NIR laser pointer for in vivo photothermal therapy of murine LM3 tumor using intratumoral China ink as a photothermal agent

The photothermal effect is one of the most promising photonic procedures currently under development to successfully treat several clinical disorders, none the least some kinds of cancer. At present, this field is undergoing a renewed interest due to advances in both photothermal materials and better-suited light sources. However, scientific studies in this area are sometimes hampered by the relative unavailability of state-of-art materials or the complexity of setting up a dedicated optical facility. Here, we present a simple and affordable approach to do research in the photothermal field that relies on a commercial NIR laser pointer and a readily available everyday pigment: China ink. A proof-of-concept study is presented in which mice bearing intradermal LM3 mammary adenocarcinoma tumors were successfully treated in vivo employing China ink and the laser pointer. TUNEL and Ki-67 post-treatment tissue assessment clearly indicates the deleterious action of the photothermal treatment on the tumor. Therefore, the feasibility of this simple approach has been demonstrated, which may inspire other groups to implement simple procedures to further explore the photothermal effec

Sex- and age-related differences in the contribution of ultrasound-measured visceral and subcutaneous abdominal fat to fatty liver index in overweight and obese Caucasian adults

Differences in body fat distribution may be a reason for the sex-, age-, and ethnicity-related differences in the prevalence of fatty liver disease (FL). This study aimed to evaluate the sex- and age-related differences in the contribution of visceral (VAT) and subcutaneous (SAT) abdominal fat, measured by ultrasound, to fatty liver index (FLI) in a large sample of overweight and obese Caucasian adults, and to identify the VAT and SAT cut-off values predictive of high FL risk. A cross-sectional study on 8103 subjects was conducted. Anthropometrical measurements were taken and biochemical parameters measured. VAT and SAT were measured by ultrasonography. FLI was higher in men and increased with increasing age, VAT, and SAT. The sex*VAT, age*VAT, sex*SAT, and age*SAT interactions negatively contributed to FLI, indicating a lower VAT and SAT contribution to FLI in men and in the elderly for every 1 cm of increment. Because of this, sex- and age-specific cut-off values for VAT and SAT were estimated. In conclusion, abdominal adipose tissue depots are associated with FLI, but their contribution is sex- and age-dependent. Sex- and age-specific cut-off values of ultrasound-measured VAT and SAT are suggested, but they need to be validated in external populations

Performance of three model-based iterative reconstruction algorithms using a CT task-based image quality metric

In this study we evaluated the task-based image quality of a low contrast clinical task for the abdomen protocol (e.g., pancreatic tumour) of three different CT vendors, exploiting three model-based iterative reconstruction (MBIR) levels. We used three CT systems equipped with a full, partial, advanced MBIR algorithms. Acquisitions were performed on a phantom at three dose levels. Acquisitions were reconstructed with a standard kernel, using filtered back projection algorithm (FBP) and three levels of the MBIR. The noise power spectrum (NPS), the normalized one (nNPS) and the task-based transfer function (TTF) were computed following the method proposed by the American Association of Physicists in Medicine task group report-233 (AAPM TG-233). Detectability index (d') of a small lesion (small feature; 100 HU and 5-mm diameter) was calculated using non-prewhitening with eye-filter model observer (NPWE).The nNPS, NPS and TTF changed differently depending on CT system. Higher values of d' were obtained with advanced-MBIR, followed by full-MBIR and partial-MBIR.Task-based image quality was assessed for three CT scanners of different vendors, considering a clinical question. Detectability can be a tool for protocol optimisation and dose reduction since the same dose levels on different scanners correspond to different d' values.Comment: 7 pages, 5 figures, 3 table

Delta-Radiomics Predicts Response to First-Line Oxaliplatin-Based Chemotherapy in Colorectal Cancer Patients with Liver Metastases

