FDG PET/CT Metrics Are Correlated to the Pathological Response in Esophageal Cancer Patients Treated With Induction Chemotherapy Followed by Neoadjuvant Chemo-Radiotherapy.

BACKGROUND AND OBJECTIVE: The 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 METHODS: Esophageal 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. RESULTS: Fifty-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). CONCLUSIONS: 18F-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.

Predictors of Local Control for Stereotactic Ablative Radiotherapy (SAbR) in Pulmonary Oligometastases from Gastrointestinal Malignancies.

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.

Dosimetric Feasibility Study of Dose Escalated Stereotactic Body Radiation Therapy (SBRT) in Locally Advanced Pancreatic Cancer (LAPC) Patients: It Is Time to Raise the Bar.

BACKGROUND AND OBJECTIVE: To 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 METHODS: Twenty 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. RESULTS: PTVsib 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. CONCLUSIONS: In 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.

Real-time control of respiratory motion: Beyond radiation therapy.

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.

Is there a correlation between 3T multiparametric MRI and molecular subtypes of breast cancer?

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.

Texture analysis of 3D dose distributions for predictive modelling of toxicity rates in radiotherapy.

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 < 0.04). CONCLUSION: Inclusion of 3D dosimetric texture analysis features in predictive modelling of GI and GU toxicity rates in prostate cancer radiotherapy improved prediction performance, which was statistically significant for GI.

1H-MR spectroscopy of suspicious breast mass lesions at 3T: a clinical experience.

OBJECTIVES: To test 3T proton magnetic resonance spectroscopy (1H-MRS) for breast mass lesions. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.