Neoadjuvant chemotherapy (NAC) is becoming the standard of care for locally advanced breast cancer, aiming to reduce tumor size before surgery. Unfortunately, less than 30% of patients generally achieve a pathological complete response and approximately 5% of patients show disease progression while receiving NAC. Accurate assessment of the response to NAC is crucial for subsequent surgical planning. Furthermore, early prediction of tumor response could avoid patients being overtreated with useless chemotherapy sections, which are not free from side effects and psychological implications. In this review, we first analyze and compare the accuracy of conventional and advanced imaging techniques as well as discuss the application of artificial intelligence tools in the assessment of tumor response after NAC. Thereafter, the role of advanced imaging techniques, such as MRI, nuclear medicine, and new hybrid PET/MRI imaging in the prediction of the response to NAC is described in the second part of the review. Finally, future perspectives in NAC response prediction, represented by AI applications, are discussed.

Imaging plays a crucial role in the management of oncologic patients, from the initial diagnosis to staging and treatment response monitoring. Recently, it has been suggested that its importance could be further increased by accessing a new layer of previously hidden quantitative data at the pixel level. Using a multi-step process, radiomics extracts potential biomarkers from medical images that could power decision support tools. Despite the growing interest and rising number of research articles being published, radiomics is still far from fulfilling its promise of guiding oncologic imaging toward personalized medicine. This is, at least partly, due to the heterogeneous methodological quality in radiomic research, caused by the complexity of the analysis pipelines. In this review, we aim to disentangle this complexity with a stepwise approach. Specifically, we focus on challenges to face during image preprocessing and segmentation, how to handle imbalanced classes and avoid information leaks, as well as strategies for the proper validation of findings.

Background: Differentiated thyroid cancer (DTC) patients have an outstanding overall long-term survival rate, and certain subsets of DTC patients have a very high likelihood of disease recurrence. Radioactive iodine (RAI) therapy is a cornerstone in DTC management, but cancer cells can eventually develop resistance to RAI. Radioactive iodine-refractory DTC (RAIR-DTC) is a condition defined by ATA 2015 guidelines when DTC cannot concentrate RAI ab initio or loses RAI uptake ability after the initial therapy. The RAIR condition implies that RAI cannot reveal new met-astatic foci, so RAIR-DTC metabolic imaging needs new tracers. ¹⁸F-FDG PET/CT has been widely used and has demonstrated prognostic value, but ¹⁸F-FDG DTC avidity may remain low. Fibroblast activation protein inhibitors (FA-Pi)s, prostatic-specific membrane antigen (PSMA), and somatostatin receptor (SSTR) tracers have been proposed as theragnostic agents in experimental settings and Arg-Gly-Asp (RGD) peptides in the diagnostic trial field. Multi-targeted tyrosine kinase inhibitors are relatively new drugs approved in RAIR-DTC therapy. Despite the promising targeted setting, they relate to frequent adverse-event onset. Sorafenib and trametinib have been included in re-differentiation protocols aimed at re-inducing RAI accumulation in DTC cells. Results appear promising, but not excellent. Conclusions: RAIR-DTC remains a challenging nosological entity. There are still controversies on RAIR-DTC definition and post-RAI therapy evaluation, with post-therapy whole-body scan (PT-WBS) the only validated criterion of response. The recent introduction of multiple diagnostic and therapeutic agents obliges physicians to pursue a multidisciplinary approach aiming to correct drug introduction and timing choice.

Cystic lymphangioma is a rare benign lesion derived from the detachment of the lymph sacs from venous drainage systems; the treatment of choice is a surgical excision and the final diagnosis is of histological type. To compare the results of ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI) in patients with cystic lymphangioma to clearly evaluate the anatomic as well as the structural lesion features necessary for differential diagnosis and for the patient treatment planning. We analyzed the imaging results of six patients admitted in our department to evaluate cyst-like tumor masses clinically palpable or detected by US. All the patients underwent US, CT, and MRI. The pathology reports demonstrated a mesenterial cystic lymphangioma in five cases underwent surgical resection and in the last case a chest cystic lymphangioma underwent a fine needle aspiration biopsy (FNAB). In all the cases, the results of US, CT, and MRI were concordant showing cyst-like tumor masses in the abdomen (n = 5) and chest (n = 1) ranging in size from 3.5 to 15 cm. According to our experience, we suggest that the appropriate diagnostic imaging protocol in patients with cystic lymphangioma should initially include the US study and followed by a MRI scan with contrast administration. CT should be avoided because of radiation exposure. US and MRI may also be useful in the follow-up of patients who refuse surgical resection or in whom surgery is contraindicated or postponed as well as to early detect a possible disease relapse.