Development of a Secure Web-Based Medical Imaging Analysis Platform: The AWESOMME Project.

Precision medicine research benefits from machine learning in the creation of robust models adapted to the processing of patient data. This applies both to pathology identification in images, i.e., annotation or segmentation, and to computer-aided diagnostic for classification or prediction. It comes with the strong need to exploit and visualize large volumes of images and associated medical data. The work carried out in this paper follows on from a main case study piloted in a cancer center. It proposes an analysis pipeline for patients with osteosarcoma through segmentation, feature extraction and application of a deep learning model to predict response to treatment. The main aim of the AWESOMME project is to leverage this work and implement the pipeline on an easy-to-access, secure web platform. The proposed WEB application is based on a three-component architecture: a data server, a heavy computation and authentication server and a medical imaging web-framework with a user interface. These existing components have been enhanced to meet the needs of security and traceability for the continuous production of expert data. It innovates by covering all steps of medical imaging processing (visualization and segmentation, feature extraction and aided diagnostic) and enables the test and use of machine learning models. The infrastructure is operational, deployed in internal production and is currently being installed in the hospital environment. The extension of the case study and user feedback enabled us to fine-tune functionalities and proved that AWESOMME is a modular solution capable to analyze medical data and share research algorithms with in-house clinicians.

An Integrated Cancer Prevention Strategy: the Viewpoint of the Leon Berard Comprehensive Cancer Center Lyon, France.

This article describes some of the key prevention services in the Leon Berard Comprehensive Cancer Center (CLB) Lyon, France, which are based on clinical prevention services, outreach activities, and collaboration with professional and territorial health communities. In addition, research is embedded at all stages of the prevention continuum, from understanding cancer causes through to the implementation of prevention interventions during and after cancer. Health promotion activities in the community and dedicated outpatient primary cancer prevention services for individuals at increased risk have been implemented. The CLB's experience illustrates how prevention can be integrated into the comprehensive mission of cancer centers, and how in turn, the cancer centers may contribute to bridging the current fragmentation between cancer care and the different components of primary, secondary, and tertiary prevention. With increasing cancer incidence, the shift toward integrated prevention-centered cancer care is not only key for improving population health, but this may also provide a response to the shortage of hospital staff and overcrowding in cancer services, as well as offer opportunities to reduce carbon emissions from cancer care.

Optimal control in a magnetization-prepared rapid acquisition gradient-echo sequence.

This article proposes a numerical framework to determine the optimal magnetization preparation in a three-dimensional magnetization-prepared rapid gradient-echo (MP-RAGE) sequence to obtain the best achievable contrast between target tissues based on differences in their relaxation times. The benefit lies in the adaptation of the algorithm of optimal control, GRAdient Ascent Pulse Engineering (GRAPE), to the optimization of magnetization preparation in a cyclic sequence without full recovery between each cycle. This numerical approach optimizes magnetization preparation of an arbitrary number of radio frequency pulses to enhance contrast, taking into account the establishment of a steady state in the longitudinal component of the magnetization. The optimal control preparation offers an optimized mixed T 1 / T 2 contrast in this traditional T 1 -weighted sequence. To show the versatility of the proposed method, numerical and in vitro results are described. Examples of contrasts acquired on brain regions of a healthy volunteer are presented for potential applications at 3 T.

Characterization of Breast Tumors from MR Images Using Radiomics and Machine Learning Approaches.

Determining histological subtypes, such as invasive ductal and invasive lobular carcinomas (IDCs and ILCs) and immunohistochemical markers, such as estrogen response (ER), progesterone response (PR), and the HER2 protein status is important in planning breast cancer treatment. MRI-based radiomic analysis is emerging as a non-invasive substitute for biopsy to determine these signatures. We explore the effectiveness of radiomics-based and CNN (convolutional neural network)-based classification models to this end. T1-weighted dynamic contrast-enhanced, contrast-subtracted T1, and T2-weighted MR images of 429 breast cancer tumors from 323 patients are used. Various combinations of input data and classification schemes are applied for ER+ vs. ER-, PR+ vs. PR-, HER2+ vs. HER2-, and IDC vs. ILC classification tasks. The best results were obtained for the ER+ vs. ER- and IDC vs. ILC classification tasks, with their respective AUCs reaching 0.78 and 0.73 on test data. The results with multi-contrast input data were generally better than the mono-contrast alone. The radiomics and CNN-based approaches generally exhibited comparable results. ER and IDC/ILC classification results were promising. PR and HER2 classifications need further investigation through a larger dataset. Better results by using multi-contrast data might indicate that multi-parametric quantitative MRI could be used to achieve more reliable classifiers.

