{"id":20115,"date":"2026-11-12T05:15:44","date_gmt":"2026-11-12T08:15:44","guid":{"rendered":"https:\/\/rtmedical.com.br\/tmp-en-1794471343663\/"},"modified":"2026-11-12T05:15:51","modified_gmt":"2026-11-12T08:15:51","slug":"nacbi-rads-breast-mri-neoadjuvant","status":"publish","type":"post","link":"https:\/\/rtmedical.com.br\/en\/nacbi-rads-breast-mri-neoadjuvant\/","title":{"rendered":"NacBI-RADS: Breast MRI Score Gauges Neoadjuvant Response"},"content":{"rendered":"

NacBI-RADS, a structured reporting score for multiparametric breast MRI, identified pathologic complete response to neoadjuvant chemotherapy more accurately than size-based RECIST 1.1 in a retrospective study of 68 patients published November 10 in European Radiology<\/em>. None of the three radiologists who applied the score labeled a patient as a complete responder when the surgical specimen still contained cancer; with RECIST 1.1, that happened in 9 to 14 patients, depending on the reader.<\/p>\n

Averaged across the three readers, NacBI-RADS reached 86.7% sensitivity (vs. 78.7% for RECIST 1.1), 100% specificity (vs. 73.3%), 100% positive predictive value (PPV, vs. 63.7%) and 92.7% negative predictive value (NPV, vs. 85.7%). The averages, computed by Diagnostic Imaging, match the paper’s per-reader table. The PPV gain, which the outlet described as “over 36 percent,” is a 36.3 percentage-point difference; the other gaps are 8, 26.7 and 7 points.<\/p>\n

\"Bar
NacBI-RADS vs. RECIST 1.1 for recognizing pathologic complete response (mean of three readers). Chart: RT Medical, data from Cicciarelli et al., European Radiology (2026).<\/figcaption><\/figure>\n

How NacBI-RADS was built and tested<\/h2>\n

The work comes from the breast imaging group in the Department of Radiological, Oncological and Pathological Sciences at Sapienza University of Rome, Policlinico Umberto I, with Federica Cicciarelli as first author and Federica Pediconi as the study’s guarantor. The team reviewed patients who completed neoadjuvant chemotherapy between January and September 2025 and had a staging MRI, a post-treatment MRI and surgery. Of 88 patients screened, 20 were excluded for prior surgery or chemotherapy, metastatic disease at baseline, incomplete imaging or no surgery. Among the 68 included (mean age 51.8 years), pathology showed complete response (ypT0\/Tis ypN0) in 25 (36.8%) and residual disease in 43 (63.2%).<\/p>\n

Every exam was acquired on a 3 T scanner with an eight-channel breast coil. The score adds up points from four features: peritumoral edema on fat-suppressed T2-weighted images; the change in apparent diffusion coefficient (\u0394ADC) between baseline and post-treatment scans, measured on diffusion-weighted imaging with b-values of 0, 500 and 1,000 s\/mm\u00b2; tumor size on contrast-enhanced images, measured as in RECIST 1.1; and axillary node status using Node-RADS. The total maps to a category from 1 (complete response) to 5 (progression), with partial-complete response (2), minimal response (3) and stable disease (4) in between.<\/p>\n

Three radiologists with 15, 7 and 5 years of breast imaging experience read all cases independently, blinded to pathology and to one another, and also classified each lesion with RECIST 1.1. Surgical pathology was the reference standard.<\/p>\n

What the numbers show, and what they leave open<\/h2>\n

The area under the ROC curve ranged from 0.942 to 0.960 across readers, and agreement was very high: Cohen’s kappa of 0.931 to 0.953 and an overall Fleiss’ kappa of 0.939. Among the components, tumor size was the most reproducible (kappa 0.936); peritumoral edema and \u0394ADC came in around 0.84, and Node-RADS at 0.867.<\/p>\n

The paper’s accuracy metrics treat complete response as the outcome to be detected. That is why 100% specificity and PPV mean that category 1 was never assigned to a patient with residual disease. RECIST 1.1, by contrast, called complete response in patients who still had tumor in the breast or only in the axilla, and rated as partial response several patients who had no tumor left at surgery. In the other direction, NacBI-RADS missed 3 or 4 of the 25 complete responders, depending on the reader.<\/p>\n

The averages hide one detail. Category 2 was the most used (32 to 35 patients per reader) and absorbed nearly all residual disease: for reader 1, 31 of the 34 patients in that category still had tumor. Because the paper does not report how much residual tumor was present, for example as a residual cancer burden (RCB) index, it is not possible to tell how many of those cases were truly minimal. In practice, the binary metrics mostly test the boundary between category 1 and everything else.<\/p>\n

“In clinical practice, a structured system such as NacBI-RADS could provide radiologists with a standardized framework for reporting post-NAC MRI examinations, facilitating multidisciplinary discussion and supporting surgical decision-making in patients who may be candidates for treatment de-escalation,” Cicciarelli and colleagues write.<\/p>\n

Why tumor size misleads after chemotherapy<\/h2>\n

Pathologic complete response matters because it is associated with better event-free survival, most clearly in triple-negative and HER2-positive tumors, as the CTNeoBC pooled analysis published in The Lancet<\/em> in 2014 showed. RECIST 1.1 looks only at the longest diameter: complete response is disappearance of the lesion, partial response requires at least a 30% decrease, and progression a 20% or greater increase. After chemotherapy, though, fibrosis and scar can keep enhancing and mimic tumor, while some cancers, more often luminal ones, regress by fragmentation and leave scattered foci that MRI does not show. That is why MRI tends to predict complete response more reliably in triple-negative and HER2-positive disease than in luminal tumors. The Rome study did not report results by subtype.<\/p>\n