The purpose of this paper is to develop and validate a delta-radiomics score to predict the response of individual colorectal cancer liver metastases (lmCRC) to first-line FOLFOX chemotherapy. Three hundred one lmCRC were manually segmented on both CT performed at baseline and after the first cycle of first-line FOLFOX, and 107 radiomics features were computed by subtracting textural features of CT at baseline from those at timepoint 1 (TP1). LmCRC were classified as nonresponders (R−) if they showed progression of disease (PD), according to RECIST1.1, before 8 months, and as responders (R+), otherwise. After feature selection, we developed a decision tree statistical model trained using all lmCRC coming from one hospital. The final output was a delta-radiomics signature subsequently validated on an external dataset. Sensitivity, specificity, positive (PPV), and negative (NPV) predictive values in correctly classifying individual lesions were assessed on both datasets. Per-lesion sensitivity, specificity, PPV, and NPV were 99%, 94%, 95%, 99%, 85%, 92%, 90%, and 87%, respectively, in the training and validation datasets. The delta-radiomics signature was able to reliably predict R− lmCRC, which were wrongly classified by lesion RECIST as R+ at TP1, (93%, averaging training and validation set, versus 67% of RECIST). The delta-radiomics signature developed in this study can reliably predict the response of individual lmCRC to oxaliplatin-based chemotherapy. Lesions forecasted as poor or nonresponders by the signature could be further investigated, potentially paving the way to lesion-specific therapies

Delta-Radiomics Predicts Response to First-Line Oxaliplatin-Based Chemotherapy in Colorectal Cancer Patients with Liver Metastases

SIMPLE SUMMARY: Oxaliplatin-based chemotherapy remains the mainstay of first-line therapy in patients with metastatic colorectal cancer (mCRC). Unfortunately, only approximately 60% of treated patients achieve response, and half of responders will experience an early onset of disease progression. Furthermore, some individuals will develop a mixed response due to the emergence of resistant tumor subclones. The ability to predicting which patients will acquire resistance could help them avoid the unnecessary toxicity of oxaliplatin therapies. Furthermore, sorting out lesions that do not respond, in the context of an overall good response, could trigger further investigation into their mutational landscape, providing mechanistic insight towards the planning of a more comprehensive treatment. In this study, we validated a delta-radiomics signature capable of predicting response to oxaliplatin-based first-line treatment of individual liver colorectal cancer metastases. Findings could pave the way to a more personalized treatment of patients with mCRC. ABSTRACT: The purpose of this paper is to develop and validate a delta-radiomics score to predict the response of individual colorectal cancer liver metastases (lmCRC) to first-line FOLFOX chemotherapy. Three hundred one lmCRC were manually segmented on both CT performed at baseline and after the first cycle of first-line FOLFOX, and 107 radiomics features were computed by subtracting textural features of CT at baseline from those at timepoint 1 (TP1). LmCRC were classified as nonresponders (R−) if they showed progression of disease (PD), according to RECIST1.1, before 8 months, and as responders (R+), otherwise. After feature selection, we developed a decision tree statistical model trained using all lmCRC coming from one hospital. The final output was a delta-radiomics signature subsequently validated on an external dataset. Sensitivity, specificity, positive (PPV), and negative (NPV) predictive values in correctly classifying individual lesions were assessed on both datasets. Per-lesion sensitivity, specificity, PPV, and NPV were 99%, 94%, 95%, 99%, 85%, 92%, 90%, and 87%, respectively, in the training and validation datasets. The delta-radiomics signature was able to reliably predict R− lmCRC, which were wrongly classified by lesion RECIST as R+ at TP1, (93%, averaging training and validation set, versus 67% of RECIST). The delta-radiomics signature developed in this study can reliably predict the response of individual lmCRC to oxaliplatin-based chemotherapy. Lesions forecasted as poor or nonresponders by the signature could be further investigated, potentially paving the way to lesion-specific therapies

Radiomics predicts response of individual HER2-amplified colorectal cancer liver metastases in patients treated with HER2-targeted therapy

The aim of our study was to develop and validate a machine learning algorithm to predict response of individual HER2-amplified colorectal cancer liver metastases (lmCRC) undergoing dual HER2-targeted therapy. Twenty-four radiomics features were extracted after 3D manual segmentation of 141 lmCRC on pretreatment portal CT scans of a cohort including 38 HER2-amplified patients; feature selection was then performed using genetic algorithms. lmCRC were classified as nonresponders (R−), if their largest diameter increased more than 10% at a CT scan performed after 3 months of treatment, responders (R+) otherwise. Sensitivity, specificity, negative (NPV) and positive (PPV) predictive values in correctly classifying individual lesion and overall patient response were assessed on a training dataset and then validated on a second dataset using a Gaussian naïve Bayesian classifier. Per-lesion sensitivity, specificity, NPV and PPV were 89%, 85%, 93%, 78% and 90%, 42%, 73%, 71% respectively in the testing and validation datasets. Per-patient sensitivity and specificity were 92% and 86%. Heterogeneous response was observed in 9 of 38 patients (24%). Five of nine patients were carriers of nonresponder lesions correctly classified as such by our radiomics signature, including four of seven harboring only one nonresponder lesion. The developed method has been proven effective in predicting behavior of individual metastases to targeted treatment in a cohort of HER2 amplified patients. The model accurately detects responder lesions and identifies nonresponder lesions in patients with heterogeneous response, potentially paving the way to multimodal treatment in selected patients. Further validation will be needed to confirm our findings