Radiomics combined with transcriptomics to predict response to immunotherapy from patients treated with PD-1/PD-L1 inhibitors for advanced NSCLC.

Introduction: In this study, we aim to build radiomics and multiomics models based on transcriptomics and radiomics to predict the response from patients treated with the PD-L1 inhibitor. Materials and methods: One hundred and ninety-five patients treated with PD-1/PD-L1 inhibitors were included. For all patients, 342 radiomic features were extracted from pretreatment computed tomography scans. The training set was built with 110 patients treated at the Léon Bérard Cancer Center. An independent validation cohort was built with the 85 patients treated in Dijon. The two sets were dichotomized into two classes, patients with disease control and those considered non-responders, in order to predict the disease control at 3 months. Various models were trained with different feature selection methods, and different classifiers were evaluated to build the models. In a second exploratory step, we used transcriptomics to enrich the database and develop a multiomic signature of response to immunotherapy in a 54-patient subgroup. Finally, we considered the HOT/COLD status. We first trained a radiomic model to predict the HOT/COLD status and then prototyped a hybrid model integrating radiomics and the HOT/COLD status to predict the response to immunotherapy. Results: Radiomic signature for 3 months' progression-free survival (PFS) classification: The most predictive model had an area under the receiver operating characteristic curve (AUROC) of 0.94 on the training set and 0.65 on the external validation set. This model was obtained with the t-test selection method and with a support vector machine (SVM) classifier. Multiomic signature for PFS classification: The most predictive model had an AUROC of 0.95 on the training set and 0.99 on the validation set. Radiomic model to predict the HOT/COLD status: the most predictive model had an AUROC of 0.93 on the training set and 0.86 on the validation set. HOT/COLD radiomic hybrid model for PFS classification: the most predictive model had an AUROC of 0.93 on the training set and 0.90 on the validation set. Conclusion: In conclusion, radiomics could be used to predict the response to immunotherapy in non-small-cell lung cancer patients. The use of transcriptomics or the HOT/COLD status, together with radiomics, may improve the working of the prediction models.

Prognostic Factors for Local Recurrence after Cryoablation of Desmoid Tumors.

PURPOSE: To determine the risk factors for local of adult patients treated for desmoid tumors by cryoablation. MATERIALS AND METHODS: Eighty-four patients treated for nonabdominopelvic desmoid tumors by cryoablation from July 2012 to July 2020 were included in a retrospective study. The population was composed of 64 women (76.19%) and 20 men (23.81%), aged from 16 to 75 years (median, 35 years ± 14.25). Each patient underwent preprocedural gadolinium-enhanced magnetic resonance imaging and was followed up to 36 months with the same technique. Clinical features, such as tumor size and previous treatment, epidemiological features, and the technical parameters of cryoablation, were studied. RESULTS: Local relapse was found in 19 (22.62%) of 84 patients. The 12-, 24-, and 36-month progression-free survival rates were 89% (95% confidence interval [CI], 79-94), 74% (95% CI, 60-83), and 68% (95% CI, 53-79), respectively. In univariate analysis, significant prognostic factors associated with local recurrence were non-abdominal wall location (P = .042), debulking strategy (P = .0105), risk of visceral injury (P = .034) or peripheral nerve injury during cryoablation (P = .033), previous radiation therapy (P = .043), and treatment before 2016 (P = .008). In multivariate analysis, abdominal wall tumors displayed the best outcome, whereas the neck and trunk showed a high rate of recurrence (hazard ratio, 7.307 [95% CI, 1.396-38.261]). CONCLUSIONS: The local recurrence of desmoid tumors after cryoablation depends on a number of prognostic factors, in particular, a non-abdominal wall location of the tumor and previous local treatment such as surgery or radiation therapy.

Prediction of lipomatous soft tissue malignancy on MRI: comparison between machine learning applied to radiomics and deep learning.

