[(18)F]FDG-PET/CT metabolic parameters as useful prognostic factors in cervical cancer patients treated with chemo-radiotherapy.

To compare the prognostic value of different anatomical and functional metabolic parameters determined using [(18)F]FDG-PET/CT with other clinical and pathological prognostic parameters in cervical cancer (CC). Thirty-eight patients treated with standard curative doses of chemo-radiotherapy (CRT) underwent pre- and post-therapy [(18)F]FDG-PET/CT. [(18)F]FDG-PET/CT parameters including mean tumor standardized uptake values (SUV), metabolic tumor volume (MTV) and tumor glycolytic volume (TGV) were measured before the start of CRT. The post-treatment tumor metabolic response was evaluated. These parameters were compared to other clinical prognostic factors. Survival curves were estimated by using the Kaplan-Meier method. Cox regression analysis was performed to determine the independent contribution of each prognostic factor. After 37 months of median follow-up (range, 12-106), overall survival (OS) was 71 % [95 % confidence interval (CI), 54-88], disease-free survival (DFS) 61 % [95 % CI, 44-78] and loco-regional control (LRC) 76 % [95 % CI, 62-90]. In univariate analyses the [(18)F]FDG-PET/CT parameters unfavorably influencing OS, DFS and LRC were pre-treatment TGV-cutoff ≥562 (37 vs. 76 %, p = 0.01; 33 vs. 70 %, p = 0.002; and 55 vs. 83 %, p = 0.005, respectively), mean pre-treatment tumor SUV cutoff ≥5 (57 vs. 86 %, p = 0.03; 36 vs. 88 %, p = 0.004; 65 vs. 88 %, p = 0.04, respectively) and a partial tumor metabolic response after treatment (9 vs. 29 %, p = 0.0008; 0 vs. 83 %, p < 0.0001; 22 vs. 96 %, p < 0.0001, respectively). After multivariate analyses a partial tumor metabolic response after treatment remained as an independent prognostic factor unfavorably influencing DFS and LRC (RR 1:7.7, p < 0.0001, and RR 1:22.6, p = 0.0003, respectively) while the pre-treatment TGV-cutoff ≥562 negatively influenced OS and DFS (RR 1:2, p = 0.03, and RR 1:2.75, p = 0.05). Parameters capturing the pre-treatment glycolytic volume and metabolic activity of [(18)F]FDG-positive disease provide important prognostic information in patients with CC treated with CRT. The post-therapy [(18)F]FDG-PET/CT uptake (partial tumor metabolic response) is predictive of disease outcome

Automatic extraction of recurrent patterns of high dominant frequency mapping during human persistent atrial fibrillation

Purpose: Identifying targets for catheter ablation remains challenging in persistent atrial fibrillation (persAF). The dominant frequency (DF) of atrial electrograms during atrial fibrillation (AF) is believed to primarily reflect local activation. Highest DF (HDF) might be responsible for the initiation and perpetuation of persAF. However, the spatiotemporal behaviour of DF remains not fully understood. Some DFs during persAF were shown to lack spatiotemporal stability, while others exhibit recurrent behaviour. We sought to develop a tool to automatically detect recurrent DF patterns in persAF patients. Methods: Non-contact mapping of the left atrium (LA) was performed in 10 patients undergoing persAF HDF ablation. 2048 virtual electrograms (vEGMs, EnSite Array, Abbott Laboratories, USA) were collected for up to 5 min before and after ablation. Frequency spectrum was estimated using fast Fourier transform and DF was identified as the peak between 4-10 Hz and organization index (OI) was calculated. The HDF maps were identified per 4-second window and an automated pattern recognition algorithm was used to find recurring HDF spatial patterns. Dominant patterns (DPs) were defined as the HDF pattern with the highest recurrence. Results: DPs were found in all patients. Patients in atrial flutter after ablation had a single DP over the recorded time period. The time interval (median [IQR]) of DP recurrence for the patients in AF after ablation (7 patients) decreased from 21.1 s [11.8 49.7s] to 15.7 s [6.5 18.2 s]. The DF inside the DPs presented lower temporal standard deviation (0.18±0.06 Hz vs. 0.29±0.12 Hz, p<0.05) and higher OI (0.35±0.03 vs. 0.31±0.04, p<0.05). The atrial regions with the highest proportion of HDF region were the septum and the left upper pulmonary vein. Conclusion: Multiple recurrent spatiotemporal HDF patterns exist during persAF. The proposed method can identify and quantify the spatiotemporal repetition of the HDFs, where the high recurrences of DP may suggest a more organised rhythm. DPs presented a more consistent DF and higher organisation compared with non-DPs, suggesting that DF with higher OI might be more likely to recur. Recurring patterns offer a more comprehensive dynamic insight of persAF behaviour, and ablation targeting such regions may be beneficial

