Dataset Information

Machine Learning Prediction of Radiofrequency Thermal Ablation Efficacy: A New Option to Optimize Thyroid Nodule Selection.

ABSTRACT:

Background

Radiofrequency (RF) is a therapeutic modality for reducing the volume of large benign thyroid nodules. If thermal therapies are interpreted as an alternative strategy to surgery, critical issues in their use are represented by the extent of nodule reduction and by the durability of nodule reduction over a long period of time.

Objective

To assess the ability of machine learning to discriminate nodules with volume reduction rate (VRR) < or ?50% at 12 months following RF treatment.

Methods

A machine learning model was trained with a dataset of 402 cytologically benign thyroid nodules subjected to RF at six Italian Institutions. The model was trained with the following variables: baseline nodule volume, echostructure, macrocalcalcifications, vascularity, and 12-month VRR.

Results

After training, the model could distinguish between nodules having VRR <50% from those having VRR ?50% in 85% of cases (accuracy: 0.85; 95% confidence interval [CI]: 0.80-0.90; sensitivity: 0.70; 95% CI: 0.62-0.75; specificity: 0.99; 95% CI: 0.98-1.0; positive predictive value: 0.95; 95% CI: 0.92-0.98; negative predictive value: 0.95; 95% CI: 0.92-0.98).

Conclusions

This study demonstrates that a machine learning model can reliably identify those nodules that will have VRR < or ?50% at 12 months after one RF treatment session. Predicting which nodules will be poor or good responders represents valuable data that may help physicians and patients decide on the best treatment option between thermal ablation and surgery or in predicting if more than one session might be necessary to obtain a significant volume reduction.

SUBMITTER: Negro R

PROVIDER: S-EPMC7445654 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Publications

Machine Learning Prediction of Radiofrequency Thermal Ablation Efficacy: A New Option to Optimize Thyroid Nodule Selection.

Negro Roberto R Rucco Matteo M Creanza Annalisa A Mormile Alberto A Limone Paolo Piero PP Garberoglio Roberto R Spiezia Stefano S Monti Salvatore S Cugini Christian C El Dalati Ghassan G Deandrea Maurilio M

European thyroid journal 20191219 4

<h4>Background</h4>Radiofrequency (RF) is a therapeutic modality for reducing the volume of large benign thyroid nodules. If thermal therapies are interpreted as an alternative strategy to surgery, critical issues in their use are represented by the extent of nodule reduction and by the durability of nodule reduction over a long period of time.<h4>Objective</h4>To assess the ability of machine learning to discriminate nodules with volume reduction rate (VRR) < or ≥50% at 12 months following RF t ...[more]

PMID: 32903883

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Project description:BackgroundSince its inception, the Bethesda System for Reporting Thyroid Cytopathology (TBS) has been widely adopted. Each category conveys a risk of malignancy and recommended next steps, though it is unclear if each category also predicts the type and extent of malignancy. If so, this would greatly expand the utility of the TBS by providing prognostic information in addition to baseline cancer risk.MethodsAll patients prospectively enrolled into the authors' thyroid nodule database from 1995 to 2013 with histologically proven malignancy were analyzed. The primary ultrasound-guided fine-needle aspiration cytology (AUS, atypia of unknown significance; FN, follicular neoplasm; SUSP, suspicious; M, malignant) was correlated with the type of thyroid cancer and histological features known to impact prognosis and recurrence, including lymph node metastasis (LNM), lymphovascular invasion, and extrathyroidal extension (ETE). Primary cytology was separately correlated with higher risk malignancy.ResultsA total of 1291 malignancies were identified, with primary cytology AUS in 130 cases, FN in 241 cases, SUSP in 411 cases, and M in 509 cases. AUS, SUSP, and M cytology were progressively associated with an increasing risk of high-risk disease (p?<?0.001), LNM (p?<?0.001), ETE (p?<?0.001), and margin positivity (p?<?0.001). Notably, 71% of malignancies with AUS cytology were follicular variants of papillary thyroid cancer compared with 63% with SUSP cytology and only 20% with M cytology. In contrast, high-risk malignancies were diagnosed in only 4% with AUS cytology, but 9% and 27% with SUSP and M cytology, respectively. FN conveyed a significantly increased risk of follicular thyroid carcinoma compared with all other types (28% vs. 2%; p?<?0.001). A composite endpoint of recurrence, distant metastases, and death similarly increased as cytology progressed from AUS to SUSP to M (p?<?0.001).ConclusionIn addition to predicting cancer prevalence, the TBS also imparts important prognostic information about cancer type, variant, and risk of recurrence. These data extend the utility of TBS classification by fostering an improved understanding of the risk posed by any confirmed malignancy.

Project description:BackgroundMinimal invasive methods are needed as an alternative to surgery for treatment of lung metastases.Patients and methodsThe prospective database of two cancer centers including all consecutive patients treated with radiofrequency ablation (RFA) for lung metastasis over 8 years was reviewed. RFA was carried out under general anesthesia, with computed tomography guidance using a 15-gauge multitined expandable electrodes RF needle.ResultsFive hundred sixty-six patients including 290 men (51%), 62.7 ± 13.2 years old with primary tumor to the colon (34%), rectum (18%), kidney (12%), soft tissue (9%) and miscellaneous (27%) received 642 RFA for 1037 lung metastases. Fifty-three percent of patients had 1 metastasis, 25% had 2, 14% had 3, 5% had 4 and 4% had 5-8. Metastases were unilateral (75%), or bilateral (25%). The median diameter [extremes] of metastases was 15 mm (4-70). Twenty-two percent of patients had extrapulmonary disease amenable to local therapy including 49 liver, 16 bone and 60 miscellaneous metastases. Median follow-up was 35.5 months. Median overall survival (OS) was 62 months. Four-year local efficacy was 89%. Four-year lung disease control rate was 44.1%, with patient retreated safely up to four times. Primary origin, disease-free interval, size and number of metastases were associated with OS in multivariate analysis. Progression at RFA site was associated with poor OS [P = 0.011, hazard ratio (HR): 1.69 (95% confidence interval 1.13-2.54)]. In the 293 colorectal cancer metastases, size >2 cm (HR = 2.10, P = 0.0027) and a number of metastases ?3 (HR = 1.86, P = 0.011) remained significantly associated with OS. A prognostic score made of three groups based on the four above-mentioned prognostic factors demonstrated 3-year OS rates of respectively 82.2%, 69.5% and 53.6% (log-rank test, P ? 0.0001) among the three groups in the overall population, and of 81.3%, 72.8% and 57.9% (log-rank test, P = 0.005) in the colorectal cancer patients.ConclusionRadiofrequency is an option for treatment of small size lung metastases, namely the ones below 2-3 cm.

Dataset Information

Machine Learning Prediction of Radiofrequency Thermal Ablation Efficacy: A New Option to Optimize Thyroid Nodule Selection.

Background

Objective

Methods

Results

Conclusions

Publications

Machine Learning Prediction of Radiofrequency Thermal Ablation Efficacy: A New Option to Optimize Thyroid Nodule Selection.

Similar Datasets

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