OBJECTIVES: Malignancy of lipomatous soft-tissue tumours diagnosis is suspected on magnetic resonance imaging (MRI) and requires a biopsy. The aim of this study is to compare the performances of MRI radiomic machine learning (ML) analysis with deep learning (DL) to predict malignancy in patients with lipomas oratypical lipomatous tumours. METHODS: Cohort include 145 patients affected by lipomatous soft tissue tumours with histology and fat-suppressed gadolinium contrast-enhanced T1-weighted MRI pulse sequence. Images were collected between 2010 and 2019 over 78 centres with non-uniform protocols (three different magnetic field strengths (1.0, 1.5 and 3.0 T) on 16 MR systems commercialised by four vendors (General Electric, Siemens, Philips, Toshiba)). Two approaches have been compared: (i) ML from radiomic features with and without batch correction; and (ii) DL from images. Performances were assessed using 10 cross-validation folds from a test set and next in external validation data. RESULTS: The best DL model was obtained using ResNet50 (resulting into an area under the curve (AUC) of 0.87 ± 0.11 (95% CI 0.65-1). For ML/radiomics, performances reached AUCs equal to 0.83 ± 0.12 (95% CI 0.59-1) and 0.99 ± 0.02 (95% CI 0.95-1) on test cohort using gradient boosting without and with batch effect correction, respectively. On the external cohort, the AUC of the gradient boosting model was equal to 0.80 and for an optimised decision threshold sensitivity and specificity were equal to 100% and 32% respectively. CONCLUSIONS: In this context of limited observations, batch-effect corrected ML/radiomics approaches outperformed DL-based models.

Prediction of Histologic Neoadjuvant Chemotherapy Response in Osteosarcoma Using Pretherapeutic MRI Radiomics.

Histologic response to chemotherapy for osteosarcoma is one of the most important prognostic factors for survival, but assessment occurs after surgery. Although tumor imaging is used for surgical planning and follow-up, it lacks predictive value. Therefore, a radiomics model was developed to predict the response to neoadjuvant chemotherapy based on pretreatment T1-weighted contrast-enhanced MRI. A total of 176 patients (median age, 20 years [range, 5-71 years]; 107 male patients) with osteosarcoma treated with neoadjuvant chemotherapy and surgery between January 2007 and December 2018 in three different centers in France (Centre Léon Bérard in Lyon, Centre Hospitalier Universitaire de Nantes in Nantes, and Hôpital Cochin in Paris) were retrospectively analyzed. Various models were trained from different configurations of the data sets. Two different methods of feature selection were tested with and without ComBat harmonization (ReliefF and t test) to select the most relevant features, and two different classifiers were used to build the models (an artificial neural network and a support vector machine). Sixteen radiomics models were built using the different combinations of feature selection and classifier applied on the various data sets. The most predictive model had an area under the receiver operating characteristic curve of 0.95, a sensitivity of 91%, and a specificity 92% in the training set; respective values in the validation set were 0.97, 91%, and 92%. In conclusion, MRI-based radiomics may be useful to stratify patients receiving neoadjuvant chemotherapy for osteosarcomas. Keywords: MRI, Skeletal-Axial, Oncology, Radiomics, Osteosarcoma, Pediatrics Supplemental material is available for this article. © RSNA, 2022.

Influence of cellular models and individual factor in the biological response to head CT scan exams.

BACKGROUND: While computed tomography (CT) exams are the major cause of medical exposure to ionising radiation, the radiation-induced risks must be documented. We investigated the impact of the cellular models and individual factor on the deoxyribonucleic acid double-strand breaks (DSB) recognition and repair in human skin fibroblasts and brain astrocytes exposed to current head CT scan conditions. METHOD: Nine human primary fibroblasts and four human astrocyte cell lines with different levels of radiosensitivity/susceptibility were exposed to a standard head CT scan exam using adapted phantoms. Cells were exposed to a single-helical (37.4 mGy) and double-helical (37.4 mGy + 5 min + 37.4 mGy) examination. DSB signalling and repair was assessed through anti-γH2AX and anti-pATM immunofluorescence. RESULTS: Head CT scan induced a significant number of γH2AX and pATM foci. The kinetics of both biomarkers were found strongly dependent on the individual factor. Particularly, in cells from radiosensitive/susceptible patients, DSB may be significantly less recognised and/or repaired, whatever the CT scan exposure conditions. Similar conclusions were reached with astrocytes. CONCLUSIONS: Our results highlight the importance of both individual and tissue factors in the recognition and repair of DSB after current head CT scan exams. Further investigations are needed to better define the radiosensitivity/susceptibility of individual humans.