The other components try to capture treatment biology. ADC reflects how freely water moves in tissue: highly cellular tumors restrict diffusion and have low ADC, and treatment-induced cell death tends to raise the value before the tumor shrinks. The authors treated a 20% to 25% increase as a favorable signal, based on earlier work that includes the multicenter ACRIN 6698 trial. In the paper’s examples, one patient with triple-negative cancer had an 88.6% rise in ADC and no residual enhancement (category 1); another had only a 16% rise and a tumor that grew from 28 to 33 mm (category 5).<\/p>\n

According to the authors, peritumoral edema on T2 may reflect more aggressive biology, while Node-RADS, proposed in 2021, grades suspicion of nodal involvement on a five-point scale. The approach fits with the BI-RADS v2025 edition and its new section on axillary lymph nodes<\/a>, and with the push toward non-contrast breast MRI, where diffusion plays a central role<\/a>.<\/p>\n

Surgical de-escalation: where a score like this could fit<\/h2>\n

The authors see a role in surgical planning: extent of resection, the choice between breast-conserving surgery and mastectomy, and axillary management. Here it helps to separate practice from research. Less extensive axillary surgery for selected patients whose nodes convert to negative after neoadjuvant therapy already appears in guidelines. Omitting breast surgery in patients with an image-guided biopsy showing complete response, however, remains limited to clinical trials, and no imaging score, NacBI-RADS included, has been validated for that decision.<\/p>\n

Response assessment is moving on other fronts too, such as HER2-targeted PET\/CT to predict complete response<\/a>. The practical advantage of NacBI-RADS is that it relies on sequences already in a full breast MRI protocol (T2, diffusion and dynamic contrast-enhanced imaging), with no new hardware. For centers that follow neoadjuvant patients with MRI, the harder issue is that ADC varies with vendor, field strength, b-values and region-of-interest (ROI) placement. A 20% threshold calibrated on a single 3 T scanner should not be transferred without harmonizing protocols and auditing local results against pathology.<\/p>\n

Study limitations and what to watch<\/h2>\n

The authors call the work exploratory. It is retrospective and single-center, with 68 patients and one scanner. The same readers applied both NacBI-RADS and RECIST 1.1, and tumor size, the basis of RECIST, is also one of the score’s four components. The weight of each parameter was not analyzed separately, and the cutoffs still need testing in an independent population. The paper acknowledges that differences in b-values, readout technique and ROI placement change \u0394ADC, and calls for prospective multicenter validation with long-term outcomes before the score is used to tailor therapy or reduce surgery.<\/p>\n

In a commentary published the same day in European Radiology<\/em>, Marina \u00c1lvarez-Benito of the Breast Cancer Unit at Reina Sof\u00eda University Hospital in C\u00f3rdoba, Spain, notes that no reader assigned category 1 to a patient with residual disease, but that “there is still room for improvement in identifying all women who achieved complete pathological response.” She suggests scoring breast and axilla separately, adding axillary ultrasound and clinical and molecular data, and expects radiomics and AI to contribute, an area where regulated products already exist, such as the breast MRI-based tool the FDA cleared to estimate recurrence risk<\/a>. The next question is whether NacBI-RADS holds up across other centers, scanners and tumor subtypes.<\/p>\n

Source:<\/strong> Diagnostic Imaging \u2014 Could an Emerging NacBI-RADS System for mpMRI Bolster Assessment of NAC Response?<\/a>. Original paper: Cicciarelli F et al., European Radiology (2026)<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

NacBI-RADS, a structured breast MRI score, beat RECIST 1.1 at flagging complete response to neoadjuvant chemotherapy in 68 patients. See the data.<\/p>\n","protected":false},"author":5,"featured_media":20067,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"ngg_post_thumbnail":0,"_rt_cluster":"","fifu_image_url":"","fifu_image_alt":"","footnotes":""},"categories":[100],"tags":[],"class_list":["post-20115","post","type-post","status-publish","format-standard","has-post-thumbnail","category-radiology"],"aioseo_notices":[],"rt_seo":{"title":"","description":"NacBI-RADS, a structured breast MRI score, beat RECIST 1.1 at flagging complete response to neoadjuvant chemotherapy in 68 patients. See the data.","canonical":"","og_image":"","robots":"index,follow","schema_type":"Article","include_in_llms":true,"llms_label":"NacBI-RADS multiparametric breast MRI score for neoadjuvant response","llms_summary":"A retrospective Sapienza study (European Radiology, 2026; 68 patients, 3 readers) found NacBI-RADS, which combines peritumoral edema, \u0394ADC, post-contrast size and Node-RADS, recognized pathologic complete response with 100% specificity and PPV vs 73.3% and 63.7% for RECIST 1.1; AUC 0.942-0.960, kappa 0.931-0.953.","faq_items":[],"video":[],"gtin":"","mpn":"","brand":"","aggregate_rating":[]},"_links":{"self":[{"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/posts\/20115\/"}],"collection":[{"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/posts\/"}],"about":[{"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/types\/post\/"}],"author":[{"embeddable":true,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/users\/5\/"}],"replies":[{"embeddable":true,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/comments\/?post=20115"}],"version-history":[{"count":1,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/posts\/20115\/revisions\/"}],"predecessor-version":[{"id":20119,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/posts\/20115\/revisions\/20119\/"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/media\/20067\/"}],"wp:attachment":[{"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/media\/?parent=20115"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/categories\/?post=20115"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rtmedical.com.br\/en\/wp-json\/wp\/v2\/tags\/?post=20115"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}