eprintid: 10186604 rev_number: 8 eprint_status: archive userid: 699 dir: disk0/10/18/66/04 datestamp: 2024-02-05 14:22:16 lastmod: 2024-12-23 07:10:06 status_changed: 2024-02-05 14:22:16 type: article metadata_visibility: show sword_depositor: 699 creators_name: Ponomarchuk, E creators_name: Thomas, G creators_name: Song, M creators_name: Krokhmal, A creators_name: Kvashennikova, A creators_name: Wang, YN creators_name: Khokhlova, V creators_name: Khokhlova, T title: Histology-based quantification of boiling histotripsy outcomes via ResNet-18 network: Towards mechanical dose metrics ispublished: pub divisions: UCL divisions: B04 divisions: C05 divisions: F42 keywords: High intensity focused, ultrasound, Non-invasive surgery, Boiling histotripsy, Histology, Computer vision, Neural network note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: This work was focused on the newly developed ultrasonic approach for non-invasive surgery – boiling histotripsy (BH) – recently proposed for mechanical ablation of tissues using pulsed high intensity focused ultrasound (HIFU). The BH lesion is known to depend in size and shape on exposure parameters and mechanical properties, structure and composition of tissue being treated. The aim of this work was to advance the concept of BH dose by investigating quantitative relationships between the parameters of the lesion, pulsing protocols, and targeted tissue properties. A HIFU focus of a 1.5 MHz 256-element array driven by power-enhanced Verasonics system was electronically steered along the grid within 12 × 4 × 12 mm volume to produce volumetric lesions in porcine liver (soft, with abundant collagenous structures) and bovine myocardium (stiff, homogenous cellular) ex vivo tissues with various pulsing protocols (1–10 ms pulses, 1–15 pulses per point). Quantification of the lesion size and completeness was performed through serial histological sectioning, and a computer vision approach using a combination of manual and automated detection of fully fractionated and residual tissue based on neural network ResNet-18 was developed. Histological sample fixation led to underestimation of BH ablation rate compared to the ultrasound-based estimations, and provided similar qualitative feedback as did gross inspection. This suggests that gross observation may be sufficient for qualitatively evaluating the BH treatment completeness. BH efficiency in liver tissue was shown to be insensitive to the changes in pulsing protocol within the tested parameter range, whereas in bovine myocardium the efficiency increased with either increasing pulse length or number of pulses per point or both. The results imply that one universal mechanical dose metric applicable to an arbitrary tissue type is unlikely to be established. The dose metric as a product of the BH pulse duration and the number of pulses per sonication point (BHD1) was shown to be more relevant for initial planning of fractionation of collagenous tissues. The dose metric as a number of pulses per point (BHD2) is more suitable for the treatment planning of softer targets primarily containing cellular tissue, allowing for significant acceleration of treatment using shorter pulses. date: 2024-03-01 date_type: published publisher: Elsevier BV official_url: http://dx.doi.org/10.1016/j.ultras.2023.107225 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 2136747 doi: 10.1016/j.ultras.2023.107225 lyricists_name: Krokhmal, Alisa lyricists_id: AKROK08 actors_name: Krokhmal, Alisa actors_id: AKROK08 actors_role: owner full_text_status: public publication: Ultrasonics volume: 138 article_number: 107225 issn: 0041-624X citation: Ponomarchuk, E; Thomas, G; Song, M; Krokhmal, A; Kvashennikova, A; Wang, YN; Khokhlova, V; Ponomarchuk, E; Thomas, G; Song, M; Krokhmal, A; Kvashennikova, A; Wang, YN; Khokhlova, V; Khokhlova, T; - view fewer <#> (2024) Histology-based quantification of boiling histotripsy outcomes via ResNet-18 network: Towards mechanical dose metrics. Ultrasonics , 138 , Article 107225. 10.1016/j.ultras.2023.107225 <https://doi.org/10.1016/j.ultras.2023.107225>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10186604/1/BHdoseRevised_13Dec2023.pdf