Influence of cellular models and individual factor in the biological response to chest CT scan exams.

BACKGROUND: While computed tomography (CT) exams are the major cause of medical exposure to ionising radiation, there is increasing evidence that the potential radiation-induced risks must be documented. We investigated the impact of cellular models and individual factor on the deoxyribonucleic acid double-strand breaks (DSB) recognition and repair in human fibroblasts and mammary epithelial cells exposed to current chest CT scan conditions. METHOD: Twelve human primary fibroblasts and four primary human mammary epithelial cell lines with different levels of radiosensitivity/susceptibility were exposed to a standard chest CT scan exam using adapted phantoms. Cells were exposed to a single helical irradiation (14.4 mGy) or to a topogram followed, after 1 min, by one single helical examination (1.1 mGy + 14.4 mGy). DSB signalling and repair was assessed through anti-γH2AX and anti-pATM immunofluorescence. RESULTS: Chest CT scan induced a significant number of γH2AX and pATM foci. The kinetics of both biomarkers were found strongly dependent on the individual factor. The topogram may also influence the biological response of radiosensitive/susceptible fibroblasts to irradiation. Altogether, our findings show that a chest CT scan exam may result in 2 to 3 times more unrepaired DSB in cells from radiosensitive/susceptible patients. CONCLUSIONS: Both individual and tissue factors in the recognition and repair of DSB after current CT scan exams are important. Further investigations are needed to better define the radiosensitivity/susceptibility of individual humans.

Multicontrast MRI-based radiomics for the prediction of pathological complete response to neoadjuvant chemotherapy in patients with early triple negative breast cancer.

INTRODUCTION: To assess pre-therapeutic MRI-based radiomic analysis to predict the pathological complete response to neoadjuvant chemotherapy (NAC) in women with early triple negative breast cancer (TN). MATERIALS AND METHODS: This monocentric retrospective study included 75 TN female patients with MRI (T1-weighted, T2-weighted, diffusion-weighted and dynamic contrast enhancement images) performed before NAC. For each patient, the tumor(s) and the parenchyma were independently segmented and analyzed with radiomic analysis to extract shape, size, and texture features. Several sets of features were realized based on the 4 different sequence images. Performances of 4 classifiers (random forest, multilayer perceptron, support vector machine (SVM) with linear or quadratic kernel) were compared based on pathological complete response (defined on the excised tissues), on 100 draws with 75% as training set and 25% as test. RESULTS: The combination of features extracted from different MR images improved the classifier performance (more precisely, the features from T1W, T2W and DWI). The SVM with quadratic kernel showed the best performance with a mean AUC of 0.83, a sensitivity of 0.85 and a specificity of 0.75 in the test set. CONCLUSION: MRI-based radiomics may be relevant to predict NAC response in TN cancer. Our results promote the use of multi-contrast MRI sources for radiomics, providing enrich source of information to enhance model generalization.

Sarcopenia and serum biomarkers of oxidative stress after a 6-month physical activity intervention in women with metastatic breast cancer: results from the ABLE feasibility trial.

PURPOSE: Sarcopenia has been identified as an important prognostic factor for patients with cancer. This study aimed at exploring the potential associations between a 6-month physical activity intervention and muscle characteristics, sarcopenia, oxidative stress and toxicities in patients with metastatic breast cancer. METHODS: Women newly diagnosed with metastatic breast cancer (N = 49) participated in an unsupervised, personalized, 6-month physical activity intervention with activity tracker. Computerized tomography images at the third lumbar vertebra were analysed at baseline, three months and six months to assess sarcopenia (muscle mass index < 40 cm2/m2) and muscle quality (poor if muscle attenuation < 37.8 Hounsfield Units). Oxidative markers included plasma antioxidant enzymes (catalase, glutathione peroxidase and superoxide dismutase activities), prooxidant enzymes (NADPH oxidase and myeloperoxidase activities) and oxidative stress damage markers (advanced oxidation protein products, malondialdehyde (MDA) and DNA oxidation. RESULTS: At baseline 53% (mean age 55 years (SD 10.41)) were sarcopenic and 75% had poor muscle quality. Muscle cross sectional area, skeletal muscle radiodensity, lean body mass remained constant over the six months (p = 0.75, p = 0.07 and p = 0.75 respectively), but differed significantly between sarcopenic and non-sarcopenic patients at baseline and 6-months. Sarcopenic patients at baseline were more likely to have an increase of MDA (p = 0.02) at 6 months. Being sarcopenic during at least one moment during the 6-month study was associated with a higher risk of developing severe toxicities (grade > 2) (p = 0.02). CONCLUSIONS: This study suggests potential benefits of physical activity for maintenance of muscle mass. Sarcopenia can alter many parameters and disturb the pro and antioxidant balance.

