Ex vivo and in vivo evaluation of laser‐induced thermotherapy for nodular thyroid disease

Ritz, J.‐P.; Lehmann, Kai S.; Zurbuchen, Urte; Knappe, Verena; Schumann, Thomas; Buhr, H. J.; Holmer, Christoph

doi:10.1002/lsm.20805

Cited by 23 publications

(13 citation statements)

References 37 publications

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“…In addition to quantitative measures such as nodule volume and delivered energy, structural features are also crucial. Both with RA and L, spongiform appearance of the nodule and intranodular vascularity are associated with a better response, probably because heat spreads more thoroughly than in compact nodules and periphery-only vascularized nodules [9,16,30].…”

Section: Discussionmentioning

confidence: 99%

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

Negro¹,

Rucco²,

Creanza³

et al. 2019

Eur Thyroid J

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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.

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Section: Discussionmentioning

confidence: 99%

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

Negro¹,

Rucco²,

Creanza³

et al. 2019

Eur Thyroid J

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“…This finding was enforced by the evidence that those patients who underwent surgery for nodule's enlargement more frequently carried a solid nodule. The clue that LA performed better in spongiform than solid nodules certainly needs more confirmation, but it may be logically explained by the different densities of the nodules treated with elevated temperature [26]. It may be speculated that solid nodules, due to their compactness, attenuate the heat diffusion more than spongiform ones; indeed, the thermal energy required to induce cell death varies in different tissues.…”

Section: Discussionmentioning

confidence: 99%

Laser ablation is more effective for spongiform than solid thyroid nodules. A 4-year retrospective follow-up study

Negro

Salem

Greco

2016

International Journal of Hyperthermia

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“…Cell death may continue for up to 72 hours after a procedure because of coagulation of microvessels and ischemic injury (41). Microscopically, the coagulation zone is surrounded by a rim of dense fibrotic tissue that separates necrotic from viable tissue (40, 42-44) (Fig. 11).…”

Section: Introductionmentioning

confidence: 99%

Thermal Ablation for Benign Thyroid Nodules: Radiofrequency and Laser

et al. 2011

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Although ethanol ablation has been successfully used to treat cystic thyroid nodules, this procedure is less effective when the thyroid nodules are solid. Radiofrequency (RF) ablation, a newer procedure used to treat malignant liver tumors, has been valuable in the treatment of benign thyroid nodules regardless of the extent of the solid component. This article reviews the basic physics, techniques, applications, results, and complications of thyroid RF ablation, in comparison to laser ablation.

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Ex vivo and in vivo evaluation of laser‐induced thermotherapy for nodular thyroid disease

Abstract: This study is the first to demonstrate a dose-response relationship for LITT of thyroid tissue. LITT is suitable for singular thyroid nodules and induces reproducible clinically relevant lesions with irreversible cell damage in an appropriate application time.

Cited by 23 publications

References 37 publications

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

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

Laser ablation is more effective for spongiform than solid thyroid nodules. A 4-year retrospective follow-up study

Thermal Ablation for Benign Thyroid Nodules: Radiofrequency and Laser

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