A K-Nearest Neighbour Classifier for Predicting Catheter Ablation Responses Using Noncontact Electrograms During Persistent Atrial Fibrillation

The mechanisms for the initiation and maintenance of atrial fibrillation (AF) are still poorly understood. Identification of atrial sites which are effective ablation targets remains challenging. Supervised machine learning has emerged as an effective tool for handling classification problems with multiple features. The main goal of this work is to use learning algorithms in predicting the responses of ablating electrograms and their effect on terminating AF and the cycle length changes. A total of 3,206 electrograms (EGMs) from ten persistent AF (persAF) patients were used. 5-fold cross-validation was applied, in which 80 % of the data were used as training set and 20 % used as validation. Dominant frequency (DF) and organisation index (OI) were calculated from EGMs (264 seconds) for all patients and used as input features. A k-nearest neighbour (KNN) classifier was trained using ablation lesion data and deployed in additional 17,274 EGMs that were not ablated. The classification accuracy of 85.2 % was achieved for the KNN classifier. We have proposed a supervised learning algorithm using DF features, which has shown the ability of accurately performing EGM signal classification that could be potentially used to identify ablation targets and become a robust real-time patient diagnosis system

Dominant Frequency Variability Mapping for Identifying Stable Drivers during Persistent Atrial Fibrillation using Non‐Contact Mapping

Catheter ablation is a widely-used therapy to treat atrial fibrillation (AF), but the identification of ablation targets remain challenging in persistent AF (persAF). Dominant frequency (DF) mapping has been shown to be spatiotemporally unstable in persAF, with DF variability (DFV) correlating with the spectral organisation index (OI). This study aims to assess DFV at ablation sites between patients with AF termination and non-termination. 10 persAF patients undergoing LA ablation were enrolled. AF was terminated in 4 patients after ablating highest DFs. 2048-channel virtual electrograms (Ensite Array) were analysed in Matlab. DFV index (DFVI) was proposed to quantify DF temporal stability. Mock ablation targets were identified based on DFVI and the percentage of region actually ablated was computed. Ablation sites in termination patients revealed higher OI and lower DFVI. In the termination group, a greater proportion of DFVI was ablated. Atrial regions with higher temporal stability and organisation may offer more precise locations of stable focal drivers and may lead to higher success in AF termination following ablation

Dominant Frequency Variability Mapping for Identifying Stable Drivers during Persistent Atrial Fibrillation using Non‐Contact Mapping

Catheter ablation is a widely-used therapy to treat atrial fibrillation (AF), but the identification of ablation targets remain challenging in persistent AF (persAF). Dominant frequency (DF) mapping has been shown to be spatiotemporally unstable in persAF, with DF variability (DFV) correlating with the spectral organisation index (OI). This study aims to assess DFV at ablation sites between patients with AF termination and non-termination. 10 persAF patients undergoing LA ablation were enrolled. AF was terminated in 4 patients after ablating highest DFs. 2048-channel virtual electrograms (Ensite Array) were analysed in Matlab. DFV index (DFVI) was proposed to quantify DF temporal stability. Mock ablation targets were identified based on DFVI and the percentage of region actually ablated was computed. Ablation sites in termination patients revealed higher OI and lower DFVI. In the termination group, a greater proportion of DFVI was ablated. Atrial regions with higher temporal stability and organisation may offer more precise locations of stable focal drivers and may lead to higher success in AF termination following ablation

Characteristics of Ablated Rotors in Terminating Persistent Atrial Fibrillation Using Non-Contact Mapping

Early data has shown beneficial outcomes after rotor-guided catheter ablation in persistent atrial fibrillation (persAF). We aim to investigate the rotor characteristics at ablation sites that terminated AF (terminators) compared to those at sites that did not (non-terminators)