Cryoablation for Palliation of Painful Bone Metastases: The MOTION Multicenter Study.

Purpose: To assess the clinical effectiveness of cryoablation for palliation of painful bone metastases. Materials and Methods: MOTION (Multicenter Study of Cryoablation for Palliation of Painful Bone Metastases) (ClinicalTrials.gov NCT02511678) was a multicenter, prospective, single-arm study of adults with metastatic bone disease who were not candidates for or had not benefited from standard therapy, that took place from February 2016 to March 2018. At baseline, participants rated their pain using the Brief Pain Inventory-Short Form (reference range from 0 to 10 points); those with moderate to severe pain, who had at least one metastatic candidate tumor for ablation, were included. The primary effectiveness endpoint was change in pain score from baseline to week 8. Participants were followed for 24 weeks after treatment. Statistical analyses included descriptive statistics and logistic regression to evaluate changes in pain score over the postprocedure follow-up period. Results: A total of 66 participants (mean age, 60.8 years ± 14.3 [standard deviation]; 35 [53.0%] men) were enrolled and received cryoablation; 65 completed follow-up. Mean change in pain score from baseline to week 8 was -2.61 points (95% CI: -3.45, -1.78). Mean pain scores improved by 2 points at week 1 and reached clinically meaningful levels (more than a 2-point decrease) after week 8; scores continued to improve throughout follow-up. Quality of life improved, opioid doses were stabilized, and functional status was maintained over 6 months. Serious adverse events occurred in three participants. Conclusion: Cryoablation of metastatic bone tumors provided rapid and durable pain palliation, improved quality of life, and offered an alternative to opioids for pain control.Keywords: Ablation Techniques, Metastases, Pain Management, Radiation Therapy/OncologySupplemental material is available for this article.© RSNA, 2021.

Portal vein embolization with ethylene-vinyl alcohol copolymer for contralateral lobe hypertrophy before liver resection: safety, feasibility and initial experience.

BACKGROUND: To report our preliminary experience with preoperative portal vein embolization (PVE) using liquid ethylene vinyl alcohol (EVOH) copolymer. METHODS: Retrospectively review of patients with primary or secondary liver malignancies scheduled for extensive hepatectomy after the induction of future liver remnant (FLR) hypertrophy by right or left PVE with EVOH as the only embolic agent between 2014 and 2018 at two academic centers. Cross-sectional imaging liver volumetry data obtained before and 3-6 weeks after PVE were used to assess the FLR volume (FLRV) increase, degree of FLR hypertrophy and the FLR kinetic growth rate (KGR). RESULTS: Twenty-six patients (17 males; mean age, 58.7±11 years; range, 32-79 years) were included. The technical and clinical success rate was 100%. PVE produced adequate FLR hypertrophy in all patients. Embolization occurred in all targeted portal branches and in no non-target vessels. The %FLRV increased by 52.9%±32.5% and the degree of FLR hypertrophy was 16.7%±6.8%. The KGR was 4.4%±2.0% per week. Four patients experience minor complications after PVE which resolved with symptomatic treatment. The resection rate was 84.5%. One patient died during surgery for reasons unrelated to PVE. CONCLUSIONS: Preoperative PVE with EVOH copolymer is feasible, safe, and effective in inducing FLR hypertrophy.

MRI-based radiomics to predict lipomatous soft tissue tumors malignancy: a pilot study.