Utility of percutaneous lung biopsy for diagnosing filamentous fungal infections in hematologic malignancies

Background and Objectives. The incidence of invasive filamentous fungal infections in hematologic patients is increasing as a consequence of high dose chemotherapy and bone marrow transplant procedures. Mortality is usually very high. The diagnosis is often difficult and yet a fast, accurate diagnosis is of fundamental importance for treating the infection and planning subsequent management of the hematologic disease. We evaluated the sensitivity of computed tomography (CT)-guided percutaneous biopsy in diagnosing pulmonary fungal infections. Design and Methods. Between 1997 and 2002 we performed 17 CT-guided percutaneous transthoracic lung biopsies in 17 hematologic patients with suspected filamentous fungi infection with negative BAL, to obtain a certain diagnosis and to know what species of fungi was responsible for infection. In all cases suspected mycosis began during the post-chemotherapy aplastic period. Patients were receiving antifungal therapy at the time of all biopsies. When the platelet count rose above 50 7109/L, CT-guided percutaneous lung biopsy with fine-needle aspiration for cytology was performed. Results. Twelve of 17 patients had histologic confirmation of the fungal infection (70.5%), 8 with Aspergillus spp. 4 with Mucorales spp. Biopsies provided non-specific results in 4 cases; in 2 of these cases, clinical course and response to therapy confirmed the diagnosis of mycosis; in the last case bronchoalveolar carcinoma was found as a new diagnosis. Cultures were positive in only 6 cases, all for Aspergillus spp. The sensitivity of CT-guided percutaneous lung biopsy was 70.6% and its positive predictive value (PPV) was 100%. This procedure provided an immediate diagnosis and only one side-effect (1 pneumothorax, without complications). Interpretation and Conclusions. Histologic discrimination between aspergillosis and mucormycosis is very important for deciding secondary prophylaxis during transplant procedures, because Mucor is usually resistant to azoles

Performance of the model for end-stage liver disease score for mortality prediction and the potential role of etiology

Background & Aims: Although the discriminative ability of the model for end-stage liver disease (MELD) score is generally considered acceptable, its calibration is still unclear. In a validation study, we assessed the discriminative performance and calibration of 3 versions of the model: original MELD-TIPS, used to predict survival after transjugular intrahepatic portosystemic shunt (TIPS); classic MELD-Mayo; and MELD-UNOS, used by the United Network for Organ Sharing (UNOS). We also explored recalibrating and updating the model. Methods: In total, 776 patients who underwent elective TIPS (TIPS cohort) and 445 unselected patients (non-TIPS cohort) were included. Three, 6 and 12-month mortality predictions were calculated by the 3 MELD versions: discrimination was assessed by c-statistics and calibration by comparing deciles of predicted and observed risks. Cox and Fine and Grey models were used for recalibration and prognostic analyses. Results: In the TIPS/non-TIPS cohorts, the etiology of liver disease was viral in 402/188, alcoholic in 185/130, and non-alcoholic steatohepatitis in 65/33; mean follow-up±SD was 25±9/19±21 months; and the number of deaths at 3-6-12 months was 57-102-142/31-47-99, respectively. C-statistics ranged from 0.66 to 0.72 in TIPS and 0.66 to 0.76 in non-TIPS cohorts across prediction times and scores. A post hoc analysis revealed worse c-statistics in non-viral cirrhosis with more pronounced and significant worsening in the non-TIPS cohort. Calibration was acceptable with MELD-TIPS but largely unsatisfactory with MELD-Mayo and -UNOS whose performance improved much after recalibration. A prognostic analysis showed that age, albumin, and TIPS indication might be used to update the MELD. Conclusions: In this validation study, the performance of the MELD score was largely unsatisfactory, particularly in non-viral cirrhosis. MELD recalibration and candidate variables for an update to the MELD score are proposed. Lay summary: While the discriminative performance of the model for end-stage liver disease (MELD) score is credited to be fair to good, its calibration, the correspondence of observed to predicted mortality, is still unsettled. We found that application of 3 different versions of the MELD in 2 independent cirrhosis cohorts yielded largely imprecise mortality predictions particularly in non-viral cirrhosis. Thus, we propose a recalibration and suggest candidate variables for an update to the model