OBJECTIVES: To develop and validate a MRI-based radiomic method to predict malignancies in lipomatous soft tissue tumors. METHODS: This retrospective study searched in the database of our pathology department, data from patients with lipomatous soft tissue tumors, with histology and gadolinium-contrast enhanced T1w MR images, obtained from 56 centers with non-uniform protocols. For each tumor, 87 radiomic features were extracted by two independent observers to evaluate the inter-observer reproducibility. A reduction of learning base dimension was performed from reproducibility and relevancy criteria. A model was subsequently prototyped using a linear support vector machine to predict malignant lesions. RESULTS: Eighty-one subjects with lipomatous soft tissue tumors including 40 lipomas and 41 atypical lipomatous tumors or well-differentiated liposarcomas with fat-suppressed T1w contrast enhanced MR images available were retrospectively enrolled. Based on a Pearson's correlation coefficient threshold at 0.8, 55 out of 87 (63.2%) radiomic features were considered reproducible. Further introduction of relevancy finally selected 35 radiomic features to be integrated in the model. To predict malignant tumors, model diagnostic performances were as follow: AUROC = 0.96; sensitivity = 100%; specificity = 90%; positive predictive value = 90.9%; negative predictive value = 100% and overall accuracy = 95.0%. CONCLUSION: This work demonstrates that radiomics allows to predict malignancy in soft tissue lipomatous tumors with routinely used MR acquisition in clinical oncology. These encouraging results need to be further confirmed in an external validation population.

Feasibility and characterization of a safe susceptibility-matched endorectal coil for MR spectroscopy.

When using endorectal coils, local radiofrequency (RF) heating may occur in the surrounding tissue. Furthermore, most endorectal coils create a susceptibility artifact detrimental to both anatomical magnetic resonance imaging (MRI) and spectroscopy (MRS) acquisitions. We aimed at assessing the safety and MRS performance of a susceptibility-matched endorectal coil for further rectal wall analysis. Experiments were performed on a General Electric MR750 3 T scanner. A variable number of miniaturized passive RF traps were incorporated in the reception cable. The assessment of RF heating and coil sensitivity was conducted on a 1.5% agar-agar phantom doped with NaCl. Several susceptibility-matched materials such as Ultem, perfluorocarbon and barium sulfate were then compared with an external coil. Finally, Ultem was used as a solid support for an endorectal coil and compared with a reference coil. Phantom experiments exhibited a complete suppression of both the RF heating phenomenon and the coil sensitivity artifact. Ultem was the material that produced the smallest image distortion. The full width at half maximum of MR spectra acquired using the susceptibility-matched endorectal coil showed at least 30% narrowing compared with a reference endorectal coil. A susceptibility-matched endorectal coil with RF traps incorporated was validated on phantoms. This coil appears to be a promising device for future in vivo experiments.

Design and methods of a national, multicenter, randomized and controlled trial to assess the efficacy of a physical activity program to improve health-related quality of life and reduce fatigue in women with metastatic breast cancer: ABLE02 trial.

BACKGROUND: Patients with a metastatic breast cancer suffer from a deteriorated health-related quality of life and numerous symptoms such as pain, severe fatigue and a decrease of their physical fitness. As the feasibility of a physical activity program has been demonstrated in this population, ABLE02 aims to assess the efficacy of a 6 month-physical activity program using connected devices to improve health-related quality of life and to reduce fatigue in women with metastatic breast cancer. METHODS: ABLE02 is a prospective, national, multicenter, randomized, controlled and open-label study. A total of 244 patients with a metastatic breast cancer, with at least one positive hormone receptor and a first-line chemotherapy planned, will be randomly assigned (1:1 ratio) to: (i) the intervention arm to receive physical activity recommendations, an activity tracker to wear 24 h a day during the whole intervention (6 months) with at least three weekly walking sessions and quizzes each week on physical activity and nutrition (ii) the control arm to receive physical activity recommendations only. Health-related quality of life will be assessed every 6 weeks and main assessments will be conducted at baseline, M3, M6, M12 and M18 to evaluate the clinical, physical, biological and psychological parameters and survival of participants. All questionnaires will be completed on a dedicated application. DISCUSSION: An activity program based on a smartphone application linked to an activity tracker may help to improve quality of life and reduce fatigue of patients with a metastatic breast cancer. The growth of e-health offers the opportunity to get real-time data as well as improving patient empowerment in order to change long-term behaviors. TRIAL REGISTRATION: NCT number: NCT04354233 .

Cryoneurolysis in Patients with Dorsal Neuropathic Pain Secondary to Tumor Invasion.

PURPOSE: To evaluate the safety and efficacy of cryoneurolysis (CNL) in patients with refractory thoracic neuropathic pain related to tumor invasion. MATERIALS AND METHODS: Between January 2013 and May 2017, this single-center and retrospective study reviewed 27 computed tomography-guided CNLs performed on 26 patients for refractory thoracic neuropathic pain related to tumor invasion. Patients with cognitive impairment were excluded. Pain levels were recorded on a visual analog scale (VAS) before the procedure, on days 1, 7, 14, 28 and at each subsequent follow-up appointment. CNL was clinically successful if the postprocedural VAS decreased by 3 points or more. To determine the duration of clinical success, the end of pain relief was defined as either an increased VAS of 2 or more points, the introduction of a new analgesic treatment, a death with controlled pain, or for lost to follow-up patients, the latest follow-up appointment date with controlled pain. RESULTS: Technical success rate was 96.7% and clinical success rate was 100%. Mean preprocedural pain score was 6.4 ± 1.7 and decreased to 2.4 ± 2.4 at day 1; 1.8 ± 1.7 at day 7 (P < .001); 3.3 ± 2.5 at day 14; 3.4 ± 2.6 at day 28 (P < .05). The median duration of pain relief was 45 days (range 14-70). Two minor complications occurred. CONCLUSIONS: Cryoneurolysis is a safe procedure that significantly decreased pain scores in patients with thoracic neuropathic pain related to tumor invasion, with a median duration of clinical success of 45 days.

Percutaneous Cryoablation of Symptomatic Intramuscular Venous Malformation.

PURPOSE: To evaluate the efficacy and safety of cryoablation for venous malformations. MATERIALS AND METHODS: A total of 12 patients with symptomatic intramuscular venous malformations who underwent percutaneous cryoablation between February 2015 and December 2018 were retrospectively studied. The mean age was 42 y (range, 19-58 y). Pain was reported by 11 patients (92%) and swelling by 1 (8%). Pain was assessed with a visual analog scale (VAS) before and after cryoablation. Lesion size was followed with magnetic resonance (MR) imaging at baseline and at 3-mo follow-up. Median initial VAS score was 7 (range, 0-8), and median initial lesion size was 32.5 mm (range, 11-150 mm). RESULTS: The median VAS score at 3 mo was 0 (range, 0-4), and the median lesion size at 3 mo was 0 mm (range, 0-142 mm). Eleven of 12 patients reported an improvement in their pain. MR imaging control showed a treatment scar with no residual lesion in 5 patients and decreased lesion size in 4. No major complications were reported. One minor hematoma and 1 small myositis were noted as defined by Society of Interventional Radiology criteria. CONCLUSIONS: Percutaneous cryoablation is effective and safe for treatment of symptomatic intramuscular venous malformations, with improvement of symptoms.

Local Control and Analgesic Efficacy of Percutaneous Cryoablation for Desmoid Tumors.

OBJECTIVE: Cryoablation is being more and more often used to treat desmoid tumors. We report our experience of cryoablation as a local and analgesic treatment for inoperable or recurring desmoid tumors. METHODS: This study includes 34 patients who underwent percutaneous cryoablation of 41 desmoid tumors between July 2012 and September 2016. All patients underwent pain assessment using a visual analog scale (VAS) and preoperative imaging. All cryoablation procedures were performed using the same cryoablation system. Patients received clinical and radiological follow-up at 6 months post-procedure, with pain-rating and adverse events being recorded. A long-term follow-up was achieved until 31 December 2018. Disease-free survival at 3 years was also recorded. Radiological tumor response was determined by tumor measurements using RECIST 1.1. RESULTS: Twelve patients benefitted from curative treatment on 100% of the tumor volume, but 22 patients received debulking treatment because of the risk of neighboring structures. Two patients had a postoperative hematoma grade 2 of the CIRSE classification system for complications, and two patients had grade 4 complications involving palsy of the common fibular nerve. Disease-free survival at 3 years was 42.2%. The mean VAS pain scores were 5.7 and 2.4 at pretreatment and 6 months, respectively, showing a mean reduction of 3.3 (p < 0.001). At 6 months, all measured tumor dimensions were significantly lower than pretreatment. CONCLUSION: Cryoablation is an effective therapeutic option for the local treatment and for the analgesic management of desmoid tumors.